The following is a conversation with Pamela McCordick.

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 Vangenbaum, who's considered to be the father of expert systems, The Edge of Chaos, that features women, and many more books.

I came across her work in an unusual way by stumbling in 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

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 5 stars on iTunes, support it on Patreon, or simply connect with me on Twitter, at Lex Friedman, spelled F-R-I-D-M-A-N.

And now, here's my conversation with Pamela

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.

So tell me if you could, the story of how you first arrived at the book, the journey of beginning to write it?

And I was sitting under the portal at Stanford 1 day, the house we were renting for the summer and I thought, I should write a novel about these weird people in AI I know.

Then I thought, don't write a novel, write a history, simple.

Just go around, interview them, splice it together, Voila, instant book.

And so I thought, well, this is a great opportunity.

And there were people who, 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.

This is what I want to do, I hope you'll cooperate.

And he said, oh, mutter, mutter, well, okay, it's your time.

And- 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?

The founders of the field are alive and kicking and able to talk about what they're doing.

Did they sound or feel like founders at the time?

Did they know that they have founded something?

Oh yeah, they knew what they were doing was very important.

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 gonna write a book about you.

Maybe looking 63 years ago, the Dartmouth conference.

So Marvin Minsky was there, McCarthy was there, Claude Shannon, Alan Newell, Herb Simon, some of the folks you've mentioned.

He was not at Dartmouth, but I mean, in general.

I mean, all of these are players, not at Dartmouth, but in that era.

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...

Of course, the 4 founding fathers were extraordinary guys, They really were.

Alan Newell, Herbert Simon, Marvin Minsky, John McCarthy.

They were the 4 who were not only at the Dartmouth conference, but Newell and Simon arrived there with a working program called the logic theorist.

Everybody else had great ideas about how they might do it, but they weren't going to do it yet.

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 edited by Feigenbaum and Julian Feldman called Computers and Thought.

It was the first textbook of readings of AI.

And they only did it because they were trying to teach AI to people at Berkeley and there was nothing, you'd have to send them to this journal and that journal.

This was not the internet where you could go look at an article.

So, I was fascinated from the get-go by AI.

And that's why you saw that historical, that literary background, which I think is very much a part of the continuum of AI.

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 going to succeed.

In fact, the final chapter is very wishy-washy, frankly.

Yeah, so was there the idea that AI began with the wish to forge the gods?

So the spiritual component that we crave to create this other thing greater than ourselves?

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.

McCarthy had got the idea in 1949 when he was a Caltech student.

And he listened to somebody's lecture, it's in my book, I forget who it was, and he thought, oh, that would be fun to do.

And he took a very mathematical approach.

Minsky was hybrid, and Newell and Simon were very much cognitive psychology.

How can we simulate various things about human cognition?

What happened over the many years is, of course, our definition of intelligence expanded tremendously.

These days, biologists are comfortable talking about the intelligence of a cell, the intelligence of the brain, not just human brain, but the intelligence of any kind of brain.

Cephalopods, I mean, an octopus is really intelligent by any amount.

We wouldn't have thought of that in the 60s, even the 70s.

And I did hear 1 behavioral primatologist, Franz De Waal, say, AI taught us the questions to ask.

It's when you try to build it, is when you start to actually ask questions of, it puts a mirror to ourselves.

It seems like not many people were asking the questions that you were, or just trying to look at this field the way you were.

When I went to get funding for this, because I needed somebody to transcribe the interviews and I needed travel expenses, I went to everything you could think of, the NSF, the DARPA.

There was an Air Force place that doled out money.

And each of them said, well, that was very interesting.

And the National Science Foundation actually said to me in plain English, hey, you're only a writer.

But you know, the historians of science will be crawling all over this field.

I'm writing for the general audience, so I thought.

I finally got a private grant without knowing who it was from, from Ed Fredkin at MIT.

He was a wealthy man and he liked what he called crackpot ideas and he considered this a crackpot idea.

This a crackpot idea and he was willing to support it.

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.

Maybe I'm not familiar, but it's certainly not many.

If we think about bigger than just these couple of decades, few decades, what are the roots of AI?

Yes, Of course, there's all the legendary stuff, the Golem and the early robots of the 20th century.

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.

Yeah, how do you think Odysseus' ship gets from 1 place to another?

He doesn't have the crew people to do that, the crewmen.

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 intelligent behavior.

And when he ran out of funding, the British government finally said, that's enough.

He and Lady Lovelace decided, oh, well why don't we play the ponies with this?

He had other ideas for raising money too.

But if we actually reach back once again, I think people don't actually really know that robots do appear, or ideas of robots.

You talk about the Hellenic and the Hebraic points of view.

I defined it this way, the Hellenic point of view is robots are great.

They help this guy Hephaestus, this god Hephaestus in his forge.

I presume he made them to help him, and so on and so forth.

And they welcome the whole idea of robots.

The Hebraic view has to do with, I think it's the second commandment, thou shalt not make any graven image.

In other words, you better not start imitating humans because that's just forbidden.

And a lot of the reaction to artificial intelligence has been a sense that this is, this is somehow wicked, this is somehow blasphemous.

Now, you can say, yeah, but there are gonna be some downsides.

And I say, yes, there are, but blasphemy is not 1 of them.

You know, there is a kind of fear that feels to be almost primal.

Because so much of our society has religious roots, and so there is a feeling of, like you said, blasphemy, of creating the other, of creating something, you know, it doesn't have to be artificial intelligence, it's creating life in general.

There's the annotated Frankenstein on my coffee table.

It really is just beautifully perceptive.

Yes, We do fear this and we have good reason to fear it, but because it can get out of hand.

Maybe you can speak to that fear, 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 can think about bias, of discrimination in algorithms, you can think about 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 to me it feels like the fear that people have is deeper than that.

So have you thought about the psychology of it?

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

I guess that's a primal fear of almost kind of a kind of mortality.

So around the time you said you worked with, at Stanford with Ed Feigenbaum.

Throughout his history, clearly a key person, 1 of the many in the history of AI.

How has he changed in general around him?

How has Stanford changed in the last, how many years are we talking about here?

So maybe it doesn't have to be about him, it could be 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 the 70s, 79, changed through the decades?

In Ed's case, 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.

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

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.

I think it's very hard when you're down at the algorithmic level and you're just trying to make something work, which is hard enough, just step back and think of the big picture.

It reminds me of when I was in Santa Fe, I knew a lot of archaeologists, 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.

No, they're trying to match the shard to where it came from.

That's, you know, where did this corn, the remainder of this corn come from?

And I think this is part of the AI, any scientific field.

You're so busy doing the hard work, and it is hard work, that you don't step back and say, oh, well, now let's talk about

So none of the, even Minsky and McCarthy, they.

But in a different way from how I looked at it.

The 2 cognitive psychologists, Newell and Simon, they wanted to imagine reforming cognitive psychology so that we would really, really understand the brain.

And John McCarthy saw it as, I think I'm 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.

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 1 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.

1 of the conventions is that you have a villain and 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 going to be.

So when we tell stories about AI, it's always with this paradigm.

You know, looking back, the classics, RUR is certainly the machines trying to overthrow the humans.

Frankenstein, of course, is the guy who created him, the human, Dr.

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 the monster that he later becomes.

It's really the people who drive him, by driving him away, they bring out the worst.

He becomes at 1 point the friend of a blind man.

He serves this blind man and they become very friendly.

But when the sighted people of the blind man's family come in, ah, you've got a monster here.

So it's very didactic in its way, and what I didn't know is that Mary Shelley and Percy Shelley were great readers of the literature surrounding abolition in the United States, the abolition of slavery.

You are making monsters of these people because you won't give them the respect and love that they deserve.

Do you have, if we get philosophical for a second, do you worry that once we create machines that are a little bit more intelligent, let's look at Roomba that vacuums

cleaner, That this darker part of human nature where we abuse the other, the somebody who's different, will come out?

But I think that what AI has to offer the human race will be so attractive that people will be won over.

So you have looked deep into these people, had deep conversations, and it's 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.

What about the years at CMU, Carnegie Mellon with Joe and with?

not in AI, he was in algorithmic complexity.

Was there always a line between AI and computer science, for example?

There was a kind of outcast period for AI.

For instance, in 1974, the new field was hardly 10 years old.

The new field of computer science was asked by the National Science Foundation, I believe, but it may have been the National Academies, I can't remember, to tell us, tell your fellow scientists where computer science is and what it means.

And they only agreed to put it in because Don Knuth said, hey, this is important.

I talked to him recently too, so out of all the people.

Yes, but you see, an AI person couldn't have made that argument.

He wouldn't have been believed, but Knuth was believed,

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

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?

And Herb almost always would like a sherry.

So he'd stop in, and we'd talk for an hour, 2 hours.

My journal says we talked this afternoon for 3 hours.

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

We both love literature, and Herb had read Proust in the original French twice all the way through.

So we talked about literature, we talked about languages, we talked about music, because he loved music.

We talked about art, because he was actually enough of a painter that he had to give it up because he was afraid it was interfering with his research.

So no, it was really just chat, chat, but it was very warm.

So, 1 summer, I said to Herb, you know, my students have all the really interesting conversations.

I was teaching at the University of Pittsburgh then in the English department.

You know, they get to talk about the meaning of life and that kind of thing.

I have university meetings where we talk about the photocopying budget and, you know, whether the course on romantic poetry should be 1 semester or 2.

He said, but you could do something about that.

Dot, that was his wife, Dot and I used to have a salon at the University of Chicago every Sunday night.

And we would have essentially an open house and people knew it wasn't for small talk.

He said, but my advice would be that you choose the topic ahead of time.

So, the following, we exchanged mail over the summer.

That was US post in those days because you didn't have personal email.

And I decided I would organize it and there would be 8 of us.

Alan Newell and his wife, Herb Simon and his wife, Dorothea.

There was a novelist in town, a man named Mark Harris, he had just arrived, and his wife, Josephine.

Mark was most famous then for a novel called Bang the Drum Slowly, which was about baseball.

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