How to put AI ethics into practice? AI Human Impact

Original recording ↗

Back to CV · Download Markdown

Investing in human impact

Question is how to put AI ethics into practice. Well, here's one way. We can make it possible for people to invest in technology companies where AI conforms to humans instead of having humans conform to the AI.

And to do that, what we need is a model for objectively scoring AI-intensive businesses. I mean those companies that have artificial intelligence working at the core of their business operation. We need a way of scoring them on a humanitarian scale.

Investment direction — original presentation slide
Presentation slide · Investment direction
Source details

Speech references

  1. 00:05.430–00:25.710
  2. 00:25.950–00:46.330

Opening question

Original display: 00:01.480–00:05.400
Selected frame: 00:05. Reading placement is editorial; display times are unchanged.

Original presentation frame: Opening question

Displayed title-card wording:

How to put AI ethics into practice?

Exact Markdown and source mapping

DISC-0064-VIS-001

**Displayed title-card wording:**

> How to put AI ethics into practice?
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-001",
    "state_id": "DISC-0064-VIS-001",
    "heading": "Opening question",
    "frame_source": "../frames/DISC-0064-VIS-001.jpg",
    "frame_sha256": "ccb55a0f28e55861510cccfe02a27d3649977702d446803428f74d99ff1a98c5",
    "frame_pts_seconds": 5,
    "display_intervals": [
      {
        "start_seconds": 1.48,
        "end_seconds": 5.4,
        "duration_seconds": 3.92,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": false,
    "substantive_exception": "Source question framing; substantive short-card exception.",
    "placement_after": "START",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed title-card wording:**\n\n> How to put AI ethics into practice?",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-001.jpg",
        "original_evidence_image_sha256": "16db57f10e77011d6bc56a14e795129e27ed0a8e40ba87eddd85f09765ca8df9",
        "original_evidence_pts_seconds": 1.48,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\scene_scan\\cut-01-1.480.jpg",
        "evaluated_slide_markdown_sha256": "13677ac496282cba71fbe41b481c069967f45aec2dd964b099ee98c66ae49451",
        "evaluated_placement_after": "START",
        "placement_assessment": "Before opening question; actual title card immediately precedes speech.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": null
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "markdown_span": {
      "char_start": 276,
      "char_end": 533,
      "utf8_start": 278,
      "utf8_end": 535,
      "line_start": 7,
      "line_end": 17,
      "exact_text": "<!-- DISC-0064-VIS-001 | display timing in companion; reading placement is editorial -->\n\n### Opening question\n\n![Original video frame at 00:05.000](../frames/DISC-0064-VIS-001.jpg)\n\n**Displayed title-card wording:**\n\n> How to put AI ethics into practice?\n\n",
      "text_sha256": "33ba715e69bc64cb188ea567abd6f2f7ac1a7de40d4b4b6a9bf8c1a35fc9d07c"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P001",
      "word_span": [
        0,
        38
      ],
      "text": "Question is how to put AI ethics into practice. Well, here's one way. We can make it possible for people to invest in technology companies where AI conforms to humans instead of having humans conform to the AI.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00001",
        "DISC-0064-RUN-20261031-01-SEG-00002",
        "DISC-0064-RUN-20261031-01-SEG-00003"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0005"
      ],
      "original_start_seconds": 5.43,
      "original_end_seconds": 25.71,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 599,
        "char_end": 809,
        "utf8_start": 603,
        "utf8_end": 813,
        "line_start": 19,
        "line_end": 19,
        "exact_text": "Question is how to put AI ethics into practice. Well, here's one way. We can make it possible for people to invest in technology companies where AI conforms to humans instead of having humans conform to the AI.",
        "text_sha256": "8deb934be2e45ed13a07b3d97ed88e1172e61283e982bb6890a0dc167b47d27f"
      }
    },
    {
      "passage_id": "DISC-0064-P002",
      "word_span": [
        38,
        82
      ],
      "text": "And to do that, what we need is a model for objectively scoring AI-intensive businesses. I mean those companies that have artificial intelligence working at the core of their business operation. We need a way of scoring them on a humanitarian scale.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00003",
        "DISC-0064-RUN-20261031-01-SEG-00004",
        "DISC-0064-RUN-20261031-01-SEG-00005",
        "DISC-0064-RUN-20261031-01-SEG-00006"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0001"
      ],
      "original_start_seconds": 25.95,
      "original_end_seconds": 46.33,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 1245,
        "char_end": 1494,
        "utf8_start": 1251,
        "utf8_end": 1500,
        "line_start": 36,
        "line_end": 36,
        "exact_text": "And to do that, what we need is a model for objectively scoring AI-intensive businesses. I mean those companies that have artificial intelligence working at the core of their business operation. We need a way of scoring them on a humanitarian scale.",
        "text_sha256": "d69b732364985f2e893b340dfa6666bf06ea2edd1a8d48e6b4244fc042fbf486"
      }
    }
  ]
}

Investment direction

Original display: 00:19.520–00:26.800
Selected frame: 00:20. Reading placement is editorial; display times are unchanged.

Open the full slide image

Displayed presentation wording:

AI HUMAN IMPACT INVESTING
Invest in those technology companies
where the AI conforms to humans,
instead of humans conforming to the AI

Exact Markdown and source mapping

DISC-0064-VIS-002

**Displayed presentation wording:**

> AI HUMAN IMPACT INVESTING
> Invest in those technology companies
> where the AI conforms to humans,
> instead of humans conforming to the AI
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-002",
    "state_id": "DISC-0064-VIS-002",
    "heading": "Investment direction",
    "frame_source": "../frames/DISC-0064-VIS-002.jpg",
    "frame_sha256": "823ff152e4628f5e77970c9b94b8810f23d1a4df542298e009172cbdaa2252d4",
    "frame_pts_seconds": 20,
    "display_intervals": [
      {
        "start_seconds": 19.52,
        "end_seconds": 26.8,
        "duration_seconds": 7.28,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": true,
    "substantive_exception": null,
    "placement_after": "DISC-0064-P001",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Invest in those technology companies\n> where the AI conforms to humans,\n> instead of humans conforming to the AI",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-002.jpg",
        "original_evidence_image_sha256": "07796ae784a1861282132fc87ccf96a2af5ab1bf6bf2d7dbf5d675dc16c9c42b",
        "original_evidence_pts_seconds": 25,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\visual_scan\\frame-000025000000.jpg",
        "evaluated_slide_markdown_sha256": "2e2682dc6c8567eeb36bec6328864d494c68196381ee9238f8af93c27d471833",
        "evaluated_placement_after": "DISC-0064-P001",
        "placement_assessment": "After P001 complete investment/conformity proposition; slide displays during that proposition.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": null
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "markdown_span": {
      "char_start": 811,
      "char_end": 1179,
      "utf8_start": 815,
      "utf8_end": 1183,
      "line_start": 21,
      "line_end": 34,
      "exact_text": "<!-- DISC-0064-VIS-002 | display timing in companion; reading placement is editorial -->\n\n### Investment direction\n\n![Original video frame at 00:20.000](../frames/DISC-0064-VIS-002.jpg)\n\n**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Invest in those technology companies\n> where the AI conforms to humans,\n> instead of humans conforming to the AI\n\n",
      "text_sha256": "acb319a0aa9d574fd1a936f290146d3b8a29f5763bfdeb17eafe83689a9f918e"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P001",
      "word_span": [
        0,
        38
      ],
      "text": "Question is how to put AI ethics into practice. Well, here's one way. We can make it possible for people to invest in technology companies where AI conforms to humans instead of having humans conform to the AI.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00001",
        "DISC-0064-RUN-20261031-01-SEG-00002",
        "DISC-0064-RUN-20261031-01-SEG-00003"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0005"
      ],
      "original_start_seconds": 5.43,
      "original_end_seconds": 25.71,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 599,
        "char_end": 809,
        "utf8_start": 603,
        "utf8_end": 813,
        "line_start": 19,
        "line_end": 19,
        "exact_text": "Question is how to put AI ethics into practice. Well, here's one way. We can make it possible for people to invest in technology companies where AI conforms to humans instead of having humans conform to the AI.",
        "text_sha256": "8deb934be2e45ed13a07b3d97ed88e1172e61283e982bb6890a0dc167b47d27f"
      }
    },
    {
      "passage_id": "DISC-0064-P002",
      "word_span": [
        38,
        82
      ],
      "text": "And to do that, what we need is a model for objectively scoring AI-intensive businesses. I mean those companies that have artificial intelligence working at the core of their business operation. We need a way of scoring them on a humanitarian scale.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00003",
        "DISC-0064-RUN-20261031-01-SEG-00004",
        "DISC-0064-RUN-20261031-01-SEG-00005",
        "DISC-0064-RUN-20261031-01-SEG-00006"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0001"
      ],
      "original_start_seconds": 25.95,
      "original_end_seconds": 46.33,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 1245,
        "char_end": 1494,
        "utf8_start": 1251,
        "utf8_end": 1500,
        "line_start": 36,
        "line_end": 36,
        "exact_text": "And to do that, what we need is a model for objectively scoring AI-intensive businesses. I mean those companies that have artificial intelligence working at the core of their business operation. We need a way of scoring them on a humanitarian scale.",
        "text_sha256": "d69b732364985f2e893b340dfa6666bf06ea2edd1a8d48e6b4244fc042fbf486"
      }
    }
  ]
}

Scoring companies

Original display: 00:42.080–00:47.960
Selected frame: 00:45. Reading placement is editorial; display times are unchanged.

Original presentation frame: Scoring companies

Displayed presentation wording:

AI HUMAN IMPACT INVESTING
Objectively score AI-intensive companies
on an humanitarian scale

Exact Markdown and source mapping

DISC-0064-VIS-003

**Displayed presentation wording:**

> AI HUMAN IMPACT INVESTING
> Objectively score AI-intensive companies
> on an humanitarian scale
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-003",
    "state_id": "DISC-0064-VIS-003",
    "heading": "Scoring companies",
    "frame_source": "../frames/DISC-0064-VIS-003.jpg",
    "frame_sha256": "680bab155849e01827910a9576ecaa7762fb70161be3c633c07dc322490691b1",
    "frame_pts_seconds": 45,
    "display_intervals": [
      {
        "start_seconds": 42.08,
        "end_seconds": 47.96,
        "duration_seconds": 5.88,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": true,
    "substantive_exception": null,
    "placement_after": "DISC-0064-P002",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Objectively score AI-intensive companies\n> on an humanitarian scale",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-003.jpg",
        "original_evidence_image_sha256": "a13c6a83743e17107c2e66defe8b87a7541ca808671cc1a984a62c98394e1b6f",
        "original_evidence_pts_seconds": 47.92,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\scene_scan\\cut-07-before.jpg",
        "evaluated_slide_markdown_sha256": "baac48640c5a6f9433f5cae8f841a78eed94ad925ebfbafb93e7b23b76a4d532",
        "evaluated_placement_after": "DISC-0064-P002",
        "placement_assessment": "After P002 complete humanitarian-scoring proposition; slide displays near its ending.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": null
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "markdown_span": {
      "char_start": 1496,
      "char_end": 1816,
      "utf8_start": 1502,
      "utf8_end": 1822,
      "line_start": 38,
      "line_end": 50,
      "exact_text": "<!-- DISC-0064-VIS-003 | display timing in companion; reading placement is editorial -->\n\n### Scoring companies\n\n![Original video frame at 00:45.000](../frames/DISC-0064-VIS-003.jpg)\n\n**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Objectively score AI-intensive companies\n> on an humanitarian scale\n\n",
      "text_sha256": "2b8ae3648f5c8862f93628223cd7701e6b25ce02e737be51cefd931846583b1c"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P001",
      "word_span": [
        0,
        38
      ],
      "text": "Question is how to put AI ethics into practice. Well, here's one way. We can make it possible for people to invest in technology companies where AI conforms to humans instead of having humans conform to the AI.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00001",
        "DISC-0064-RUN-20261031-01-SEG-00002",
        "DISC-0064-RUN-20261031-01-SEG-00003"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00001-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00002-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0005"
      ],
      "original_start_seconds": 5.43,
      "original_end_seconds": 25.71,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 599,
        "char_end": 809,
        "utf8_start": 603,
        "utf8_end": 813,
        "line_start": 19,
        "line_end": 19,
        "exact_text": "Question is how to put AI ethics into practice. Well, here's one way. We can make it possible for people to invest in technology companies where AI conforms to humans instead of having humans conform to the AI.",
        "text_sha256": "8deb934be2e45ed13a07b3d97ed88e1172e61283e982bb6890a0dc167b47d27f"
      }
    },
    {
      "passage_id": "DISC-0064-P002",
      "word_span": [
        38,
        82
      ],
      "text": "And to do that, what we need is a model for objectively scoring AI-intensive businesses. I mean those companies that have artificial intelligence working at the core of their business operation. We need a way of scoring them on a humanitarian scale.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00003",
        "DISC-0064-RUN-20261031-01-SEG-00004",
        "DISC-0064-RUN-20261031-01-SEG-00005",
        "DISC-0064-RUN-20261031-01-SEG-00006"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00003-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00004-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00005-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0001"
      ],
      "original_start_seconds": 25.95,
      "original_end_seconds": 46.33,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 1245,
        "char_end": 1494,
        "utf8_start": 1251,
        "utf8_end": 1500,
        "line_start": 36,
        "line_end": 36,
        "exact_text": "And to do that, what we need is a model for objectively scoring AI-intensive businesses. I mean those companies that have artificial intelligence working at the core of their business operation. We need a way of scoring them on a humanitarian scale.",
        "text_sha256": "d69b732364985f2e893b340dfa6666bf06ea2edd1a8d48e6b4244fc042fbf486"
      }
    }
  ]
}

And the good news is we have a lot of help. There've been more than 80 principles produced in the last few years, and more are coming, along with principles of the principles and principles of principles of the principles, and so on. So we have a lot of sets of ideas that try to define what kinds of requirements are necessary for artificial intelligence to serve the human condition.

Source details

Speech references

  1. 00:47.500–01:19.020

Displayed research quotation

Original display: 00:53.960–00:57.720
Selected frame: 00:55. Reading placement is editorial; display times are unchanged.

Original presentation frame: Displayed research quotation

Displayed third-party research extract — Thomas Ploug and Søren Holm; Elsevier branding.

Visible title: “The four dimensions of contestable AI diagnostics- A patient-[partly obscured by the AI Policy Exchange overlay] / approach to explainable AI.”

In response to these problems, public committees and expert groups, research institutions and private companies have in recent years issued reports on and guidelines for responsible use of AI. A systematic review of the corpus of such guidelines found 84 documents containing ethical principles and guidelines for the use of AI [11]. The review identifies a significant global convergence on the importance of, among others, the transparency or explainability of AI decision-making. The review also finds, however, a significant variance in the posited features of transparency. Thus, for instance, transparency is posited to 1) serve very

Editorial note: the extract continues beyond the bottom of the recorded frame. The line-wrap division “trans-parency” is joined above; no missing continuation is reconstructed.

AI-generated visual description: Yellow highlighting marks the finding about 84 documents containing ethical principles and guidelines for AI. The spoken “more than 80 principles” is retained separately above; the displayed text refers to documents.

Additional displayed metadata: Thomas Ploug; Søren Holm · Aalborg University Copenhagen, Centre for Applied Ethics and Philosophy of Science, Department of Communication, A. C. Meyers Vænge 15, 2450, Copenhagen SV, Denmark · University of Manchester, Centre for Social Ethics and Policy, School of Law, Manchester M13 9PL, United Kingdom · Center for Medical Ethics, Faculty of Medicine, University of Oslo, Oslo, Norway

Exact Markdown and source mapping

DISC-0064-VIS-004

**Displayed third-party research extract — Thomas Ploug and Søren Holm; Elsevier branding.**

Visible title: “The four dimensions of contestable AI diagnostics- A patient-[partly obscured by the AI Policy Exchange overlay] / approach to explainable AI.”

> In response to these problems, public committees and expert groups, research institutions and private companies have in recent years issued reports on and guidelines for responsible use of AI. A systematic review of the corpus of such guidelines found 84 documents containing ethical principles and guidelines for the use of AI [11]. The review identifies a significant global convergence on the importance of, among others, the transparency or explainability of AI decision-making. The review also finds, however, a significant variance in the posited features of transparency. Thus, for instance, transparency is posited to 1) serve very

*Editorial note: the extract continues beyond the bottom of the recorded frame. The line-wrap division “trans-parency” is joined above; no missing continuation is reconstructed.*

**AI-generated visual description:** Yellow highlighting marks the finding about 84 documents containing ethical principles and guidelines for AI. The spoken “more than 80 principles” is retained separately above; the displayed text refers to documents.
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-004",
    "state_id": "DISC-0064-VIS-004",
    "heading": "Displayed research quotation",
    "frame_source": "../frames/DISC-0064-VIS-004.jpg",
    "frame_sha256": "fcf5873d15b4b013ddbaa5f04aab441372226b71204860fbf33b815653343640",
    "frame_pts_seconds": 55,
    "display_intervals": [
      {
        "start_seconds": 53.96,
        "end_seconds": 57.72,
        "duration_seconds": 3.76,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": false,
    "substantive_exception": "Short extract supplies substantive support for the principles claim and the number 84.",
    "placement_after": "DISC-0064-P003",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed third-party research extract — Thomas Ploug and Søren Holm; Elsevier branding.**\n\nVisible title: “The four dimensions of contestable AI diagnostics- A patient-[partly obscured by the AI Policy Exchange overlay] / approach to explainable AI.”\n\n> In response to these problems, public committees and expert groups, research institutions and private companies have in recent years issued reports on and guidelines for responsible use of AI. A systematic review of the corpus of such guidelines found 84 documents containing ethical principles and guidelines for the use of AI [11]. The review identifies a significant global convergence on the importance of, among others, the transparency or explainability of AI decision-making. The review also finds, however, a significant variance in the posited features of transparency. Thus, for instance, transparency is posited to 1) serve very\n\n*Editorial note: the extract continues beyond the bottom of the recorded frame. The line-wrap division “trans-parency” is joined above; no missing continuation is reconstructed.*\n\n**AI-generated visual description:** Yellow highlighting marks the finding about 84 documents containing ethical principles and guidelines for AI. The spoken “more than 80 principles” is retained separately above; the displayed text refers to documents.",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-004.jpg",
        "original_evidence_image_sha256": "608201018f0bc5c3fc7b16a14597cb9ddc0f1589e2d938f5e8f332bb5cc5800f",
        "original_evidence_pts_seconds": 56.96,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\focused_visual_1\\frame-000056960000.jpg",
        "evaluated_slide_markdown_sha256": "6b9ad0c4543289cbbc0f4981053e657d2c0bd29fb224c57b6682d178e5c0162e",
        "evaluated_placement_after": "DISC-0064-P003",
        "placement_assessment": "After P003 principles discussion, preserving the displayed third-party support and its different documents wording.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": "SECOND_PASS_ENCODING_REPAIRS.json"
      }
    },
    "automatic_clearance": true,
    "qualifications": [
      "Part of the article title is obscured by a publisher overlay; visible paragraph ends mid-sentence. No hidden text filled. Affiliations retained below as ancillary metadata; no journal/year inferred."
    ],
    "ancillary_displayed_metadata": [
      "Thomas Ploug; Søren Holm",
      "Aalborg University Copenhagen, Centre for Applied Ethics and Philosophy of Science, Department of Communication, A. C. Meyers Vænge 15, 2450, Copenhagen SV, Denmark",
      "University of Manchester, Centre for Social Ethics and Policy, School of Law, Manchester M13 9PL, United Kingdom",
      "Center for Medical Ethics, Faculty of Medicine, University of Oslo, Oslo, Norway"
    ],
    "markdown_span": {
      "char_start": 2269,
      "char_end": 3797,
      "utf8_start": 2277,
      "utf8_end": 3820,
      "line_start": 54,
      "line_end": 70,
      "exact_text": "<!-- DISC-0064-VIS-004 | display timing in companion; reading placement is editorial -->\n\n### Displayed research quotation\n\n![Original video frame at 00:55.000](../frames/DISC-0064-VIS-004.jpg)\n\n**Displayed third-party research extract — Thomas Ploug and Søren Holm; Elsevier branding.**\n\nVisible title: “The four dimensions of contestable AI diagnostics- A patient-[partly obscured by the AI Policy Exchange overlay] / approach to explainable AI.”\n\n> In response to these problems, public committees and expert groups, research institutions and private companies have in recent years issued reports on and guidelines for responsible use of AI. A systematic review of the corpus of such guidelines found 84 documents containing ethical principles and guidelines for the use of AI [11]. The review identifies a significant global convergence on the importance of, among others, the transparency or explainability of AI decision-making. The review also finds, however, a significant variance in the posited features of transparency. Thus, for instance, transparency is posited to 1) serve very\n\n*Editorial note: the extract continues beyond the bottom of the recorded frame. The line-wrap division “trans-parency” is joined above; no missing continuation is reconstructed.*\n\n**AI-generated visual description:** Yellow highlighting marks the finding about 84 documents containing ethical principles and guidelines for AI. The spoken “more than 80 principles” is retained separately above; the displayed text refers to documents.\n\n",
      "text_sha256": "11ad994cef1fe99040300f6a37d1d1dd63a6793fa342ebe3ab829c8f74aa4bf8"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P003",
      "word_span": [
        82,
        152
      ],
      "text": "And the good news is we have a lot of help. There've been more than 80 principles produced in the last few years, and more are coming, along with principles of the principles and principles of principles of the principles, and so on. So we have a lot of sets of ideas that try to define what kinds of requirements are necessary for artificial intelligence to serve the human condition.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00006",
        "DISC-0064-RUN-20261031-01-SEG-00007",
        "DISC-0064-RUN-20261031-01-SEG-00008",
        "DISC-0064-RUN-20261031-01-SEG-00009",
        "DISC-0064-RUN-20261031-01-SEG-00010"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0020",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0020",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0001"
      ],
      "original_start_seconds": 47.5,
      "original_end_seconds": 79.02,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 1882,
        "char_end": 2267,
        "utf8_start": 1890,
        "utf8_end": 2275,
        "line_start": 52,
        "line_end": 52,
        "exact_text": "And the good news is we have a lot of help. There've been more than 80 principles produced in the last few years, and more are coming, along with principles of the principles and principles of principles of the principles, and so on. So we have a lot of sets of ideas that try to define what kinds of requirements are necessary for artificial intelligence to serve the human condition.",
        "text_sha256": "0159ea2e488c86c62a0e4c4d77eb814e9c68529bb23624006796ab5b115e998f"
      }
    }
  ]
}

Build the framework

Original display: 01:19.840–01:22.280
Selected frame: 01:20. Reading placement is editorial; display times are unchanged.

Original presentation frame: Build the framework

Displayed presentation wording:

AI HUMAN IMPACT INVESTING
Build the framework

Exact Markdown and source mapping

DISC-0064-VIS-005

**Displayed presentation wording:**

> AI HUMAN IMPACT INVESTING
> Build the framework
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-005",
    "state_id": "DISC-0064-VIS-005",
    "heading": "Build the framework",
    "frame_source": "../frames/DISC-0064-VIS-005.jpg",
    "frame_sha256": "7cbaff81a69c6bcd113e8574f1d705015aa4e880b05bd6b26eea8719eade24e2",
    "frame_pts_seconds": 80,
    "display_intervals": [
      {
        "start_seconds": 79.84,
        "end_seconds": 82.28,
        "duration_seconds": 2.44,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": false,
    "substantive_exception": "Substantive structural card introduces construction of the model.",
    "placement_after": "DISC-0064-P003",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Build the framework",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-005.jpg",
        "original_evidence_image_sha256": "d661615400933a0e34935fd4ff2937c0d41ad78db18c431aa43c1583b97327bd",
        "original_evidence_pts_seconds": 79.84,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\scene_scan\\cut-10-79.840.jpg",
        "evaluated_slide_markdown_sha256": "518733eb12a28629bb5d4df5390c6d4ee53de7703fb75e4b18db0141df858eaf",
        "evaluated_placement_after": "DISC-0064-P003",
        "placement_assessment": "After P003 and immediately before P004 framework construction; source card begins between those thought bounds.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": null
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "markdown_span": {
      "char_start": 3797,
      "char_end": 4071,
      "utf8_start": 3820,
      "utf8_end": 4094,
      "line_start": 70,
      "line_end": 81,
      "exact_text": "<!-- DISC-0064-VIS-005 | display timing in companion; reading placement is editorial -->\n\n### Build the framework\n\n![Original video frame at 01:20.000](../frames/DISC-0064-VIS-005.jpg)\n\n**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Build the framework\n\n",
      "text_sha256": "0e6e1c54c6a07c19b4c0f8d91be002a9113ad838416ec1c369e446c5d3ef4d18"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P003",
      "word_span": [
        82,
        152
      ],
      "text": "And the good news is we have a lot of help. There've been more than 80 principles produced in the last few years, and more are coming, along with principles of the principles and principles of principles of the principles, and so on. So we have a lot of sets of ideas that try to define what kinds of requirements are necessary for artificial intelligence to serve the human condition.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00006",
        "DISC-0064-RUN-20261031-01-SEG-00007",
        "DISC-0064-RUN-20261031-01-SEG-00008",
        "DISC-0064-RUN-20261031-01-SEG-00009",
        "DISC-0064-RUN-20261031-01-SEG-00010"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00006-WORD-0020",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00007-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00008-WORD-0020",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00009-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0001"
      ],
      "original_start_seconds": 47.5,
      "original_end_seconds": 79.02,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 1882,
        "char_end": 2267,
        "utf8_start": 1890,
        "utf8_end": 2275,
        "line_start": 52,
        "line_end": 52,
        "exact_text": "And the good news is we have a lot of help. There've been more than 80 principles produced in the last few years, and more are coming, along with principles of the principles and principles of principles of the principles, and so on. So we have a lot of sets of ideas that try to define what kinds of requirements are necessary for artificial intelligence to serve the human condition.",
        "text_sha256": "0159ea2e488c86c62a0e4c4d77eb814e9c68529bb23624006796ab5b115e998f"
      }
    }
  ]
}

A framework of nine values

Now, we need to boil down to key elements, and this is what that model is going to look like in the end. I'm fast-forwarding. There are three pillars of AI ethics: the personal, the social and the technical. And each one of those supports three values.

So, as you can see here, within the personal we have autonomy, dignity and privacy. Within the social we have fairness, solidarity and sustainability. And then on the technical front we have performance, safety and accountability.

And now, one quick point: the critical category is all the values of personal freedom, that is, autonomy, dignity and privacy. These are the key performance indicators for AI ethical evaluations of companies, because the purpose of humanitarian artificial intelligence is to increase individual human potential. The reason we have the ethics of AI in the first place is to help each one of us as individuals do more independently.

Displayed slide table

Personal FreedomSocial WellbeingTechnical Trustworthiness
AutonomyFairnessPerformance
DignitySolidaritySafety
PrivacySustainabilityAccountability
Values / Key Performance Indicators · presentation wording
Source details

Speech references

  1. 01:20.360–01:41.260
  2. 01:41.260–01:56.850
  3. 01:56.850–02:33.840

Values and key performance indicators

Original display: 01:25.480–01:58.120
Selected frame: 01:30. Reading placement is editorial; display times are unchanged.

Original presentation frame: Values and key performance indicators

Displayed presentation wording and table:

VALUES / KEY PERFORMANCE INDICATORS

Personal FreedomSocial WellbeingTechnical Trustworthiness
AutonomyFairnessPerformance
DignitySolidaritySafety
PrivacySustainabilityAccountability
Exact Markdown and source mapping

DISC-0064-VIS-006

**Displayed presentation wording and table:**

> VALUES / KEY PERFORMANCE INDICATORS

| Personal Freedom | Social Wellbeing | Technical Trustworthiness |
|---|---|---|
| Autonomy | Fairness | Performance |
| Dignity | Solidarity | Safety |
| Privacy | Sustainability | Accountability |
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-006",
    "state_id": "DISC-0064-VIS-006",
    "heading": "Values and key performance indicators",
    "frame_source": "../frames/DISC-0064-VIS-006.jpg",
    "frame_sha256": "e8f00a40fa5accfdbc4eef8aa55e73f7409c9406d61453eba6f37bbc72425bfb",
    "frame_pts_seconds": 90,
    "display_intervals": [
      {
        "start_seconds": 85.48,
        "end_seconds": 118.12,
        "duration_seconds": 32.64,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": true,
    "substantive_exception": null,
    "placement_after": "DISC-0064-P005",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed presentation wording and table:**\n\n> VALUES / KEY PERFORMANCE INDICATORS\n\n| Personal Freedom | Social Wellbeing | Technical Trustworthiness |\n|---|---|---|\n| Autonomy | Fairness | Performance |\n| Dignity | Solidarity | Safety |\n| Privacy | Sustainability | Accountability |",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-006.jpg",
        "original_evidence_image_sha256": "61aa53b79b3cd7da20539465c60c8f4451178279ce00d2ee1f51c980e7ff32a5",
        "original_evidence_pts_seconds": 115,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\visual_scan\\frame-000115000000.jpg",
        "evaluated_slide_markdown_sha256": "eacf10f6a3dbfa787f2bcf739d2e667ee643a0e5d9b78dd39b11d7389a8b8faf",
        "evaluated_placement_after": "DISC-0064-P005",
        "placement_assessment": "After P005 complete enumeration; source table remains displayed throughout the enumeration.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": null
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "markdown_span": {
      "char_start": 4689,
      "char_end": 5180,
      "utf8_start": 4716,
      "utf8_end": 5207,
      "line_start": 89,
      "line_end": 105,
      "exact_text": "<!-- DISC-0064-VIS-006 | display timing in companion; reading placement is editorial -->\n\n### Values and key performance indicators\n\n![Original video frame at 01:30.000](../frames/DISC-0064-VIS-006.jpg)\n\n**Displayed presentation wording and table:**\n\n> VALUES / KEY PERFORMANCE INDICATORS\n\n| Personal Freedom | Social Wellbeing | Technical Trustworthiness |\n|---|---|---|\n| Autonomy | Fairness | Performance |\n| Dignity | Solidarity | Safety |\n| Privacy | Sustainability | Accountability |\n\n",
      "text_sha256": "0ac2d1760fdd5c12474c7ccf02fc71f388b4210870954f1ebecdff20027e9491"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P004",
      "word_span": [
        152,
        200
      ],
      "text": "Now, we need to boil down to key elements, and this is what that model is going to look like in the end. I'm fast-forwarding. There are three pillars of AI ethics: the personal, the social and the technical. And each one of those supports three values.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00010",
        "DISC-0064-RUN-20261031-01-SEG-00011",
        "DISC-0064-RUN-20261031-01-SEG-00012"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0012"
      ],
      "original_start_seconds": 80.36,
      "original_end_seconds": 101.26,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 4137,
        "char_end": 4389,
        "utf8_start": 4162,
        "utf8_end": 4414,
        "line_start": 83,
        "line_end": 83,
        "exact_text": "Now, we need to boil down to key elements, and this is what that model is going to look like in the end. I'm fast-forwarding. There are three pillars of AI ethics: the personal, the social and the technical. And each one of those supports three values.",
        "text_sha256": "772234badcf74008976a32a294a3d92b710e26347266a4644beaf352b3f8e4e8"
      }
    },
    {
      "passage_id": "DISC-0064-P005",
      "word_span": [
        200,
        236
      ],
      "text": "So, as you can see here, within the personal we have autonomy, dignity and privacy. Within the social we have fairness, solidarity and sustainability. And then on the technical front we have performance, safety and accountability.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00012",
        "DISC-0064-RUN-20261031-01-SEG-00013",
        "DISC-0064-RUN-20261031-01-SEG-00014",
        "DISC-0064-RUN-20261031-01-SEG-00015"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0001"
      ],
      "original_start_seconds": 101.26,
      "original_end_seconds": 116.85,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 4457,
        "char_end": 4687,
        "utf8_start": 4484,
        "utf8_end": 4714,
        "line_start": 87,
        "line_end": 87,
        "exact_text": "So, as you can see here, within the personal we have autonomy, dignity and privacy. Within the social we have fairness, solidarity and sustainability. And then on the technical front we have performance, safety and accountability.",
        "text_sha256": "8a93d070f580bd30c3ac647b1c030cce2164d1f1b67f7cc92d31478431ef7c89"
      }
    },
    {
      "passage_id": "DISC-0064-P006",
      "word_span": [
        236,
        307
      ],
      "text": "And now, one quick point: the critical category is all the values of personal freedom, that is, autonomy, dignity and privacy. These are the key performance indicators for AI ethical evaluations of companies, because the purpose of humanitarian artificial intelligence is to increase individual human potential. The reason we have the ethics of AI in the first place is to help each one of us as individuals do more independently.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00015",
        "DISC-0064-RUN-20261031-01-SEG-00016",
        "DISC-0064-RUN-20261031-01-SEG-00017",
        "DISC-0064-RUN-20261031-01-SEG-00018",
        "DISC-0064-RUN-20261031-01-SEG-00019",
        "DISC-0064-RUN-20261031-01-SEG-00020"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0008"
      ],
      "original_start_seconds": 116.85,
      "original_end_seconds": 153.84,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 5246,
        "char_end": 5676,
        "utf8_start": 5275,
        "utf8_end": 5705,
        "line_start": 107,
        "line_end": 107,
        "exact_text": "And now, one quick point: the critical category is all the values of personal freedom, that is, autonomy, dignity and privacy. These are the key performance indicators for AI ethical evaluations of companies, because the purpose of humanitarian artificial intelligence is to increase individual human potential. The reason we have the ethics of AI in the first place is to help each one of us as individuals do more independently.",
        "text_sha256": "4404ed5e7dc1856fd74dcc3a0defa2685b78230c82998c7522a6dbb50f554790"
      }
    }
  ]
}

Apply the model

Original display: 02:34.560–02:37.440
Selected frame: 02:35. Reading placement is editorial; display times are unchanged.

Original presentation frame: Apply the model

Displayed presentation wording:

AI HUMAN IMPACT INVESTING
Apply the model

Exact Markdown and source mapping

DISC-0064-VIS-007

**Displayed presentation wording:**

> AI HUMAN IMPACT INVESTING
> Apply the model
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-007",
    "state_id": "DISC-0064-VIS-007",
    "heading": "Apply the model",
    "frame_source": "../frames/DISC-0064-VIS-007.jpg",
    "frame_sha256": "d5ff1c81391cccdbef2a763333c0b934ab3818624bec45e0e5aeaffd1ad330e2",
    "frame_pts_seconds": 155,
    "display_intervals": [
      {
        "start_seconds": 154.56,
        "end_seconds": 157.44,
        "duration_seconds": 2.88,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": false,
    "substantive_exception": "Substantive structural card introduces company grading.",
    "placement_after": "DISC-0064-P006",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Apply the model",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-007.jpg",
        "original_evidence_image_sha256": "e52b84d858e835d1f472ef2ff977f1cc813c2318ce9859fa0cd19f04b5bcc6a5",
        "original_evidence_pts_seconds": 154.56,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\scene_scan\\cut-14-154.560.jpg",
        "evaluated_slide_markdown_sha256": "e1be398f5e5d9fc385b4bf7f4f251769144d3eee464edd6e8c028a4db70fb502",
        "evaluated_placement_after": "DISC-0064-P006",
        "placement_assessment": "After P006 personal-freedom explanation, before P007 model application; source short card begins between those bounds.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": null
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "markdown_span": {
      "char_start": 5678,
      "char_end": 5944,
      "utf8_start": 5707,
      "utf8_end": 5973,
      "line_start": 109,
      "line_end": 120,
      "exact_text": "<!-- DISC-0064-VIS-007 | display timing in companion; reading placement is editorial -->\n\n### Apply the model\n\n![Original video frame at 02:35.000](../frames/DISC-0064-VIS-007.jpg)\n\n**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Apply the model\n\n",
      "text_sha256": "c80442c280f859ed730abbf9deae72f763f96fd4db938a9b70fdd20c8648a570"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P004",
      "word_span": [
        152,
        200
      ],
      "text": "Now, we need to boil down to key elements, and this is what that model is going to look like in the end. I'm fast-forwarding. There are three pillars of AI ethics: the personal, the social and the technical. And each one of those supports three values.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00010",
        "DISC-0064-RUN-20261031-01-SEG-00011",
        "DISC-0064-RUN-20261031-01-SEG-00012"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00010-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00011-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0012"
      ],
      "original_start_seconds": 80.36,
      "original_end_seconds": 101.26,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 4137,
        "char_end": 4389,
        "utf8_start": 4162,
        "utf8_end": 4414,
        "line_start": 83,
        "line_end": 83,
        "exact_text": "Now, we need to boil down to key elements, and this is what that model is going to look like in the end. I'm fast-forwarding. There are three pillars of AI ethics: the personal, the social and the technical. And each one of those supports three values.",
        "text_sha256": "772234badcf74008976a32a294a3d92b710e26347266a4644beaf352b3f8e4e8"
      }
    },
    {
      "passage_id": "DISC-0064-P005",
      "word_span": [
        200,
        236
      ],
      "text": "So, as you can see here, within the personal we have autonomy, dignity and privacy. Within the social we have fairness, solidarity and sustainability. And then on the technical front we have performance, safety and accountability.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00012",
        "DISC-0064-RUN-20261031-01-SEG-00013",
        "DISC-0064-RUN-20261031-01-SEG-00014",
        "DISC-0064-RUN-20261031-01-SEG-00015"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00012-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00013-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00014-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0001"
      ],
      "original_start_seconds": 101.26,
      "original_end_seconds": 116.85,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 4457,
        "char_end": 4687,
        "utf8_start": 4484,
        "utf8_end": 4714,
        "line_start": 87,
        "line_end": 87,
        "exact_text": "So, as you can see here, within the personal we have autonomy, dignity and privacy. Within the social we have fairness, solidarity and sustainability. And then on the technical front we have performance, safety and accountability.",
        "text_sha256": "8a93d070f580bd30c3ac647b1c030cce2164d1f1b67f7cc92d31478431ef7c89"
      }
    },
    {
      "passage_id": "DISC-0064-P006",
      "word_span": [
        236,
        307
      ],
      "text": "And now, one quick point: the critical category is all the values of personal freedom, that is, autonomy, dignity and privacy. These are the key performance indicators for AI ethical evaluations of companies, because the purpose of humanitarian artificial intelligence is to increase individual human potential. The reason we have the ethics of AI in the first place is to help each one of us as individuals do more independently.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00015",
        "DISC-0064-RUN-20261031-01-SEG-00016",
        "DISC-0064-RUN-20261031-01-SEG-00017",
        "DISC-0064-RUN-20261031-01-SEG-00018",
        "DISC-0064-RUN-20261031-01-SEG-00019",
        "DISC-0064-RUN-20261031-01-SEG-00020"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00015-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00016-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00017-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00018-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00019-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0008"
      ],
      "original_start_seconds": 116.85,
      "original_end_seconds": 153.84,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 5246,
        "char_end": 5676,
        "utf8_start": 5275,
        "utf8_end": 5705,
        "line_start": 107,
        "line_end": 107,
        "exact_text": "And now, one quick point: the critical category is all the values of personal freedom, that is, autonomy, dignity and privacy. These are the key performance indicators for AI ethical evaluations of companies, because the purpose of humanitarian artificial intelligence is to increase individual human potential. The reason we have the ethics of AI in the first place is to help each one of us as individuals do more independently.",
        "text_sha256": "4404ed5e7dc1856fd74dcc3a0defa2685b78230c82998c7522a6dbb50f554790"
      }
    }
  ]
}

Applying the model

So that's the model. We have a set of AI humanitarian values, and then we can go through and apply them as grades.

For example, we might say that a company like Apple, that does well in amplifying personal autonomy and also does well with privacy protection, we might say a company like that scores highly.

Apple example — original presentation slide
Presentation slide · Apple example
Source details

Speech references

  1. 02:34.140–02:42.420
  2. 02:42.700–02:54.710

Apple example

Original display: 02:45.440–02:55.720
Selected frame: 02:50. Reading placement is editorial; display times are unchanged.

Open the full slide image

Displayed table wording:

Personal FreedomSocial WellbeingTechnical Trustworthiness
AutonomyFairnessPerformance
DignitySolidaritySafety
PrivacySustainabilityAccountability

AI-generated visual description: A grey Apple logo appears above the table. Green strokes underline Autonomy and Privacy in the Personal Freedom column; Dignity is not underlined. No numerical grades are displayed.

Exact Markdown and source mapping

DISC-0064-VIS-008

**Displayed table wording:**

| Personal Freedom | Social Wellbeing | Technical Trustworthiness |
|---|---|---|
| Autonomy | Fairness | Performance |
| Dignity | Solidarity | Safety |
| Privacy | Sustainability | Accountability |

**AI-generated visual description:** A grey Apple logo appears above the table. Green strokes underline Autonomy and Privacy in the Personal Freedom column; Dignity is not underlined. No numerical grades are displayed.
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-008",
    "state_id": "DISC-0064-VIS-008",
    "heading": "Apple example",
    "frame_source": "../frames/DISC-0064-VIS-008.jpg",
    "frame_sha256": "dc26da6df5e130ef40a1fb2da3b82d730fb7c7cce66a700239ff1d04426ae314",
    "frame_pts_seconds": 170,
    "display_intervals": [
      {
        "start_seconds": 165.44,
        "end_seconds": 175.72,
        "duration_seconds": 10.28,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": true,
    "substantive_exception": null,
    "placement_after": "DISC-0064-P008",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed table wording:**\n\n| Personal Freedom | Social Wellbeing | Technical Trustworthiness |\n|---|---|---|\n| Autonomy | Fairness | Performance |\n| Dignity | Solidarity | Safety |\n| Privacy | Sustainability | Accountability |\n\n**AI-generated visual description:** A grey Apple logo appears above the table. Green strokes underline Autonomy and Privacy in the Personal Freedom column; Dignity is not underlined. No numerical grades are displayed.",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-008.jpg",
        "original_evidence_image_sha256": "18fe4cc5987515988dc579ba60871774ac36ddd682a2415be21f98750872d7b8",
        "original_evidence_pts_seconds": 175,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\visual_scan\\frame-000175000000.jpg",
        "evaluated_slide_markdown_sha256": "cbafd0f82e7d7ea3f27f30671fe35cf8822c903190d447c161e4f0e58063b7f5",
        "evaluated_placement_after": "DISC-0064-P008",
        "placement_assessment": "After P008 Apple example; original table highlights the same Autonomy and Privacy values during the example.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": null
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "markdown_span": {
      "char_start": 6385,
      "char_end": 7016,
      "utf8_start": 6418,
      "utf8_end": 7049,
      "line_start": 128,
      "line_end": 144,
      "exact_text": "<!-- DISC-0064-VIS-008 | display timing in companion; reading placement is editorial -->\n\n### Apple example\n\n![Original video frame at 02:50.000](../frames/DISC-0064-VIS-008.jpg)\n\n**Displayed table wording:**\n\n| Personal Freedom | Social Wellbeing | Technical Trustworthiness |\n|---|---|---|\n| Autonomy | Fairness | Performance |\n| Dignity | Solidarity | Safety |\n| Privacy | Sustainability | Accountability |\n\n**AI-generated visual description:** A grey Apple logo appears above the table. Green strokes underline Autonomy and Privacy in the Personal Freedom column; Dignity is not underlined. No numerical grades are displayed.\n\n",
      "text_sha256": "888704f58a49541155db5e5b7027913b32252e7c296cc09173b457cf9973eef0"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P007",
      "word_span": [
        307,
        330
      ],
      "text": "So that's the model. We have a set of AI humanitarian values, and then we can go through and apply them as grades.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00020",
        "DISC-0064-RUN-20261031-01-SEG-00021"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00020-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0012"
      ],
      "original_start_seconds": 154.14,
      "original_end_seconds": 162.42,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 6010,
        "char_end": 6124,
        "utf8_start": 6041,
        "utf8_end": 6155,
        "line_start": 122,
        "line_end": 122,
        "exact_text": "So that's the model. We have a set of AI humanitarian values, and then we can go through and apply them as grades.",
        "text_sha256": "acb697975e5f14b019076fdb414ced73f3770daeb841e0465e38755c4d1f0b77"
      }
    },
    {
      "passage_id": "DISC-0064-P008",
      "word_span": [
        330,
        364
      ],
      "text": "For example, we might say that a company like Apple, that does well in amplifying personal autonomy and also does well with privacy protection, we might say a company like that scores highly.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00021",
        "DISC-0064-RUN-20261031-01-SEG-00022",
        "DISC-0064-RUN-20261031-01-SEG-00023"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00021-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00022-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0011"
      ],
      "original_start_seconds": 162.7,
      "original_end_seconds": 174.71,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 6192,
        "char_end": 6383,
        "utf8_start": 6225,
        "utf8_end": 6416,
        "line_start": 126,
        "line_end": 126,
        "exact_text": "For example, we might say that a company like Apple, that does well in amplifying personal autonomy and also does well with privacy protection, we might say a company like that scores highly.",
        "text_sha256": "3bc51cf2a313216eaa9c6fd38552c2bc18556fb3a320f9457674c47970e339db"
      }
    }
  ]
}

Whereas, by contrast, a company like TikTok, which is part of ByteDance, a company or a conglomerate like that captures users in addictive dark patterns, dopamine patterns, let's say. So they're going to fail the test of increasing self-determination. They're going to fail the test of autonomy, and they're also going to fail the test of privacy, as they capture all sorts of data without any acknowledgement and spread it to who knows what places.

So we have a company that scores well, like Apple, a company that scores poorly, TikTok. And then that's the way this model would develop. We find each company and define it in terms of each of these nine values, that is, score each company in terms of its autonomy, in terms of its dignity, and down the list to accountability and safety and so on. And in that way, we could form a hierarchy of humanitarian AI companies, from better to worse.

Apple and TikTok comparison — original presentation slide
Presentation slide · Apple and TikTok comparison
Source details

Speech references

  1. 02:54.710–03:23.660
  2. 03:23.660–03:55.610

TikTok and addictive use

Original display: 02:58.440–03:05.240
Selected frame: 03:00. Reading placement is editorial; display times are unchanged.

Original presentation frame: TikTok and addictive use

Displayed third-party quotation — Forbes, John Koetsier, Senior Contributor; Consumer Tech. The screenshot shows 18 January 2020, 02:04pm EST.

Digital Crack Cocaine: The Science Behind TikTok’s Success

TikTok gained 682 million new users last year, each of whom spend an average of 50 minutes a day in the app. That’s mind-blowing, hockey-stick, off-the-charts growth that we haven’t seen since Pokemon Go.

But what makes TikTok so successful?

Displayed author note: “John Koetsier is a journalist, analyst, author, and speaker.”

AI-generated visual description: The article screenshot includes four vertical TikTok video thumbnails below the text. Small thumbnail overlays are not reliably transcribed; they are retained in the frame.

Additional displayed metadata: 30,323 views; screenshot counter, not a current measurement.

Exact Markdown and source mapping

DISC-0064-VIS-009

**Displayed third-party quotation — Forbes, John Koetsier, Senior Contributor; Consumer Tech.** The screenshot shows 18 January 2020, 02:04pm EST.

> Digital Crack Cocaine: The Science Behind TikTok’s Success

> TikTok gained 682 million new users last year, each of whom spend an average of 50 minutes a day in the app. That’s mind-blowing, hockey-stick, off-the-charts growth that we haven’t seen since Pokemon Go.
> 
> But what makes TikTok so successful?

Displayed author note: “John Koetsier is a journalist, analyst, author, and speaker.”

**AI-generated visual description:** The article screenshot includes four vertical TikTok video thumbnails below the text. Small thumbnail overlays are not reliably transcribed; they are retained in the frame.
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-009",
    "state_id": "DISC-0064-VIS-009",
    "heading": "TikTok and addictive use",
    "frame_source": "../frames/DISC-0064-VIS-009.jpg",
    "frame_sha256": "5bdbb86eda05c4cf98dd890c88179ca6bc317480ee7ecd6cbc8fbdbac567be16",
    "frame_pts_seconds": 180,
    "display_intervals": [
      {
        "start_seconds": 178.44,
        "end_seconds": 185.24,
        "duration_seconds": 6.8,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": true,
    "substantive_exception": null,
    "placement_after": "DISC-0064-P009",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed third-party quotation — Forbes, John Koetsier, Senior Contributor; Consumer Tech.** The screenshot shows 18 January 2020, 02:04pm EST.\n\n> Digital Crack Cocaine: The Science Behind TikTok’s Success\n\n> TikTok gained 682 million new users last year, each of whom spend an average of 50 minutes a day in the app. That’s mind-blowing, hockey-stick, off-the-charts growth that we haven’t seen since Pokemon Go.\n> \n> But what makes TikTok so successful?\n\nDisplayed author note: “John Koetsier is a journalist, analyst, author, and speaker.”\n\n**AI-generated visual description:** The article screenshot includes four vertical TikTok video thumbnails below the text. Small thumbnail overlays are not reliably transcribed; they are retained in the frame.",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-009.jpg",
        "original_evidence_image_sha256": "722af3b76eba4897b33be4506f0e1747d387488ed7bd4a1b70daaba5e71eac32",
        "original_evidence_pts_seconds": 185,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\visual_scan\\frame-000185000000.jpg",
        "evaluated_slide_markdown_sha256": "e02a16378ac81e74ff258f271091313c25152875b888000a5b46455e91099b08",
        "evaluated_placement_after": "DISC-0064-P009",
        "placement_assessment": "After P009 TikTok critique; source first article appears during the addictive-use portion.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": "SECOND_PASS_ENCODING_REPAIRS.json"
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "ancillary_displayed_metadata": [
      "30,323 views; screenshot counter, not a current measurement."
    ],
    "markdown_span": {
      "char_start": 7533,
      "char_end": 8482,
      "utf8_start": 7568,
      "utf8_end": 8529,
      "line_start": 148,
      "line_end": 166,
      "exact_text": "<!-- DISC-0064-VIS-009 | display timing in companion; reading placement is editorial -->\n\n### TikTok and addictive use\n\n![Original video frame at 03:00.000](../frames/DISC-0064-VIS-009.jpg)\n\n**Displayed third-party quotation — Forbes, John Koetsier, Senior Contributor; Consumer Tech.** The screenshot shows 18 January 2020, 02:04pm EST.\n\n> Digital Crack Cocaine: The Science Behind TikTok’s Success\n\n> TikTok gained 682 million new users last year, each of whom spend an average of 50 minutes a day in the app. That’s mind-blowing, hockey-stick, off-the-charts growth that we haven’t seen since Pokemon Go.\n> \n> But what makes TikTok so successful?\n\nDisplayed author note: “John Koetsier is a journalist, analyst, author, and speaker.”\n\n**AI-generated visual description:** The article screenshot includes four vertical TikTok video thumbnails below the text. Small thumbnail overlays are not reliably transcribed; they are retained in the frame.\n\n",
      "text_sha256": "28d1091704a8a6310b960e9630df5870baf61b8036b3963c7b1563f2d4ff432c"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P009",
      "word_span": [
        364,
        440
      ],
      "text": "Whereas, by contrast, a company like TikTok, which is part of ByteDance, a company or a conglomerate like that captures users in addictive dark patterns, dopamine patterns, let's say. So they're going to fail the test of increasing self-determination. They're going to fail the test of autonomy, and they're also going to fail the test of privacy, as they capture all sorts of data without any acknowledgement and spread it to who knows what places.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00023",
        "DISC-0064-RUN-20261031-01-SEG-00024",
        "DISC-0064-RUN-20261031-01-SEG-00025",
        "DISC-0064-RUN-20261031-01-SEG-00026",
        "DISC-0064-RUN-20261031-01-SEG-00027",
        "DISC-0064-RUN-20261031-01-SEG-00028"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0004"
      ],
      "original_start_seconds": 174.71,
      "original_end_seconds": 203.66,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 7082,
        "char_end": 7531,
        "utf8_start": 7117,
        "utf8_end": 7566,
        "line_start": 146,
        "line_end": 146,
        "exact_text": "Whereas, by contrast, a company like TikTok, which is part of ByteDance, a company or a conglomerate like that captures users in addictive dark patterns, dopamine patterns, let's say. So they're going to fail the test of increasing self-determination. They're going to fail the test of autonomy, and they're also going to fail the test of privacy, as they capture all sorts of data without any acknowledgement and spread it to who knows what places.",
        "text_sha256": "fb9b68332438fde68b33d67178fbbe37b012990459cf719567726baed79fc97e"
      }
    },
    {
      "passage_id": "DISC-0064-P010",
      "word_span": [
        440,
        525
      ],
      "text": "So we have a company that scores well, like Apple, a company that scores poorly, TikTok. And then that's the way this model would develop. We find each company and define it in terms of each of these nine values, that is, score each company in terms of its autonomy, in terms of its dignity, and down the list to accountability and safety and so on. And in that way, we could form a hierarchy of humanitarian AI companies, from better to worse.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00028",
        "DISC-0064-RUN-20261031-01-SEG-00029",
        "DISC-0064-RUN-20261031-01-SEG-00030",
        "DISC-0064-RUN-20261031-01-SEG-00031",
        "DISC-0064-RUN-20261031-01-SEG-00032"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0017"
      ],
      "original_start_seconds": 203.66,
      "original_end_seconds": 235.61,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 10800,
        "char_end": 11244,
        "utf8_start": 10879,
        "utf8_end": 11323,
        "line_start": 218,
        "line_end": 218,
        "exact_text": "So we have a company that scores well, like Apple, a company that scores poorly, TikTok. And then that's the way this model would develop. We find each company and define it in terms of each of these nine values, that is, score each company in terms of its autonomy, in terms of its dignity, and down the list to accountability and safety and so on. And in that way, we could form a hierarchy of humanitarian AI companies, from better to worse.",
        "text_sha256": "9bd2cf1c4e3e381c8b8c3f31793acfbe562cbc60c6c8b82669ce0bfd35b47e1d"
      }
    }
  ]
}

Privacy example added to the article comparison

Original display: 03:12.800–03:24.600
Selected frame: 03:15. Reading placement is editorial; display times are unchanged.

Original presentation frame: Privacy example added to the article comparison

Left — repeated displayed third-party quotation:

Displayed third-party quotation — Forbes, John Koetsier, Senior Contributor; Consumer Tech. The screenshot shows 18 January 2020, 02:04pm EST.

Digital Crack Cocaine: The Science Behind TikTok’s Success

TikTok gained 682 million new users last year, each of whom spend an average of 50 minutes a day in the app. That’s mind-blowing, hockey-stick, off-the-charts growth that we haven’t seen since Pokemon Go.

But what makes TikTok so successful?

Displayed author note: “John Koetsier is a journalist, analyst, author, and speaker.”

Right — displayed third-party quotation, Forbes, Zak Doffman, Contributor; Cybersecurity. The screenshot shows 26 June 2020, 01:46am EDT.

Warning—Apple Suddenly Catches TikTok Secretly Spying On Millions Of iPhone Users

Displayed author note: “I write about security and surveillance.”

AI-generated visual description: A second article screenshot is added to the right of the Koetsier screenshot. Its photograph shows the TikTok mark and wordmark; the displayed credit is “AFP VIA GETTY IMAGES.” This meaningful build preserves the left article as a repeated occurrence.

Additional displayed metadata: Left 30,323 views; right 2,250,165 views. Historical screenshot counters, not current measurements.

Exact Markdown and source mapping

DISC-0064-VIS-010

**Left — repeated displayed third-party quotation:**

**Displayed third-party quotation — Forbes, John Koetsier, Senior Contributor; Consumer Tech.** The screenshot shows 18 January 2020, 02:04pm EST.

> Digital Crack Cocaine: The Science Behind TikTok’s Success

> TikTok gained 682 million new users last year, each of whom spend an average of 50 minutes a day in the app. That’s mind-blowing, hockey-stick, off-the-charts growth that we haven’t seen since Pokemon Go.
> 
> But what makes TikTok so successful?

Displayed author note: “John Koetsier is a journalist, analyst, author, and speaker.”

**Right — displayed third-party quotation, Forbes, Zak Doffman, Contributor; Cybersecurity.** The screenshot shows 26 June 2020, 01:46am EDT.

> Warning—Apple Suddenly Catches TikTok Secretly Spying On Millions Of iPhone Users

Displayed author note: “I write about security and surveillance.”

**AI-generated visual description:** A second article screenshot is added to the right of the Koetsier screenshot. Its photograph shows the TikTok mark and wordmark; the displayed credit is “AFP VIA GETTY IMAGES.” This meaningful build preserves the left article as a repeated occurrence.
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-010",
    "state_id": "DISC-0064-VIS-010",
    "heading": "Privacy example added to the article comparison",
    "frame_source": "../frames/DISC-0064-VIS-010.jpg",
    "frame_sha256": "cd61e8f28d5fdbcca5ed56bf33f2601a56bb17155945321b047cc7e3e5c5eac6",
    "frame_pts_seconds": 195,
    "display_intervals": [
      {
        "start_seconds": 192.8,
        "end_seconds": 204.6,
        "duration_seconds": 11.8,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": true,
    "substantive_exception": null,
    "placement_after": "DISC-0064-P009",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Left — repeated displayed third-party quotation:**\n\n**Displayed third-party quotation — Forbes, John Koetsier, Senior Contributor; Consumer Tech.** The screenshot shows 18 January 2020, 02:04pm EST.\n\n> Digital Crack Cocaine: The Science Behind TikTok’s Success\n\n> TikTok gained 682 million new users last year, each of whom spend an average of 50 minutes a day in the app. That’s mind-blowing, hockey-stick, off-the-charts growth that we haven’t seen since Pokemon Go.\n> \n> But what makes TikTok so successful?\n\nDisplayed author note: “John Koetsier is a journalist, analyst, author, and speaker.”\n\n**Right — displayed third-party quotation, Forbes, Zak Doffman, Contributor; Cybersecurity.** The screenshot shows 26 June 2020, 01:46am EDT.\n\n> Warning—Apple Suddenly Catches TikTok Secretly Spying On Millions Of iPhone Users\n\nDisplayed author note: “I write about security and surveillance.”\n\n**AI-generated visual description:** A second article screenshot is added to the right of the Koetsier screenshot. Its photograph shows the TikTok mark and wordmark; the displayed credit is “AFP VIA GETTY IMAGES.” This meaningful build preserves the left article as a repeated occurrence.",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-010.jpg",
        "original_evidence_image_sha256": "2fcb9621ad6c30f4fe7967169a7569dbca47c3d9299711611c5f133aa381e1ea",
        "original_evidence_pts_seconds": 200,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\visual_scan\\frame-000200000000.jpg",
        "evaluated_slide_markdown_sha256": "ef09ee02bc92c19d030828462f095f2ebe886f0c98fbcb075725e2f6a23f46c3",
        "evaluated_placement_after": "DISC-0064-P009",
        "placement_assessment": "After P009, preserving the new second article and earlier left article; display overlaps privacy critique.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": "SECOND_PASS_ENCODING_REPAIRS.json"
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "ancillary_displayed_metadata": [
      "Left 30,323 views; right 2,250,165 views. Historical screenshot counters, not current measurements."
    ],
    "markdown_span": {
      "char_start": 8482,
      "char_end": 9882,
      "utf8_start": 8529,
      "utf8_end": 9955,
      "line_start": 166,
      "line_end": 192,
      "exact_text": "<!-- DISC-0064-VIS-010 | display timing in companion; reading placement is editorial -->\n\n### Privacy example added to the article comparison\n\n![Original video frame at 03:15.000](../frames/DISC-0064-VIS-010.jpg)\n\n**Left — repeated displayed third-party quotation:**\n\n**Displayed third-party quotation — Forbes, John Koetsier, Senior Contributor; Consumer Tech.** The screenshot shows 18 January 2020, 02:04pm EST.\n\n> Digital Crack Cocaine: The Science Behind TikTok’s Success\n\n> TikTok gained 682 million new users last year, each of whom spend an average of 50 minutes a day in the app. That’s mind-blowing, hockey-stick, off-the-charts growth that we haven’t seen since Pokemon Go.\n> \n> But what makes TikTok so successful?\n\nDisplayed author note: “John Koetsier is a journalist, analyst, author, and speaker.”\n\n**Right — displayed third-party quotation, Forbes, Zak Doffman, Contributor; Cybersecurity.** The screenshot shows 26 June 2020, 01:46am EDT.\n\n> Warning—Apple Suddenly Catches TikTok Secretly Spying On Millions Of iPhone Users\n\nDisplayed author note: “I write about security and surveillance.”\n\n**AI-generated visual description:** A second article screenshot is added to the right of the Koetsier screenshot. Its photograph shows the TikTok mark and wordmark; the displayed credit is “AFP VIA GETTY IMAGES.” This meaningful build preserves the left article as a repeated occurrence.\n\n",
      "text_sha256": "7862c1a95363dbd3398570c2287ed49d814709acb68432358036db65da979489"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P009",
      "word_span": [
        364,
        440
      ],
      "text": "Whereas, by contrast, a company like TikTok, which is part of ByteDance, a company or a conglomerate like that captures users in addictive dark patterns, dopamine patterns, let's say. So they're going to fail the test of increasing self-determination. They're going to fail the test of autonomy, and they're also going to fail the test of privacy, as they capture all sorts of data without any acknowledgement and spread it to who knows what places.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00023",
        "DISC-0064-RUN-20261031-01-SEG-00024",
        "DISC-0064-RUN-20261031-01-SEG-00025",
        "DISC-0064-RUN-20261031-01-SEG-00026",
        "DISC-0064-RUN-20261031-01-SEG-00027",
        "DISC-0064-RUN-20261031-01-SEG-00028"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0004"
      ],
      "original_start_seconds": 174.71,
      "original_end_seconds": 203.66,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 7082,
        "char_end": 7531,
        "utf8_start": 7117,
        "utf8_end": 7566,
        "line_start": 146,
        "line_end": 146,
        "exact_text": "Whereas, by contrast, a company like TikTok, which is part of ByteDance, a company or a conglomerate like that captures users in addictive dark patterns, dopamine patterns, let's say. So they're going to fail the test of increasing self-determination. They're going to fail the test of autonomy, and they're also going to fail the test of privacy, as they capture all sorts of data without any acknowledgement and spread it to who knows what places.",
        "text_sha256": "fb9b68332438fde68b33d67178fbbe37b012990459cf719567726baed79fc97e"
      }
    },
    {
      "passage_id": "DISC-0064-P010",
      "word_span": [
        440,
        525
      ],
      "text": "So we have a company that scores well, like Apple, a company that scores poorly, TikTok. And then that's the way this model would develop. We find each company and define it in terms of each of these nine values, that is, score each company in terms of its autonomy, in terms of its dignity, and down the list to accountability and safety and so on. And in that way, we could form a hierarchy of humanitarian AI companies, from better to worse.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00028",
        "DISC-0064-RUN-20261031-01-SEG-00029",
        "DISC-0064-RUN-20261031-01-SEG-00030",
        "DISC-0064-RUN-20261031-01-SEG-00031",
        "DISC-0064-RUN-20261031-01-SEG-00032"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0017"
      ],
      "original_start_seconds": 203.66,
      "original_end_seconds": 235.61,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 10800,
        "char_end": 11244,
        "utf8_start": 10879,
        "utf8_end": 11323,
        "line_start": 218,
        "line_end": 218,
        "exact_text": "So we have a company that scores well, like Apple, a company that scores poorly, TikTok. And then that's the way this model would develop. We find each company and define it in terms of each of these nine values, that is, score each company in terms of its autonomy, in terms of its dignity, and down the list to accountability and safety and so on. And in that way, we could form a hierarchy of humanitarian AI companies, from better to worse.",
        "text_sha256": "9bd2cf1c4e3e381c8b8c3f31793acfbe562cbc60c6c8b82669ce0bfd35b47e1d"
      }
    }
  ]
}

Apple and TikTok comparison

Original display: 03:24.600–03:32.680
Selected frame: 03:25. Reading placement is editorial; display times are unchanged.

Open the full slide image

Displayed presentation wording:

AI HUMAN IMPACT

AI-generated visual description: An Apple-sign photograph sits above a TikTok app-store screenshot, with a vertical double-headed arrow alongside the two. There is no numeric scale. Photographer credits are not displayed here.

Displayed third-party app-store wording:

tik tok
TikTok - Make Your Day
Real People. Real Videos.
GET
Ad
In-App Purchases
TikTok is THE destination for mobile videos. On TikTok, short-form videos are exciting, spontaneous, and genuine. Whether

Editorial note: the description ends at “Whether” in the screenshot; its continuation is not supplied.

Additional displayed metadata: T-Mobile Wi-Fi · 12:09 AM · 92% · Cancel

Exact Markdown and source mapping

DISC-0064-VIS-011

**Displayed presentation wording:**

> AI HUMAN IMPACT

**AI-generated visual description:** An Apple-sign photograph sits above a TikTok app-store screenshot, with a vertical double-headed arrow alongside the two. There is no numeric scale. Photographer credits are not displayed here.

**Displayed third-party app-store wording:**

> tik tok
> TikTok - Make Your Day
> Real People. Real Videos.
> GET
> Ad
> In-App Purchases
> TikTok is THE destination for mobile videos. On TikTok, short-form videos are exciting, spontaneous, and genuine. Whether

*Editorial note: the description ends at “Whether” in the screenshot; its continuation is not supplied.*
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-011",
    "state_id": "DISC-0064-VIS-011",
    "heading": "Apple and TikTok comparison",
    "frame_source": "../frames/DISC-0064-VIS-011.jpg",
    "frame_sha256": "4eb9fa78d9e7757a4be06be7d1b846bc6db8f8c332234dd8d9a809c89aaf213f",
    "frame_pts_seconds": 205,
    "display_intervals": [
      {
        "start_seconds": 204.6,
        "end_seconds": 212.68,
        "duration_seconds": 8.08,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": true,
    "substantive_exception": null,
    "placement_after": "DISC-0064-P009",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed presentation wording:**\n\n> AI HUMAN IMPACT\n\n**AI-generated visual description:** An Apple-sign photograph sits above a TikTok app-store screenshot, with a vertical double-headed arrow alongside the two. There is no numeric scale. Photographer credits are not displayed here.\n\n**Displayed third-party app-store wording:**\n\n> tik tok\n> TikTok - Make Your Day\n> Real People. Real Videos.\n> GET\n> Ad\n> In-App Purchases\n> TikTok is THE destination for mobile videos. On TikTok, short-form videos are exciting, spontaneous, and genuine. Whether\n\n*Editorial note: the description ends at “Whether” in the screenshot; its continuation is not supplied.*",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-011.jpg",
        "original_evidence_image_sha256": "3c95fe6185b2229f8a1475ab09f2fbefbd8a1fd7d92e146bc26c8b791ca522f2",
        "original_evidence_pts_seconds": 210,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\visual_scan\\frame-000210000000.jpg",
        "evaluated_slide_markdown_sha256": "09a04abf23f13d450b120115663fa893bb30f1676a4f2878eaab235a507c425b",
        "evaluated_placement_after": "DISC-0064-P009",
        "placement_assessment": "After P009 before P010 company hierarchy; source comparison begins just after this paragraph boundary.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": "SECOND_PASS_ENCODING_REPAIRS.json"
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "ancillary_displayed_interface_text": [
      "T-Mobile Wi-Fi",
      "12:09 AM",
      "92%",
      "Cancel"
    ],
    "markdown_span": {
      "char_start": 9882,
      "char_end": 10734,
      "utf8_start": 9955,
      "utf8_end": 10811,
      "line_start": 192,
      "line_end": 216,
      "exact_text": "<!-- DISC-0064-VIS-011 | display timing in companion; reading placement is editorial -->\n\n### Apple and TikTok comparison\n\n![Original video frame at 03:25.000](../frames/DISC-0064-VIS-011.jpg)\n\n**Displayed presentation wording:**\n\n> AI HUMAN IMPACT\n\n**AI-generated visual description:** An Apple-sign photograph sits above a TikTok app-store screenshot, with a vertical double-headed arrow alongside the two. There is no numeric scale. Photographer credits are not displayed here.\n\n**Displayed third-party app-store wording:**\n\n> tik tok\n> TikTok - Make Your Day\n> Real People. Real Videos.\n> GET\n> Ad\n> In-App Purchases\n> TikTok is THE destination for mobile videos. On TikTok, short-form videos are exciting, spontaneous, and genuine. Whether\n\n*Editorial note: the description ends at “Whether” in the screenshot; its continuation is not supplied.*\n\n",
      "text_sha256": "31d831e8964ab9acfebb6c28fc9bce80ece55af2c60db837414096cbcf300c06"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P009",
      "word_span": [
        364,
        440
      ],
      "text": "Whereas, by contrast, a company like TikTok, which is part of ByteDance, a company or a conglomerate like that captures users in addictive dark patterns, dopamine patterns, let's say. So they're going to fail the test of increasing self-determination. They're going to fail the test of autonomy, and they're also going to fail the test of privacy, as they capture all sorts of data without any acknowledgement and spread it to who knows what places.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00023",
        "DISC-0064-RUN-20261031-01-SEG-00024",
        "DISC-0064-RUN-20261031-01-SEG-00025",
        "DISC-0064-RUN-20261031-01-SEG-00026",
        "DISC-0064-RUN-20261031-01-SEG-00027",
        "DISC-0064-RUN-20261031-01-SEG-00028"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0004"
      ],
      "original_start_seconds": 174.71,
      "original_end_seconds": 203.66,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 7082,
        "char_end": 7531,
        "utf8_start": 7117,
        "utf8_end": 7566,
        "line_start": 146,
        "line_end": 146,
        "exact_text": "Whereas, by contrast, a company like TikTok, which is part of ByteDance, a company or a conglomerate like that captures users in addictive dark patterns, dopamine patterns, let's say. So they're going to fail the test of increasing self-determination. They're going to fail the test of autonomy, and they're also going to fail the test of privacy, as they capture all sorts of data without any acknowledgement and spread it to who knows what places.",
        "text_sha256": "fb9b68332438fde68b33d67178fbbe37b012990459cf719567726baed79fc97e"
      }
    },
    {
      "passage_id": "DISC-0064-P010",
      "word_span": [
        440,
        525
      ],
      "text": "So we have a company that scores well, like Apple, a company that scores poorly, TikTok. And then that's the way this model would develop. We find each company and define it in terms of each of these nine values, that is, score each company in terms of its autonomy, in terms of its dignity, and down the list to accountability and safety and so on. And in that way, we could form a hierarchy of humanitarian AI companies, from better to worse.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00028",
        "DISC-0064-RUN-20261031-01-SEG-00029",
        "DISC-0064-RUN-20261031-01-SEG-00030",
        "DISC-0064-RUN-20261031-01-SEG-00031",
        "DISC-0064-RUN-20261031-01-SEG-00032"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0017"
      ],
      "original_start_seconds": 203.66,
      "original_end_seconds": 235.61,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 10800,
        "char_end": 11244,
        "utf8_start": 10879,
        "utf8_end": 11323,
        "line_start": 218,
        "line_end": 218,
        "exact_text": "So we have a company that scores well, like Apple, a company that scores poorly, TikTok. And then that's the way this model would develop. We find each company and define it in terms of each of these nine values, that is, score each company in terms of its autonomy, in terms of its dignity, and down the list to accountability and safety and so on. And in that way, we could form a hierarchy of humanitarian AI companies, from better to worse.",
        "text_sha256": "9bd2cf1c4e3e381c8b8c3f31793acfbe562cbc60c6c8b82669ce0bfd35b47e1d"
      }
    }
  ]
}

Comparison with the nine values

Original display: 03:53.360–04:11.480
Selected frame: 03:55. Reading placement is editorial; display times are unchanged.

Original presentation frame: Comparison with the nine values

Displayed presentation wording:

AI HUMAN IMPACT
Autonomy
Dignity
Privacy
Fairness
Solidarity
Sustainability
Performance
Safety
Accountability

AI-generated visual description: The Apple photograph, TikTok app-store screenshot and vertical double-headed arrow reappear; the nine-value list is now added at the left. This is a meaningful build relative to the earlier comparison.

Displayed third-party app-store wording:

tik tok
TikTok - Make Your Day
Real People. Real Videos.
GET
Ad
In-App Purchases
TikTok is THE destination for mobile videos. On TikTok, short-form videos are exciting, spontaneous, and genuine. Whether

Editorial note: the description ends at “Whether” in the screenshot; its continuation is not supplied.

Additional displayed metadata: T-Mobile Wi-Fi · 12:09 AM · 92% · Cancel

Exact Markdown and source mapping

DISC-0064-VIS-012

**Displayed presentation wording:**

> AI HUMAN IMPACT
> Autonomy
> Dignity
> Privacy
> Fairness
> Solidarity
> Sustainability
> Performance
> Safety
> Accountability

**AI-generated visual description:** The Apple photograph, TikTok app-store screenshot and vertical double-headed arrow reappear; the nine-value list is now added at the left. This is a meaningful build relative to the earlier comparison.

**Displayed third-party app-store wording:**

> tik tok
> TikTok - Make Your Day
> Real People. Real Videos.
> GET
> Ad
> In-App Purchases
> TikTok is THE destination for mobile videos. On TikTok, short-form videos are exciting, spontaneous, and genuine. Whether

*Editorial note: the description ends at “Whether” in the screenshot; its continuation is not supplied.*
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-012",
    "state_id": "DISC-0064-VIS-012",
    "heading": "Comparison with the nine values",
    "frame_source": "../frames/DISC-0064-VIS-012.jpg",
    "frame_sha256": "ee925be6cc286ab0593aec1ac8d316edaaac974f41a139f9f658a38e7a4826f0",
    "frame_pts_seconds": 235,
    "display_intervals": [
      {
        "start_seconds": 233.36,
        "end_seconds": 251.48,
        "duration_seconds": 18.12,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": true,
    "substantive_exception": null,
    "placement_after": "DISC-0064-P010",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed presentation wording:**\n\n> AI HUMAN IMPACT\n> Autonomy\n> Dignity\n> Privacy\n> Fairness\n> Solidarity\n> Sustainability\n> Performance\n> Safety\n> Accountability\n\n**AI-generated visual description:** The Apple photograph, TikTok app-store screenshot and vertical double-headed arrow reappear; the nine-value list is now added at the left. This is a meaningful build relative to the earlier comparison.\n\n**Displayed third-party app-store wording:**\n\n> tik tok\n> TikTok - Make Your Day\n> Real People. Real Videos.\n> GET\n> Ad\n> In-App Purchases\n> TikTok is THE destination for mobile videos. On TikTok, short-form videos are exciting, spontaneous, and genuine. Whether\n\n*Editorial note: the description ends at “Whether” in the screenshot; its continuation is not supplied.*",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-012.jpg",
        "original_evidence_image_sha256": "b7c74d60657a21df369a8e208260437c99d0c13f1afb34962d266e4e722c87f8",
        "original_evidence_pts_seconds": 250,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\visual_scan\\frame-000250000000.jpg",
        "evaluated_slide_markdown_sha256": "df1a85ff1273b4cc77d5f52466b27e93acf9304b6aa07d98f089a72bac9c962e",
        "evaluated_placement_after": "DISC-0064-P010",
        "placement_assessment": "After P010 hierarchy/nine-value description before P011 investment-grade conclusion; display spans that transition.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": "SECOND_PASS_ENCODING_REPAIRS.json"
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "ancillary_displayed_interface_text": [
      "T-Mobile Wi-Fi",
      "12:09 AM",
      "92%",
      "Cancel"
    ],
    "markdown_span": {
      "char_start": 11246,
      "char_end": 12222,
      "utf8_start": 11325,
      "utf8_end": 12305,
      "line_start": 220,
      "line_end": 253,
      "exact_text": "<!-- DISC-0064-VIS-012 | display timing in companion; reading placement is editorial -->\n\n### Comparison with the nine values\n\n![Original video frame at 03:55.000](../frames/DISC-0064-VIS-012.jpg)\n\n**Displayed presentation wording:**\n\n> AI HUMAN IMPACT\n> Autonomy\n> Dignity\n> Privacy\n> Fairness\n> Solidarity\n> Sustainability\n> Performance\n> Safety\n> Accountability\n\n**AI-generated visual description:** The Apple photograph, TikTok app-store screenshot and vertical double-headed arrow reappear; the nine-value list is now added at the left. This is a meaningful build relative to the earlier comparison.\n\n**Displayed third-party app-store wording:**\n\n> tik tok\n> TikTok - Make Your Day\n> Real People. Real Videos.\n> GET\n> Ad\n> In-App Purchases\n> TikTok is THE destination for mobile videos. On TikTok, short-form videos are exciting, spontaneous, and genuine. Whether\n\n*Editorial note: the description ends at “Whether” in the screenshot; its continuation is not supplied.*\n\n",
      "text_sha256": "142274459afb83982a41132e1c30f584847d7b647d8475d880d035e6464cfb9d"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P009",
      "word_span": [
        364,
        440
      ],
      "text": "Whereas, by contrast, a company like TikTok, which is part of ByteDance, a company or a conglomerate like that captures users in addictive dark patterns, dopamine patterns, let's say. So they're going to fail the test of increasing self-determination. They're going to fail the test of autonomy, and they're also going to fail the test of privacy, as they capture all sorts of data without any acknowledgement and spread it to who knows what places.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00023",
        "DISC-0064-RUN-20261031-01-SEG-00024",
        "DISC-0064-RUN-20261031-01-SEG-00025",
        "DISC-0064-RUN-20261031-01-SEG-00026",
        "DISC-0064-RUN-20261031-01-SEG-00027",
        "DISC-0064-RUN-20261031-01-SEG-00028"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00023-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00024-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00025-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00026-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00027-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0004"
      ],
      "original_start_seconds": 174.71,
      "original_end_seconds": 203.66,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 7082,
        "char_end": 7531,
        "utf8_start": 7117,
        "utf8_end": 7566,
        "line_start": 146,
        "line_end": 146,
        "exact_text": "Whereas, by contrast, a company like TikTok, which is part of ByteDance, a company or a conglomerate like that captures users in addictive dark patterns, dopamine patterns, let's say. So they're going to fail the test of increasing self-determination. They're going to fail the test of autonomy, and they're also going to fail the test of privacy, as they capture all sorts of data without any acknowledgement and spread it to who knows what places.",
        "text_sha256": "fb9b68332438fde68b33d67178fbbe37b012990459cf719567726baed79fc97e"
      }
    },
    {
      "passage_id": "DISC-0064-P010",
      "word_span": [
        440,
        525
      ],
      "text": "So we have a company that scores well, like Apple, a company that scores poorly, TikTok. And then that's the way this model would develop. We find each company and define it in terms of each of these nine values, that is, score each company in terms of its autonomy, in terms of its dignity, and down the list to accountability and safety and so on. And in that way, we could form a hierarchy of humanitarian AI companies, from better to worse.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00028",
        "DISC-0064-RUN-20261031-01-SEG-00029",
        "DISC-0064-RUN-20261031-01-SEG-00030",
        "DISC-0064-RUN-20261031-01-SEG-00031",
        "DISC-0064-RUN-20261031-01-SEG-00032"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00028-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00029-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00030-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0017",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0018",
        "DISC-0064-RUN-20261031-01-SEG-00031-WORD-0019",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00032-WORD-0017"
      ],
      "original_start_seconds": 203.66,
      "original_end_seconds": 235.61,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 10800,
        "char_end": 11244,
        "utf8_start": 10879,
        "utf8_end": 11323,
        "line_start": 218,
        "line_end": 218,
        "exact_text": "So we have a company that scores well, like Apple, a company that scores poorly, TikTok. And then that's the way this model would develop. We find each company and define it in terms of each of these nine values, that is, score each company in terms of its autonomy, in terms of its dignity, and down the list to accountability and safety and so on. And in that way, we could form a hierarchy of humanitarian AI companies, from better to worse.",
        "text_sha256": "9bd2cf1c4e3e381c8b8c3f31793acfbe562cbc60c6c8b82669ce0bfd35b47e1d"
      }
    }
  ]
}

Human impact as an investment strategy

So where we end up is with a set of what we could call investment-grade AI humanitarian companies. And then that leads back to the original question we had, which was: how to put AI ethics into practice. And one practical answer is to develop and participate in this kind of AI human impact investing.

And then, one last point: it is your money.

This kind of investment strategy, this is not charity, it's not altruism. This is a way to benefit financially, because I believe that AI-intensive companies, companies that ensure the technology genuinely serves human being, will outperform its competitors in the medium to long term.

So there's that too.

Source details

Speech references

  1. 03:56.840–04:19.100
  2. 04:20.150–04:24.900
  3. 04:25.780–04:47.340
  4. 04:47.660–04:49.370

Investment framework reminder

Original display: 04:28.640–04:32.480
Selected frame: 04:30. Reading placement is editorial; display times are unchanged.

Original presentation frame: Investment framework reminder

Displayed presentation wording:

AI HUMAN IMPACT INVESTING
Autonomy
Dignity
Privacy
Fairness
Solidarity
Sustainability
Performance
Safety
Accountability

AI-generated visual description: The nine values are displayed as a single list. The earlier Apple and TikTok images and arrow are absent.

Exact Markdown and source mapping

DISC-0064-VIS-013

**Displayed presentation wording:**

> AI HUMAN IMPACT INVESTING
> Autonomy
> Dignity
> Privacy
> Fairness
> Solidarity
> Sustainability
> Performance
> Safety
> Accountability

**AI-generated visual description:** The nine values are displayed as a single list. The earlier Apple and TikTok images and arrow are absent.
{
  "visual_occurrence": {
    "occurrence_id": "DISC-0064-VIS-013",
    "state_id": "DISC-0064-VIS-013",
    "heading": "Investment framework reminder",
    "frame_source": "../frames/DISC-0064-VIS-013.jpg",
    "frame_sha256": "dcde91d477396432e11ed0050b87f4445570ee436f3c525b43c2eeb9fd2ec89d",
    "frame_pts_seconds": 270,
    "display_intervals": [
      {
        "start_seconds": 268.64,
        "end_seconds": 272.48,
        "duration_seconds": 3.84,
        "boundary_basis": "First changed source frame PTS; every-frame hard-cut detection and direct before/after original-frame comparison. End is exclusive first next-state frame."
      }
    ],
    "five_second_threshold_met": false,
    "substantive_exception": "Short substantive recap ties the nine values back to the investment strategy.",
    "placement_after": "DISC-0064-P013",
    "placement_semantics": "Editorial paragraph boundary; actual display interval is stored separately. No claim that all displayed wording was spoken.",
    "markdown": "**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Autonomy\n> Dignity\n> Privacy\n> Fairness\n> Solidarity\n> Sustainability\n> Performance\n> Safety\n> Accountability\n\n**AI-generated visual description:** The nine values are displayed as a single list. The earlier Apple and TikTok images and arrow are absent.",
    "attribution": "Displayed presentation wording is separately labelled; creator of slide layout not independently established. Named published quotations remain third-party. AI-generated descriptions are editorial additions.",
    "assessment": {
      "content": 3,
      "placement": 3,
      "attribution": 3,
      "pass_1_basis": "Direct native original-video frame examination, complete cut-context contact sheets, speech paragraph source times and full frame text.",
      "second_pass": {
        "status": "complete",
        "result": "agree",
        "direct_original_evidence_compared": true,
        "reviewer": "Codex AI; separate later pass by same agent, not an independent model or human",
        "original_evidence_image": "../evidence/second_pass/DISC-0064-VIS-013.jpg",
        "original_evidence_image_sha256": "a6638761b6d802ec093112ff1b97f08223cbb4652024af97cffc6c90c3624ae9",
        "original_evidence_pts_seconds": 268.64,
        "inspection_path": "C:\\Users\\JB\\Desktop\\James-Agent-Population\\James-Agent-AIHumanCondition\\AI-Human-Condition-Book\\exports\\DISC-0064_recovery_2026-10-31_01\\scene_scan\\cut-25-268.640.jpg",
        "evaluated_slide_markdown_sha256": "0d68414620d6e72082eea0d7c0cb03cc2911c89a1faab45f3d1366cab2180d9d",
        "evaluated_placement_after": "DISC-0064-P013",
        "placement_assessment": "After P013 financial-investment explanation before P014 closing aside; source value recap appears earlier within P013, and actual display time is separately retained.",
        "attribution_assessment": "Printed text, named third-party material, spoken paragraph and AI description remain separately labelled. Layout authorship is not silently assigned to James.",
        "content_assessment": "Direct frame wording/table/diagram and preserved builds agree with repaired Markdown. Explicit minor cropping/overlay qualifications retained.",
        "encoding_repair_evidence": null
      }
    },
    "automatic_clearance": true,
    "qualifications": [],
    "markdown_span": {
      "char_start": 13055,
      "char_end": 13573,
      "utf8_start": 13144,
      "utf8_end": 13662,
      "line_start": 265,
      "line_end": 286,
      "exact_text": "<!-- DISC-0064-VIS-013 | display timing in companion; reading placement is editorial -->\n\n### Investment framework reminder\n\n![Original video frame at 04:30.000](../frames/DISC-0064-VIS-013.jpg)\n\n**Displayed presentation wording:**\n\n> AI HUMAN IMPACT INVESTING\n> Autonomy\n> Dignity\n> Privacy\n> Fairness\n> Solidarity\n> Sustainability\n> Performance\n> Safety\n> Accountability\n\n**AI-generated visual description:** The nine values are displayed as a single list. The earlier Apple and TikTok images and arrow are absent.\n\n",
      "text_sha256": "7cbf993da0ffb7600e35fed41a6a47966c800d5ff2768aad6489fab76c0b75d1"
    }
  },
  "speech_paragraphs": [
    {
      "passage_id": "DISC-0064-P011",
      "word_span": [
        525,
        582
      ],
      "text": "So where we end up is with a set of what we could call investment-grade AI humanitarian companies. And then that leads back to the original question we had, which was: how to put AI ethics into practice. And one practical answer is to develop and participate in this kind of AI human impact investing.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00033",
        "DISC-0064-RUN-20261031-01-SEG-00034",
        "DISC-0064-RUN-20261031-01-SEG-00035",
        "DISC-0064-RUN-20261031-01-SEG-00036",
        "DISC-0064-RUN-20261031-01-SEG-00037"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00033-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0014",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0015",
        "DISC-0064-RUN-20261031-01-SEG-00034-WORD-0016",
        "DISC-0064-RUN-20261031-01-SEG-00035-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00035-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00035-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00035-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00035-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00035-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00035-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00035-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00036-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00036-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00036-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00036-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00036-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00036-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00036-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00037-WORD-0010"
      ],
      "original_start_seconds": 236.84,
      "original_end_seconds": 259.1,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 12288,
        "char_end": 12589,
        "utf8_start": 12373,
        "utf8_end": 12674,
        "line_start": 255,
        "line_end": 255,
        "exact_text": "So where we end up is with a set of what we could call investment-grade AI humanitarian companies. And then that leads back to the original question we had, which was: how to put AI ethics into practice. And one practical answer is to develop and participate in this kind of AI human impact investing.",
        "text_sha256": "c8867f1a1441eb1027bc8535e4d8a3eff567fb89a06a4567e1676040d6a9dda1"
      }
    },
    {
      "passage_id": "DISC-0064-P012",
      "word_span": [
        582,
        591
      ],
      "text": "And then, one last point: it is your money.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00038"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00038-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00038-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00038-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00038-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00038-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00038-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00038-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00038-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00038-WORD-0009"
      ],
      "original_start_seconds": 260.15,
      "original_end_seconds": 264.9,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 12657,
        "char_end": 12700,
        "utf8_start": 12744,
        "utf8_end": 12787,
        "line_start": 259,
        "line_end": 259,
        "exact_text": "And then, one last point: it is your money.",
        "text_sha256": "4f8d7b38254d0c716bfb92a93a313fda30c05e5b3c497fa9c34e81e86a4e0f35"
      }
    },
    {
      "passage_id": "DISC-0064-P013",
      "word_span": [
        591,
        636
      ],
      "text": "This kind of investment strategy, this is not charity, it's not altruism. This is a way to benefit financially, because I believe that AI-intensive companies, companies that ensure the technology genuinely serves human being, will outperform its competitors in the medium to long term.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00039",
        "DISC-0064-RUN-20261031-01-SEG-00040",
        "DISC-0064-RUN-20261031-01-SEG-00041",
        "DISC-0064-RUN-20261031-01-SEG-00042",
        "DISC-0064-RUN-20261031-01-SEG-00043",
        "DISC-0064-RUN-20261031-01-SEG-00044"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00039-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00039-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00039-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00039-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00039-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00040-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00040-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00040-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00040-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00040-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00040-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00040-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00041-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00041-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00041-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00041-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00041-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00041-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00041-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00042-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00042-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00042-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00042-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00042-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00042-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00042-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0006",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0007",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0008",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0009",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0010",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0011",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0012",
        "DISC-0064-RUN-20261031-01-SEG-00043-WORD-0013",
        "DISC-0064-RUN-20261031-01-SEG-00044-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00044-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00044-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00044-WORD-0004",
        "DISC-0064-RUN-20261031-01-SEG-00044-WORD-0005",
        "DISC-0064-RUN-20261031-01-SEG-00044-WORD-0006"
      ],
      "original_start_seconds": 265.78,
      "original_end_seconds": 287.34,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 12768,
        "char_end": 13053,
        "utf8_start": 12857,
        "utf8_end": 13142,
        "line_start": 263,
        "line_end": 263,
        "exact_text": "This kind of investment strategy, this is not charity, it's not altruism. This is a way to benefit financially, because I believe that AI-intensive companies, companies that ensure the technology genuinely serves human being, will outperform its competitors in the medium to long term.",
        "text_sha256": "59a435e31816c75cb30f212b6063f8f6e6de141ff48535179b90c450dbaa3b83"
      }
    },
    {
      "passage_id": "DISC-0064-P014",
      "word_span": [
        636,
        640
      ],
      "text": "So there's that too.",
      "edit_reason": "Thought-based paragraph assembly; punctuation/capitalization, AI-intensive/investment-grade hyphenation, Apple/TikTok/ByteDance orthography; routine duplicated scoring/individual/privacy and was-is restart removed where present. Substantive wording and sequence retained.",
      "edit_basis": "Editorial preparation from immutable raw recognition; targeted machine-supported lexical changes separately recorded after comparison.",
      "raw_segment_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00045"
      ],
      "raw_word_ids": [
        "DISC-0064-RUN-20261031-01-SEG-00045-WORD-0001",
        "DISC-0064-RUN-20261031-01-SEG-00045-WORD-0002",
        "DISC-0064-RUN-20261031-01-SEG-00045-WORD-0003",
        "DISC-0064-RUN-20261031-01-SEG-00045-WORD-0004"
      ],
      "original_start_seconds": 287.66,
      "original_end_seconds": 289.37,
      "time_semantics": "Parent recognition word/segment bounds; not newly measured paragraph boundaries. Shared segment IDs at thought breaks are intentional.",
      "speaker": "James Brusseau",
      "markdown_span": {
        "char_start": 13639,
        "char_end": 13659,
        "utf8_start": 13730,
        "utf8_end": 13750,
        "line_start": 288,
        "line_end": 288,
        "exact_text": "So there's that too.",
        "text_sha256": "c7084adf7bad977d8e186d37456177b352b0ba671fe6ed81def0971fa8ef9020"
      }
    }
  ]
}