How to put AI ethics into practice? AI Human Impact

James Brusseau · AI Policy Exchange · published 7 August 2020

Author-accepted conservative reading edition, with documented limitations. Acceptance does not constitute whole-recording human acoustic verification.

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.

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.

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.

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.

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.

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.