This Is How Algorithms Impact Every Aspect Of Our Lives, from News to Credit Scores to Stocks

Tracy Alloway (0:09)

Hello, and welcome to another edition of the Odd Lots Podcast. I'm Tracy Alloway.

Joe Weisenthal (0:14)

And I'm Joe Weisenthal.

Tracy Alloway (0:16)

So Joe, you know what I was thinking?

Joe Weisenthal (0:19)

No, I don't actually. What were you thinking?

Tracy Alloway (0:22)

That was a pretty open-ended question in retrospect.

Joe Weisenthal (0:25)

That would have been pretty impressive if I had gotten it right.

Tracy Alloway (0:27)

All right, what I was thinking is that we have a tendency on this show to talk a lot about quantitative trading. We talk a lot about high-frequency trading, systematic trading strategies, and we don't actually talk that much about the things that underpin all those strategies. Do you know what I'm talking about?

Joe Weisenthal (0:48)

I've thought about this before. So we just sort of speak in the abstract about what quants are doing, or we're like, oh, humans have no chance anymore at beating the algorithms.

But they're sort of in the general discussion, and I think we're a little bit better than this here, to be honest. But I think of the general discussion about all these things, we don't really dive into the math and how it really works and who comes up with all this stuff.

Tracy Alloway (1:14)

Right, right. So you hit the nail exactly on the head. So we don't talk that much about the algorithms, and there is this perception out there that the algorithms or the maths doing all this stuff are better than human beings. And I think that's a question, I don't think we actually have the answer to that. It's just an assumption that people have made. And in recent years, we have seen lots of people start to talk about weaknesses in the algorithms that underlie a lot of these strategies. And I should just say here, when we talk about algorithms, yes, you think trading, you think finance, but algorithms kind of rule our lives in a lot of different ways. Now you see a lot of the applications in business, whether it's dynamic pricing on Amazon or online advertising or content curation.

Think about the Netflix movies that get shown to you all the time.

Algorithms and the assumptions underpinning them are basically everywhere at the moment. And we're not really asking enough of the tough questions about them, I think.

Joe Weisenthal (2:21)

My most frequent thinking about algorithms these days is when I drive out of the city and I use the Weis app and it tells me like different paths to beat traffic. And sometimes it seems like it gets it totally wrong. Usually it does an amazing job. And sometimes I second guess it and regret it.

But sometimes it's like, oh, how did I get in this situation? So I have firsthand experience with occasionally they don't work perfectly.

Tracy Alloway (2:47)

Right, okay, everyone has an algorithm experience. Like you watch that one bad movie on Netflix and then suddenly for the rest of your life, you're getting pushed sequels.

Joe Weisenthal (2:58)

Or in my case, cause I have a 20 month old daughter when I go on, it just thinks that all I want to watch is children's shows.

Tracy Alloway (3:06)

So those are some of the downsides of algorithms, but I think we can do better than that. We have a really good guest to talk about all the assumptions that are actually going into these things. And it is someone I've spoken to before back in my previous life over at the Financial Times. It's Frank Pasquale. He's professor of law at the University of Maryland. He's also the author of an entire book on this subject called The Black Box Society.

Frank, thank you so much for coming on.

Frank Pasquale (3:47)

Oh, thank you, Tracy and Joe, it's great to be here.

Tracy Alloway (3:50)

So you've clearly identified some of the issues with algorithms. I think you give it away a little bit in the title of your book, The Black Box Society. These are things that are shaping our society, but we don't actually know a lot about what's going into them. Essentially, they're a black box.

What piqued your interest in this subject?

Frank Pasquale (4:11)

You know, it's a long history. I began back in 2006 looking at search engines. At the time, I was just so enthused about the way in which they helped you find things and how much easier they made research and finding music and movies and stuff. My first articles on them were all about how you could expand Fair Use Doctrine to get people more access to them.

But then I started looking at the dark side and seeing there were all these disputes about what should be highly ranked or not so highly ranked. People that had really embarrassing or untrue stories about them that got really high in the rankings and they were trying to fight that.