Pamela McCorduck: Machines Who Think and the Early Days of AI | Lex Fridman Podcast #34

1. 0:00 – 3:25

   Why McCorduck wrote "Machines Who Think": from novelist to AI historian

   1. LFLex Fridman0:00

      The following is a conversation with Pamela McCorduck. She's an author who has written on the history and the philosophical significance of artificial intelligence. Her books include Machines Who Think in 1979, The Fifth Generation in 1983 with Ed Feigenbaum, who's considered to be the father of expert systems, The Edge of Chaos, The Futures of Women, and many more books. I came across her work in an unusual way, by stumbling on a quote from Machines Who Think that is something like, "Artificial intelligence began with the ancient wish to forge the gods." That was a beautiful way to draw a connecting line between our societal relationship with AI, from the grounded day-to-day science, math and engineering, to popular stories and science fiction and myths of automatons that go back for centuries. Through her literary work, she has spent a lot of time with the seminal figures of artificial intelligence, including the founding fathers of AI from the 1956 Dartmouth summer workshop where the field was launched. I reached out to Pamela for a conversation in hopes of getting a sense of what those early days were like, and how their dreams continue to reverberate through the work of our community today. I often don't know where the conversation may take us, but I jump in and see. Having no constraints, rules or goals is a wonderful way to discover new ideas. This is the Artificial Intelligence podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter @lexfridman, spelled F-R-I-D-M-A-N. And now, here's my conversation with Pamela McCorduck. In 1979, your book, Machines Who Think was published. In it, you interview some of the early AI pioneers and explore the idea that AI was born not out of maybe math and computer science, but out of myth and legend.

   2. PMPamela McCorduck2:08

      (laughs)

   3. LFLex Fridman2:09

      (laughs) So, uh, tell me if you could the story of how you first arrived at the book, the journey of-

   4. PMPamela McCorduck2:16

      Oh.

   5. LFLex Fridman2:17

      ... beginning to write it.

   6. PMPamela McCorduck2:20

      I had been a novelist. I'd published two novels. And I was sitting, uh, under, uh, the portal at Stanford one day in the house we were renting for the summer, and I thought, "I should write a novel about these weird people in AI I know." And then I thought, "Ah, don't write a novel. Write a history. Simple. Just go around, you know, interview them, splice it together. Voila, instant book. Ha, ha, ha." It was much harder than that. (laughs) But nobody else was doing it. And so I thought, "Well, this is a great opportunity." And there were people who, uh, John McCarthy for example, thought it was a nutty idea. There were much... You know, the field had not evolved yet, so on. And he had some mathematical thing he thought I should write instead. And I said, "No, John. I am not a woman in search of a project. I'm... This is what I want to do. I hope you'll cooperate." And he said, "Oh, mutter mutter. Well, okay. It's your, your time." And-

2. 3:25 – 4:17

   Meeting the founders while the field was still young

   1. LFLex Fridman3:25

      What was the pitch for the... I mean, such a young field at that point. How do you write a personal history of a field that's so young?

   2. PMPamela McCorduck3:34

      I said, "This is wonderful. The founders of the field are alive and kicking and able to talk about what they're doing."

   3. LFLex Fridman3:41

      Did they sound or feel like founders at the time? Did they know that they've been found- that they had founded something?

   4. PMPamela McCorduck3:48

      Oh, yeah. They knew what they were doing was very important, very. What they... Uh, what I now see in retrospect is that they were at the height of their research careers. And it's humbling to me that they took time out from all the things that they had to do as a consequence of being there, and to talk to this woman who said, "I think I'm going to write a book about you." (laughs) No, it was amazing, just amazing.

3. 4:17 – 5:18

   Dartmouth legacy and the four ‘founding fathers’ of AI

   1. LFLex Fridman4:17

      So who, who stands out to you, uh, maybe looking 63 years ago at the Dartmouth conference? The, so Marvin Minsky was there, McCarthy was there, Claude Shannon, Allen Newell, Herb Simon, some of the folks you've mentioned.

   2. PMPamela McCorduck4:34

      Right.

   3. LFLex Fridman4:35

      Um, then there's the other characters, right? Um, the one, one of your co-authors.

   4. PMPamela McCorduck4:40

      (laughs)

   5. LFLex Fridman4:41

      Uh, uh, uh-

   6. PMPamela McCorduck4:42

      He wasn't at Dartmouth.

   7. LFLex Fridman4:43

      He wasn't at Dartmouth.

   8. PMPamela McCorduck4:44

      No.

   9. LFLex Fridman4:44

      But I mean, in general.

   10. PMPamela McCorduck4:44

       He was, I think an undergraduate then.

   11. LFLex Fridman4:47

       (laughs) And, uh, and of course Joe Traub. I mean, all of these are players, not at Dartmouth, but, uh, in that era.

   12. PMPamela McCorduck4:56

       Right.

   13. LFLex Fridman4:56

       Uh, and C- CMU and so on. So who are the characters, if you could paint a picture, that stand out to you from memory? Those people you've interviewed and maybe not, people that were just in the...

   14. PMPamela McCorduck5:08

       In the am- the atmosphere.

   15. LFLex Fridman5:10

       In the atmosphere.

   16. PMPamela McCorduck5:11

       Uh, of course the four founding fathers were extraordinary guys. They really were.

   17. LFLex Fridman5:16

       Who are the founding fathers?

4. 5:18 – 11:22

   Her path into AI: Stanford, Feigenbaum, and early AI literature

   1. PMPamela McCorduck5:18

      Allen Newell, Herbert Simon, Marvin Minsky, John McCarthy. They were the four who were not only at the Dartmouth conference, but Newell and Simon arrived there with a working program, uh, called the Logic Theorist. Everybody else had great ideas about how they might do it, but they weren't gonna do it yet. Um, and you mentioned Joe Traub, my husband. I, I was immersed in AI before I met Joe, because I had been Ed Feigenbaum's assistant at Stanford. And before that, I had worked on a book by, edited by Feigenbaum and Julian Feldman called...... Computers and Thought. It was the first textbook of readings of AI. And they, they only did it because they were trying to teach AI to people at Berkeley, and there was nothing... You know, you'd have to send them to this journal and that journal. This was not the internet where you could go look at a, an article. So I was fascinated from the get-go by AI. I was an En- English major, you know, what did I know? And, uh, yet I was fascinated. And that's why you saw that historical, that literary background, which I, I think is very much a part of the continuum of AI. That, uh, that AI grew out of that same impulse.

   2. LFLex Fridman6:45

      Was that, yeah, that traditional. What, what was, what drew you to AI? How did you even think of it back, back then?

   3. PMPamela McCorduck6:53

      (laughs)

   4. LFLex Fridman6:53

      What, what was the possibilities, the dreams?

   5. PMPamela McCorduck6:55

      Uh... (laughs)

   6. LFLex Fridman6:56

      What was interesting to you?

   7. PMPamela McCorduck6:58

      Uh, the idea of intelligence outside the human cranium. This was a phenomenal idea. And even when I finished Machines Who Think, I didn't know if they were gonna succeed. I... In fact, the final chapter is very wishy-washy, frankly. Uh, well, succeed, the field did. Yeah.

   8. LFLex Fridman7:20

      Yeah. So was there the idea that, uh, that AI began with a wish to forge the god? So the, the spiritual component that we crave to create this other thing greater than ourselves. Wh- what?

   9. PMPamela McCorduck7:35

      For those guys, I don't think so. Newell and Simon were cognitive psychologists. What they wanted was to simulate aspects of human intelligence, and they found they could do it on the computer. Minsky just thought it was a really cool thing to do.

   10. LFLex Fridman7:58

       (laughs)

   11. PMPamela McCorduck7:59

       Likewise, McCarthy. McCarthy had got the idea in 1949 when, when he was a Caltech student, and he listened to somebody's lecture. It's, it's in my book, I forget who it was. Uh, and he thought, "Oh, that would be fun to do. How do we do that?" And he took a very mathematical approach. Uh, Minsky was hybrid, and Newell and Simon were very much cognitive psychology. How can we simulate various things about cog- about human cognition? What happened over the many years is, of course, our definition of intelligence expanded tremendously. I mean, these days, biologists are comfortable talking about the intelligence of cell, the intelligence of the brain, uh, the... And not just human brain, but, uh, the intelligence of any kind of brain. Uh, cephalopods. I mean...

   12. LFLex Fridman8:58

       Mm-hmm.

   13. PMPamela McCorduck8:59

       ... an octopus is really (laughs) intelligent by any ima- We wouldn't have thought of that in the '60s, even the '70s. So all these things have worked in, and I did hear one behavioral, uh, primatologist, Frans de Waal say, "AI taught us the questions to ask."

   14. LFLex Fridman9:21

       (laughs) Yeah, this is what happens, right? It's, uh... When you try to build it is when you start to actually ask questions if... It puts a mirror to ourselves.

   15. PMPamela McCorduck9:30

       Yeah. Right.

   16. LFLex Fridman9:31

       Right. So you were there in the middle of, of it. It seems like not many people were asking the questions that you were, or at least try- trying to look at this field the way you were.

   17. PMPamela McCorduck9:43

       I was solo. I... When I went to get funding for this, because I needed somebody to transcribe the, uh, interviews and I needed travel expenses, I went to everything you could think of, the NSF, the DARPA, um, there was an Air Force place that doled out money. And each of them said, "Well that was, that was very interesting. That's a very interesting idea. Uh, but we'll think about it." And the National Science Foundation actually said to me in plain English, "Hey, you're only a writer. You're not an historian of science." And I said, "Yeah, that's true, but, you know, the historians of science will be crawling all over this field. I'm writing for the general audience." So I thought. And they still wouldn't budge. I finally got a private grant without knowing who it was from, from Ed Fredkin at MIT. He had... He was a wealthy man, and he liked what he called crackpot ideas, and he considered-

   18. LFLex Fridman10:54

       This a crackpot idea?

   19. PMPamela McCorduck10:54

       ... this a crackpot idea, and he was-

   20. LFLex Fridman10:56

       (laughs)

   21. PMPamela McCorduck10:56

       ... willing to support it. I am ever grateful, let me say that.

   22. LFLex Fridman11:00

       You know, some would say that a history of science approach to AI, or even just a history, or anything like the book that you've written, hasn't been written since. By... I mean, I don't... M- Maybe I'm not familiar, but it's certainly not many. If we think about bigger than just these couple of decades, few decades-

   23. PMPamela McCorduck11:21

       Mm-hmm.

5. 11:22 – 12:59

   Mythic roots of AI: Homer, the Golem, Babbage, and a long human obsession

   1. LFLex Fridman11:22

      ... what, uh, what are the roots of AI that you-

   2. PMPamela McCorduck11:27

      Oh, they go back so far. Yes, of course, there's all the legendary stuff, the Golem and the early robots of the 20th century, but they go back much further than that. If you read Homer, Homer has robots in the Iliad. And a classical scholar was pointing out to me just a few months ago, "Well, you said you just read the Odyssey. The Odyssey is full of robots." "It is?" I said. "Yeah, how do you think Odysseus' ship gets from place, one place to another? He doesn't have the crew people to do that, the crew men." Uh, "Yeah, it, it's magic. It's robots." "Oh," I thought, "How interesting." (laughs) Uh, so-We've had this notion of AI for a long time. And then, toward the end of the 19th century, the beginning of the 20th century, there were scientists who actually tried to make this happen some way or another. Not successfully. They didn't have the technology for it. And of course, Babbage in the 1850s and '60s, he saw that what he was building was capable of, uh, intelligent behavior, and he... when he ran out of funding, the British government finally said, "That's enough." Uh, he and Lady Lovelace decided, "Oh, well, why don't we make... you know, why don't we play the ponies with this?" (laughs) He had other ideas for raising money too.

6. 12:59 – 14:22

   Hellenic vs Hebraic attitudes: welcoming robots vs fearing blasphemy

   1. LFLex Fridman12:59

      But if we actually reach back once again, uh, I think people don't actually really know that robots do appear or i- ideas of robots. You, you talk about the Hellenic and the Hebraic points of view.

   2. PMPamela McCorduck13:11

      Oh, yes, mm-hmm.

   3. LFLex Fridman13:12

      Can you tell me about each?

   4. PMPamela McCorduck13:15

      I defined it this way. The Hellenic point of view is robots are great. You know, they are party help. They helped this guy, Hephaestus, this god, Hephaestus in his forge. Uh, I presume he made them to help him, uh, and so on and so forth. And, and they, they welcome the whole idea of robots. The Hebraic view has to do with, I think, it's the second commandment, uh, "Thou shalt not make, uh, any graven image."

   5. LFLex Fridman13:46

      Mm-hmm.

   6. PMPamela McCorduck13:46

      In other words, you better not start imitating humans, because that's just forbidden, right? It's the second commandment. And a lot of the reaction to artificial intelligence has been, uh, a no- a, a sense that this is... this is somehow wicked. This is somehow blasphemous. We shouldn't be going there. Now, you can say, "Yeah, but there are gonna be some downsides." And I say, "Yes, there are, but blasphemy is not one of them." (laughs)

7. 14:22 – 23:35

   Frankenstein, machine villains, and the deeper psychology of AI fear

   1. LFLex Fridman14:22

      You know, there is a kind of fear that feels to be almost primal. Uh, is, is there a religious roots to that? Because so much of our society has religious roots, and so there is a feeling of, like you said, blasphemy, the... of, of creating the other, of creating something, you know. Uh, it doesn't have to be artificial intelligence, just creating life in general.

   2. PMPamela McCorduck14:46

      Mm-hmm.

   3. LFLex Fridman14:46

      It's the Frankenstein idea.

   4. PMPamela McCorduck14:49

      There's The Annotated Frankenstein on my coffee table. (laughs)

   5. LFLex Fridman14:53

      (laughs) There's a lot.

   6. PMPamela McCorduck14:53

      Uh, it's, it's tremendous novel. It really is just beautifully perceptive. Uh, yes, uh, we, we do fear this, and we have good reason to fear it, but... because it can get out of hand.

   7. LFLex Fridman15:07

      Maybe you can speak to that fear, the, the psychology, if you've thought about it. You know, there's a practical set of fears, concerns in the short term. You can think of... if we actually think about artificial intelligence systems, you could think about bias of discrimination in algorithms or you, you can, um, think about, uh, their social networks have algorithms that recommend the content you see. Thereby these algorithms control the behavior of the masses. There's these concerns. But it... to me, it feels like the fear that people have is deeper than that. So have you thought about the psychology of it?

   8. PMPamela McCorduck15:47

      I think in a, a superficial way, I have. There is this notion that if we produce a machine that can think, it will outthink us and therefore replace us.

   9. LFLex Fridman16:02

      I guess that's a, that's a primal fear of-

   10. PMPamela McCorduck16:04

       Yes, it is.

   11. LFLex Fridman16:04

       ... almost a... or almost kind of a, a kind of mortality. So around the time... you said you worked with, um, uh, at Stanford with, uh, Ed Feigenbaum.

   12. PMPamela McCorduck16:17

       Mm-hmm.

   13. LFLex Fridman16:18

       So let's look at that one person throughout his history, clearly a key person, one of the many i- in the history of AI. How has he changed, uh, in general ar- around him? How has Stanford changed in the last... how many years are we talking about here?

   14. PMPamela McCorduck16:36

       Oh, since-

   15. LFLex Fridman16:37

       Decade.

   16. PMPamela McCorduck16:37

       ... '65.

   17. LFLex Fridman16:38

       Si- '65. So I mean, it doesn't have to be about him, it could be, uh, bigger, but... because he was a key person in expert systems for example. How is that... how are these folks who you've interviewed in, uh, the '70s, '79 changed through the decades?

   18. PMPamela McCorduck17:03

       In Ed's case, I, uh, I know him well. We are dear friends. We see each other every month or so. He told me that when Machines Who Think first came out, he really thought all the front matter was kind of baloney.

   19. LFLex Fridman17:18

       Mm-hmm.

   20. PMPamela McCorduck17:19

       And 10 years later, he said, "No, I see what you're getting at."

   21. LFLex Fridman17:25

       (laughs)

   22. PMPamela McCorduck17:25

       "Yes, this is an impulse that has been... this has been a human impulse for thousands of years to create something outside the human cranium that has intelligence." Uh, I think it's very hard when you're down at the algorithmic level and you're just trying to make something work, (laughs) which is hard enough, to s- step back and think of the big picture. It reminds me of, um, when I was in Santa Fe, I knew a lot of archeologists, which was a hobby of mine, and I would say, "Yeah, yeah. Well, you can look at the shards and say, 'Oh, this came from this tribe and this came from this trade route and so on,' but what about the big picture?" And a very distinguished archeologist said to me-... they don't think that way. You, you... No, they're, they're trying to match the shard to the, to where it came from. That's, you know, where did this corn, uh, remainder of this corn come from? Was it grown here? Was it grown elsewhere? And I think this is part of the AI, uh, any scientific field. Uh, you're so busy doing the, the hard work, and it is hard work, that you don't step back and say, "Oh, well, now let's talk about the, you know, mm-hmm, the general-"

   23. LFLex Fridman18:52

       The big picture, yeah.

   24. PMPamela McCorduck18:52

       "... meaning of all this." Yes. (laughs)

   25. LFLex Fridman18:53

       Yeah, so none, none of the even Minsky and McCarthy, they, th- the-

   26. PMPamela McCorduck18:59

       Oh, those guys did. Yeah, the Founding Fathers did.

   27. LFLex Fridman19:02

       Early on or later?

   28. PMPamela McCorduck19:03

       Pretty early on. Oh, they had, but, uh, f- in a different way from how I looked at it. The two cognitive psychologists, Newell and Simon, they wanted to imagine reforming cognitive psychology so that we would really, really understand the brain.

   29. LFLex Fridman19:23

       Yeah.

   30. PMPamela McCorduck19:25

       Minsky was more speculative. And John McCarthy saw it as, I think I'm doing, doing him right by this, he really saw it as a great boon for human beings to have this technology, and that was reason enough to do it. Uh, and he had wonderful, wonderful fables about how, if you do the mathematics, you will see that these things are really good for human beings. And if you had a technological objection, he had an answer, a technological answer, but here's how we could get over that, and then blah, blah, blah, blah. And one of his favorite things was what he called the literary problem, which, of course, he presented to me several times. That is, everything in literature, there are conventions in literature. One of the conventions is that you have, uh, a villain and, uh, a hero. And the hero, in most literature, is human, and the villain, in most literature, is a machine. And he said, "No, that's just not the way it's gonna be," but that's the way we're used to it. So when we tell stories about AI, it's always with this paradigm. And I thought, "Yeah, he's right." You know, looking back, uh, in the classics, RUR is certainly the machines trying to o- overthrow the humans. Frankenstein is different. Frankenstein is a creature. He never, he never has a name. Frankenstein, of course, is the guy who created him, the human, Dr. Frankenstein. This creature wants to be loved, wants to be accepted, and it is only when Frankenstein turns his head, in fact, runs the other way, and the creature is without love that he becomes, um, the monster that he later becomes.
8. 23:35 – 28:46

   AI as an ‘outcast’ and the CMU social world: Knuth, Traub, and Herb Simon’s sherry salon

   1. LFLex Fridman23:35

      ... interesting to get a sense of stories of the way they were thinking and the way it was changed, the way your own thinking about AI has changed. So you mentioned McCarthy. Is, um... What, what about the years at CMU-

   2. PMPamela McCorduck23:51

      Oh.

   3. LFLex Fridman23:51

      ... Carnegie Mellon with Joe and with-

   4. PMPamela McCorduck23:53

      Oh, sure.

   5. LFLex Fridman23:54

      ... with-

   6. PMPamela McCorduck23:54

      Uh, Joe was, uh, not in AI. He was, uh, in algorithmic cl- complexity.

   7. LFLex Fridman24:03

      Was there a- always a line between AI and computer science? For example, is AI its own place of outcasts? Was that the feeling?

   8. PMPamela McCorduck24:11

      There was a kind of outcast (laughs) period for AI. For instance, in 1974, uh, the new field was hardly-... 10 years old. Uh, the new field of computer science was asked by the Na- National Fi- Science Foundation, I believe, but it may have been the National Academies, I can't remember, uh, to, you know, tell us, tell a, your fellow scientists where computer science is and what it means, and they wanted to leave out AI.

   9. LFLex Fridman24:47

      (laughs)

   10. PMPamela McCorduck24:48

       And they only agreed to put it in because Don Knuth said, "Hey, this is important. You can't just leave that out."

   11. LFLex Fridman24:57

       Really? Don did it?

   12. PMPamela McCorduck24:58

       Don Knuth, yes.

   13. LFLex Fridman24:59

       (laughs) I talked to him recently too, so out of all the people, uh...

   14. PMPamela McCorduck25:03

       Yes. But you see-

   15. LFLex Fridman25:04

       Yeah.

   16. PMPamela McCorduck25:05

       ... an AI person couldn't have made that argument. It wouldn't have been believed. But Knuth was believed, yes.

   17. LFLex Fridman25:11

       So, uh, Joe Trobe worked on-

   18. PMPamela McCorduck25:13

       Ah.

   19. LFLex Fridman25:13

       ... the real stuff.

   20. PMPamela McCorduck25:15

       Uh, Joe was working on algorithmic complexity, but he would say in plain English again and again, "The smartest people I know are in AI."

   21. LFLex Fridman25:24

       Really?

   22. PMPamela McCorduck25:25

       Oh, yes. No question. Anyway, Joe, loved these guys. What happened was that... I guess it was as I started to write Machines Who Think, Herb Simon and I became very close friends. He would walk past our house on Northumberland Street every day after work, and I would just be putting my cover on my typewriter, and I would lean out the door and say, "Herb, would you like a sherry?"

   23. LFLex Fridman25:54

       (laughs)

   24. PMPamela McCorduck25:54

       And Herb almost always would like a sherry.

   25. LFLex Fridman25:57

       (laughs)

   26. PMPamela McCorduck25:58

       So he'd stop in and we'd talk for an hour, two hours. My journal says we talked this afternoon for three hours. Mm.

   27. LFLex Fridman26:06

       What was on his mind at the time if I- in terms of on, on the AI side of things?

   28. PMPamela McCorduck26:11

       Oh, uh, we didn't talk too much about AI. We talked about other things.

   29. LFLex Fridman26:14

       Just life, yeah.

   30. PMPamela McCorduck26:15

       Uh, we, we both loved literature and Herb had read Proust in the original French twice all the way through.
9. 28:46 – 37:08

   Symbolic AI, deep learning, and why she rejects the ‘AI winter’ narrative

   1. LFLex Fridman28:46

      How have your own views around artificial intelligence changed in, through the process of writing Machines Who Think and afterwards, the ripple effects?

   2. PMPamela McCorduck28:58

      I was a little skeptical that this whole thing would work out. It didn't matter. To me, it was so audacious that-

   3. LFLex Fridman29:05

      This whole thing being AI gen-

   4. PMPamela McCorduck29:07

      AI generally, yeah.

   5. LFLex Fridman29:09

      Yeah.

   6. PMPamela McCorduck29:09

      And i- in some ways, uh, it hasn't worked out the way I expected so far. That is to say there's this wonderful lot of apps, thanks to deep learning and so on-

   7. LFLex Fridman29:26

      Yeah.

   8. PMPamela McCorduck29:27

      ... but those are algorithmic.

   9. LFLex Fridman29:28

      Yeah.

   10. PMPamela McCorduck29:29

       And in the part of, uh, symbolic processing, there is very little yet.

   11. LFLex Fridman29:38

       Yes.

   12. PMPamela McCorduck29:39

       And that's a field that lies waiting for industria- uh, industrious graduate students.

   13. LFLex Fridman29:45

       (laughs) Maybe you can tell me some figures that popped up in your life in the '80s with expert systems where there was this symbolic AI possibilities of what's... You know, that, what most people think of as AI, if you dream of the possibilities of AI, is really expert systems.

   14. PMPamela McCorduck30:04

       Mm-hmm.

   15. LFLex Fridman30:05

       And those hit a few walls and, uh, there was challenges there. And I think, yes, they will reemerge again with some new breakthroughs and so on. But what did that feel like, both the possibility and the winter that followed, the slowdown in research?

   16. PMPamela McCorduck30:21

       Ah, you know, this whole thing about AI winter is, to me, a crock.

   17. LFLex Fridman30:26

       Snowy winters.

   18. PMPamela McCorduck30:27

       (laughs) ... because I look at the basic research that was being done in the '80s, which is supposed to be... My God, it was really important. It was laying down things that nobody had thought about before. But it was basic research. You couldn't monetize it.

   19. LFLex Fridman30:43

       Right.

   20. PMPamela McCorduck30:44

       Hence, the winter.

   21. LFLex Fridman30:45

       Hence, the winter.

   22. PMPamela McCorduck30:47

       Uh, you know, research, scientific research goes in fits and starts. It isn't this nice, smooth, "Oh, this follows this, follows this." No. Uh, you know, it just doesn't work that way.

   23. LFLex Fridman30:59

       The, the interesting thing, the way winters happen, it's never the fault of the researchers. It's the, it's the h- the some source of hype, over-promising. Well, no, let me take that back. Sometimes it is the fault of the researchers. (laughs) Sometimes, certain researchers might over-promise the possibilities they themselves believe-

   24. PMPamela McCorduck31:19

       Mm-hmm.

   25. LFLex Fridman31:20

       ... that we're just a few years away, that have... Just recently talked to Elon Musk, and he believes he'll have an autonomous vehic- we'll have autonomous vehicles in a year. I, and he believes it.

   26. PMPamela McCorduck31:30

       A year?

   27. LFLex Fridman31:31

       A year, yeah. We'll have mass deployment of autonomous-

   28. PMPamela McCorduck31:33

       Uh, for the record, this is 2019 right now.

   29. LFLex Fridman31:37

       Yeah.

   30. PMPamela McCorduck31:37

       So he's talking 2020.
10. 37:08 – 43:32

    Santa Fe Institute and complexity: finding new language for creative AI (Harold Cohen’s AARON)

    1. LFLex Fridman37:08

       So, you mentioned Santa Fe Institute. Uh, y- so you've written the novel Edge of Chaos, but it's inspired by the ideas of complexity-

    2. PMPamela McCorduck37:18

       Mm-hmm.

    3. LFLex Fridman37:18

       ... uh, where a lot of which have been extensively explored at the Santa Fe Institute.

    4. PMPamela McCorduck37:24

       Right.

    5. LFLex Fridman37:24

       It's a... I mean, it's, it's another fascinating topic of just sort of emergent complexity from chaos. Nobody knows how it happens really, but it seems to be where all the interesting stuff does happen.

    6. PMPamela McCorduck37:40

       Yeah. (laughs) Right.

    7. LFLex Fridman37:40

       So, how do, first, not your novel, but just complexity in general and the work at Santa Fe fit into the bigger puzzle of the history of AI?

    8. PMPamela McCorduck37:50

       (sighs)

    9. LFLex Fridman37:50

       Or, and maybe even your personal journey through that?

    10. PMPamela McCorduck37:54

        One of the last projects I did concerning AI in particular was looking at the work of Harold Cohen, the painter. And Harold was deeply involved with AI. He was a painter first. And, and what his project, Aaron, which was a lifelong project, did was reflect his own cognitive processes. Okay. H- Harold and I, even though I wrote a book about him, we had a lot of friction between us. And I went... I thought, "This is it. You know, the book died." It was published and fell into a ditch. "Uh, this is it. I'm finished. It's time for me to do something different." By chance, this was a sabbatical year for my husband, and we spent two months at the Santa Fe Institute and two months at Caltech, and then the spring semester in Munich, Germany. Okay. Those two months at the Santa Fe Institute were so restorative for me. And I began to... Uh, it, the s- the institute was very small then. Uh, it was in some kind of office complex on Old Santa Fe Trail. Everybody kept their door open. So, you could crack your head on a problem. And if you finally didn't get it, you could walk in to see Stuart Kauffman or, um, well, any number of people and say, "I don't get this. Can you explain?" And one of the people that I was talking to about complex adaptive systems was Murray Gell-Mann. And I told Murray what H- Harold Cohen had done. And I said, "You know, this sounds to me like a complex adaptive system." And he said, "Yeah, it is." Well, what do you know? Harold's Aaron had all these kissing cousins all over the world-

    11. LFLex Fridman40:10

        (laughs)

    12. PMPamela McCorduck40:10

        ... in science and in economics and so on and so forth. I was so relieved. I thought, "Okay, your instincts are okay." (laughs)

    13. LFLex Fridman40:18

        (laughs)

    14. PMPamela McCorduck40:18

        "You're, you're doing the right thing." Um, I didn't have the vocabulary, and that was one of the things that the Santa Fe Institute gave me. If I could have rewritten that book... No, it had just come out, I couldn't rewrite it, I would have had a vocabulary to explain what Aaron was doing. Okay. So I got really interested in, uh, what was going on at the institute. And the people were, again, bright and funny and willing to explain anything to this amateur. George Cowan, who was then the head of the institute, said he thought it might be a nice idea if I wrote a book about the institute. And I thought about it. And I, I had my eye on some other project, God knows what. And I said, "Uh, I'm sorry, George. Yeah, I'd, I'd really love to do it, but, you know, just not gonna work for me at this moment." And he said, "Oh, well, too bad. I think it would make an interesting book." (laughs) Well, he was right and I was wrong. I wish I'd done it. But that's interesting. I hadn't thought about that, that that was a, a road not taken that I wish I'd taken.

    15. LFLex Fridman41:25

        Well, you know what? That's... Just on that, on that point, it's quite brave for you as an, as a writer, as, um, as sort of coming from a world of literature and the literary thinking and historical thinking, I mean, just from that world and bravely talking to quite, I assume, large egos in, uh-

    16. PMPamela McCorduck41:48

        (laughs) Yeah.

    17. LFLex Fridman41:49

        ... in, (laughs) in, uh, AI or in complexity and so on. How, how did you do it? (laughs) Uh, like, where did you... I mean, I suppose they could be intimidated of you as well because it's two different worlds coming together.

    18. PMPamela McCorduck42:02

        I don't think... I, I never picked up that anybody was intimidated by me.

    19. LFLex Fridman42:06

        But how were you brave enough? Where did you find the guts to sort of-

    20. PMPamela McCorduck42:08

        God, just dumb, dumb luck. I mean, I, I... This is an interesting rock to turn over, "I'm gonna write a book about it." And, you know, people have enough patience with writers if they think they're gonna end up in a book that they let you flail around and so on.

    21. LFLex Fridman42:24

        It's... Well, but they also look if the writer has... There's like, if there's a sparkle in their eye, if they get it.

    22. PMPamela McCorduck42:31

        Yeah, sure.

    23. LFLex Fridman42:31

        Right? When were you at the Santa Fe Institute?

    24. PMPamela McCorduck42:35

        Uh, the time I'm talking about is 1994.... yeah, 1990, 1991, '92. But we then, because Joe was an external faculty member, were in Santa Fe every summer. We bought a house there, and I didn't have that much to do with the institute anymore. I was writing my novels, I was doing whatever I was doing. But I loved the institute, and I loved the, again, the audacity of the ideas. That really s- appeals to me.

    25. LFLex Fridman43:14

        I think that the, there's this feeling, much like in great e- and great institutes of neuroscience for example, that, um, it's, they're, they're in it for the long game of understanding something-

    26. PMPamela McCorduck43:29

        Yeah.

    27. LFLex Fridman43:29

        ... fundamental about reality-

    28. PMPamela McCorduck43:30

        Yeah.

    29. LFLex Fridman43:30

        ... and nature.

    30. PMPamela McCorduck43:30

        Yeah. Yeah.

11. 43:32 – 54:08

    Modern AI excitement, the singularity debate, care robots, and the ‘male gaze’ of existential risk

    1. LFLex Fridman43:32

       And that's really exciting. So, um, if we start n- now to look a little bit more recently, how, you know, AI is really popular today. How is this world, you mentioned algorithmic, but in general, is the spirit of the people, the kind of conversations you hear through the grapevine-

    2. PMPamela McCorduck43:54

       Mm-hmm.

    3. LFLex Fridman43:54

       ... and so on, is that different than the roots that you remember?

    4. PMPamela McCorduck43:57

       No. The same kind of excitement. The same kind of, "This is really gonna make a difference in the world." And it will. It has.

    5. LFLex Fridman44:07

       You know, a lot of the folks, especially young, you know, 20 years old or something, they, they think, "We've just found something special here."

    6. PMPamela McCorduck44:14

       (laughs)

    7. LFLex Fridman44:14

       "We're going to change the world tomorrow." O- on a time scale, do you have a sense of what, of the time scale at which breakthroughs in AI happen?

    8. PMPamela McCorduck44:28

       I really don't. Because l- look at deep learning. That was a, Geoffrey Hinton came up with the algorithm in '86.

    9. LFLex Fridman44:41

       Mm-hmm.

    10. NANarrator44:42

        Yeah, probably-

    11. PMPamela McCorduck44:43

        But it took all these years for the technology to be good enough, uh, to actually be, be applicable. So, no, I can't predict that at all. I can't. I wouldn't even try. (laughs)

    12. LFLex Fridman44:58

        Well, let me ask you to, not to try to predict, but to speak to the, you know, I'm sure in the '60s, as it continues now, there's people that think, let's call it, we can call it this fun word, the singularity.

    13. PMPamela McCorduck45:12

        Mm.

    14. LFLex Fridman45:13

        When there's a phase shift, there's some profound feeling where we're all really surprised by what's able to be achieved. I'm sure those dreams are there. I remember reading quotes in the '60s and those continued.

    15. PMPamela McCorduck45:27

        Sure.

    16. LFLex Fridman45:27

        How have your own views, maybe, if you look back, about the timeline of a singularity changed?

    17. PMPamela McCorduck45:37

        Well, um, I'm not a big fan of the singularity as Ray Kurzweil has presented it.

    18. LFLex Fridman45:46

        How would you define the Ray Kurzweil, sort of how would you-

    19. PMPamela McCorduck45:50

        Well, uh-

    20. LFLex Fridman45:50

        ... how do you think of singularity in those, in...

    21. PMPamela McCorduck45:53

        If I understand Kurzweil's view, it's sort of, there's gonna be this moment when machines are smarter than humans, and, you know, game, game over. However, the game over is. I mean, do they put us on a reservation? Do they... et cetera, et cetera. And first of all, machines are smarter than humans in some ways all over the place.

    22. LFLex Fridman46:19

        Yeah.

    23. PMPamela McCorduck46:19

        And they have been since adding machines were invented. So it's not, it's not gonna come, like, some great Oedipal crossroads, you know, where they meet each other and our offspring, Oedipus, says, "You're dead." (laughs)

    24. LFLex Fridman46:36

        Yeah.

    25. PMPamela McCorduck46:36

        It's just not gonna happen.

    26. LFLex Fridman46:38

        Yeah, so it's already game over with calculators, right? Uh, (laughs) they're already out, uh, do much better at, uh, basic arithmetic than us. But, you know, there's, um, human-like intelligence.

    27. PMPamela McCorduck46:51

        Mm.

    28. LFLex Fridman46:52

        And t- that's not the ones that destroy us, but, you know, somebody that you can have as a f- as a friend-

    29. PMPamela McCorduck46:58

        Oh. (laughs)

    30. LFLex Fridman46:59

        ... who you can have deep connections with, that kind of passing the Turing test and beyond.
12. 54:08 – 1:00:13

    Women in tech, MeToo as a ‘sandpile’ tipping point, and her personal motive for wanting AI to succeed

    1. LFLex Fridman54:08

       ... calm way of, of, uh, how the tech could evolve. I mean, s- speaking of which, your '96 book, The Future of Women-

    2. PMPamela McCorduck54:17

       Oh.

    3. LFLex Fridman54:18

       ... I think at the time, and now, certainly now, I mean, I'm sorry, maybe at the time, but I'm more cognizant of now, is, uh, extremely relevant. You and Nancy Ramsey talk about four possible futures-

    4. PMPamela McCorduck54:32

       Right.

    5. LFLex Fridman54:32

       ... of women in science and tech. So if we look at the decades before and after the book was released, can you tell a history, sorry, of women in science and tech-

    6. PMPamela McCorduck54:46

       Oh, boy.

    7. LFLex Fridman54:46

       ... and how it has evolved?How have things changed? Where do we stand?

    8. PMPamela McCorduck54:51

       Not enough. (laughs) They have not changed enough. Uh, the way that women are ground down (laughs) in computing is simply unbelievable.

    9. LFLex Fridman55:04

       But what are the four possible futures for women-

    10. PMPamela McCorduck55:08

        Oh.

    11. LFLex Fridman55:08

        ... in tech from the book?

    12. PMPamela McCorduck55:10

        What you're really looking at are various aspects of the present. So for each of those, you could say, "Oh, yeah. We do have backlash. Look at what's happening with abortion and so on and so forth."

    13. LFLex Fridman55:24

        Mm-hmm.

    14. PMPamela McCorduck55:24

        Uh, we have one step forward, one step back. The golden age of equality was the hardest chapter to write. And I used something from the Santa Fe Institute, which is the sandpile effect, that you drop sand very slowly onto a pile, and it grows and it grows and it grows until suddenly, it just breaks apart. And in a way, MeToo has done that. That was the last drop of sand that broke everything apart. That was a perfect example of the sandpile effect. And that made me feel good. It didn't change all of society, but it really woke a lot of people up.

    15. LFLex Fridman56:08

        But are you in general optimistic about maybe after MeToo? I mean, MeToo is about a very specific kind of thing.

    16. PMPamela McCorduck56:17

        Boy, solve that and you solve everything. (laughs)

    17. LFLex Fridman56:20

        (laughs) But are you in general optimistic about the future? Uh-

    18. PMPamela McCorduck56:23

        Yes. I'm, I'm a congenital optimist.

    19. LFLex Fridman56:26

        (laughs)

    20. PMPamela McCorduck56:27

        (laughs) I can't help it.

    21. LFLex Fridman56:28

        What about AI? What are your thoughts about-

    22. PMPamela McCorduck56:32

        When, when, when-

    23. LFLex Fridman56:33

        ... the future of AI?

    24. PMPamela McCorduck56:34

        I... Of course, I get asked, "What do you worry about?" And the one thing I worry about is the things we can't anticipate.

    25. LFLex Fridman56:42

        Huh.

    26. PMPamela McCorduck56:44

        You know, there, there's gonna be something out of left field that we'll, we will just say, "We weren't prepared for that." Uh, I am generally optimistic. When I first took up being interested in AI, like most people in the field, more intelligence was like more virtue. You know, what could be bad?

    27. LFLex Fridman57:07

        Right.

    28. PMPamela McCorduck57:08

        And in a way, I still believe that, but I realize that my notion of intelligence has broadened. There are many kinds of intelligence. And we need to imbue our machines with those many kinds.

    29. LFLex Fridman57:24

        So you've now just finished or are in the process of finishing your, the book-

    30. PMPamela McCorduck57:32

        Mm-hmm.

Episode duration: 1:00:06