The following is a conversation with Michael Kerns. He's a professor at the University of Pennsylvania

and a co-author of the new book Ethical Algorithm that is the focus of much of this conversation.

It includes algorithmic fairness bias privacy and ethics in general, but that is just one of

many fields that Michael is a world-class researcher in, some of which we touch on quickly,

including learning theory or the theoretical foundation of machine learning,

game theory, quantitative finance, computational social science and much more.

But on a personal note, when I was an undergrad early on, I worked with Michael on an algorithmic

trading project and competition that he led. That's when I first fell in love with algorithmic

game theory. While most of my research life has been a machine learning and human robot interaction,

the systematic way that game theory reveals the beautiful structure in our competitive

and cooperating world of humans has been a continued inspiration to me.

So for that and other things, I'm deeply thankful to Michael and really enjoyed having this

conversation again in person after so many years. This is the Artificial Intelligence Podcast.

If you enjoy it, subscribe by YouTube, give it five stars on Apple Podcast, support it on Patreon,

or simply connect with me on Twitter, Alex Friedman spelled F-R-I-D-M-A-N.

This episode is supported by an amazing podcast called Pessimists Archive.

Jason, the host of the show, reached out to me, look at the support this podcast,

and so I listened to it to check it out. And by listen, I mean I went through it, Netflix,

Bench style, at least five episodes in a row. It's not one of my favorite podcasts and I think

it should be one of the top podcasts in the world, frankly. It's a history show about why people

resist new things. Each episode looks at a moment in history when something new was introduced,

something that today we think of as commonplace, like recorded music, umbrellas, bicycles, cars,

...