7min chapter

Carnegie Council Podcasts cover image

Is AI Just an Artifact? with Joanna Bryson

Carnegie Council Podcasts

CHAPTER

Unraveling the Guest's Journey in AI

Exploring the guest's background, from their interest in animal behavior to their academic pursuits in behavioral sciences, AI, and philosophy. Contrasting the American and European approaches to AI research, considering historical contexts, funding priorities, and societal attitudes towards academia and innovation.

00:00
Speaker 2
Before we dive into your work and insights, Joanna, to help our listeners better understand your unique perspective in the realm of AI and the Jason Fields, could you share a bit about your background, what sparked your interest in this domain, especially at the intersection of human cognition and machine capabilities?
Speaker 1
I think I have a unique preparation, but I hope my perspective isn't that unique. It's kind of strange. Actually it's one local politician in Berlin that's like, oh, I have to do AI now and I'm reading all your papers and it all seems really obvious. I'm like, yeah. But anyway, I actually was really interested in animal behavior. I wanted to understand why different animals, why was that just, that was interesting in some general, but I realized that people are very defensive. So I thought it was better to study other animals. I was a big fan of Jane Goodall. And so I did a degree in behavioral sciences from University of Chicago. And sometime during that, I realized that a lot of human intelligence is actually sort of automatic. And also I was a science fiction fan. So I decided I would like to get involved in artificial intelligence. Oh, also I was a good programmer. It turned out I was a surprisingly good programmer. And so I thought that would be an advantage and I could get into a better PhD program if I did all that. However, I wasn't totally sure what to do my PhD in. And so I wound up programming professionally for five years, which turned out to be really useful. It was really the entire, like everything from like fixing printers to designing systems, as well as writing a lot of software. That was in the 1980s and then in 1991 I went and did my Master's degree in artificial intelligence from Edinburgh. And the great thing about that was that Edinburgh actually had artificial intelligence before computer science. So they really took artificial intelligence to be the mix of philosophy, psychology, neuroscience, music, linguistics, and of course computer science as well. But it wasn't like just some subsidiary bit of engineering. It was really a proper discipline itself. And so that was fantastic. And then I got into MIT, which was great. I didn't have a computer science degree yet. And so that was a lot of work. But eventually I escaped somewhere in the middle. I actually got another philosophy degree just because I wanted to work in a lab. And that was the easiest way to get funded to do that for a couple of years. So I worked in a climate cognitive, it was called a climate cognitive neuroscience lab, but there was no neuroscience. It was actually all behavioral. And the monkeys actually had better touch screens than I did. My computer was like a 286 and there's a 386. Anyway, this is a long time ago too. So from then I went into a computer. Actually I first did another psychology postdoc at Harvard, also in a primate lab that was also called cognitive neuroscience. So it's also to do anything invasive. It was really weird. But I was with Mark Houser, which was education otherwise. And then because he was actually working on, I think I'm credited on his moral book that came out right when it was found out that he was doing a committee fraud. So that was interesting. But he was a great mentor. I done me turn them down. I really liked working in that group. But I hated being a postdoc. And also even Harvard undergraduates could not figure out how to use my software. So I figured out that I needed to spend some more time in the computer science department, preferably one with good human computer interactions so that I could make my AI systems more usable. And so that's when I went to University of Bath. It was also at that time very hard to get positions in artificial intelligence in the United States unless you're either willing to work on weapons systems or pharmaceutical. And I was still trying to do science. And everybody in Britain sort of welcomed me back with open arms. They still thought of AI as a science and not as engineering, engineering destruction or whatever. So anyway, I've basically been in Europe professionally ever since, although I did spend a few years living in New Jersey when my husband was poached by Princeton. And I did a good sabbatical there actually with the Center for Information Technology Policy who also kept me around as an affiliate for a few years after that.
Speaker 2
It's very interesting what you said that there was such a difference between the American climate at that point and the European climate. You see the one in America that focuses very much like you said more on the defense side and what was the other thing you said? Other
Speaker 1
people.
Speaker 2
There's a lot of money in drugs. Exactly. And then it was more treated as a science in Europe. What do you attribute that to, given the timing of it as well?
Speaker 1
Yeah, I don't entirely know. But I have to say that there are way more differences between America and Europe than Europeans tend to realize. America was founded by fundamentalists and there's a lot more sort of black and white attitudes there. And of course, people are starting to realize that it's a little more libertarian and less well regulated. So I think partly just the domination of the military industrial complex and the pharmaceutical industrial complex, academic complex was why those were the things that were sucking up frames then. What's kind of interesting is that Europe still thought it was worth funding at that time, at least now I've written this as harder, but it still thought it was funding worth funding philosophies, blue sky science. And this is before 2008. I remember after 2008, a couple times, the people just talking about how important it was, the academic research really served a purpose. And I was able to get up and say, look, I wouldn't have been ready for studying what AI is doing in human society. If I hadn't spent like 10 or 15 years of my life looking at theoretical biology, just totally blue sky. And we have to support the blue sky sciences. But I don't mean to say there's no place in America that does that. Maybe right now there's more places than in Europe, but at the time, especially Britain was very, they're very tolerant of eccentricity. As long as you did a couple of papers on mainstream computer science that they could show that they're funding agencies, that they had good researchers there, then they let you spend the rest of your time as you saw fit. And that was, I didn't realize how lucky I was to be in a computer science department. Other disciplines that didn't have as obvious of payoffs to the economy were under a lot more pressure to perform and to keep coming up with being stream articles.

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