Pamela McCorduck: Machines Who Think and the Early Days of AI
音乐与艺术心理与人性AI 与机器学习技术与编程生物与进化
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"of the time scale at which breakthroughs in AI happen? I really don't. Because look at Deep Learning."
人工智能取得突破的时间尺度是多少？我真的不知道。因为看看深度学习。
— Pamela McCorduck （44:24.240）
"this is somehow blasphemous. We shouldn't be going there. Now, you can say, yeah, but there are going"
这在某种程度上是亵渎的。我们不应该去那里。现在，你可以说，是的，但是有
— Pamela McCorduck （14:08.800）
"person in expert systems, for example, how is that, how are these folks who you've interviewed in the"
例如，专家系统中的人，那怎么样，你在专家系统中采访过的这些人怎么样？
— Pamela McCorduck （16:45.000）
"answer. But here's how we could get over that and then blah, blah, blah. And one of his favorite things"
回答。但这就是我们如何克服这个问题，然后等等等等。还有他最喜欢的事情之一
— Pamela McCorduck （20:03.440）
"Fe Institute. I thought, algorithms, yeah, they're in the service of, but they're not the main event."
铁研究所。我想，算法，是的，它们是服务的，但它们不是主要事件。
— Pamela McCorduck （36:33.200）
🎙️ 完整对话（515 条）
Lex Fridman (00:00.000)
The following is a conversation with Pamela McCordick. She's an author who has written on
以下是与帕梅拉·麦考迪克的对话。她是一位作家，曾写过
Lex Fridman (00:04.800)
the history and the philosophical significance of artificial intelligence. Her books include
人工智能的历史和哲学意义。她的书包括
Lex Fridman (00:10.400)
Machines Who Think in 1979, The Fifth Generation in 1983 with Ed Feigenbaum, who's considered to
1979 年的《会思考的机器》，1983 年与 Ed Feigenbaum 合作的第五代机器，他被认为是
Lex Fridman (00:18.160)
be the father of expert systems, The Edge of Chaos that features women, and many more books.
成为专家系统之父、以女性为主角的《混沌边缘》以及更多书籍。
Lex Fridman (00:24.000)
I came across her work in an unusual way by stumbling in a quote from Machines Who Think
我以一种不寻常的方式看到了她的作品，偶然引用了《思考的机器》中的一段话
Pamela McCorduck (00:29.520)
that is something like, artificial intelligence began with the ancient wish to forge the gods.
就好像，人工智能始于古老的锻造神的愿望。
Pamela McCorduck (00:37.040)
That was a beautiful way to draw a connecting line between our societal relationship with AI
这是在我们与人工智能的社会关系之间建立联系的一种美妙方式
Pamela McCorduck (00:42.960)
from the grounded day to day science, math and engineering, to popular stories and science
从扎根的日常科学、数学和工程，到流行的故事和科学
Pamela McCorduck (00:48.560)
fiction and myths of automatons that go back for centuries. Through her literary work,
几个世纪以来关于机器人的小说和神话。通过她的文学作品，
Pamela McCorduck (00:54.800)
she has spent a lot of time with the seminal figures of artificial intelligence, including
她花了很多时间研究人工智能的开创性人物，包括
Pamela McCorduck (01:00.480)
the founding fathers of AI from the 1956 Dartmouth summer workshop where the field was launched.
人工智能的奠基人来自 1956 年达特茅斯夏季研讨会，该领域正是在该研讨会上启动的。
Pamela McCorduck (01:08.480)
I reached out to Pamela for a conversation in hopes of getting a sense of what those early
我联系帕梅拉进行了一次谈话，希望了解早期的情况
Pamela McCorduck (01:13.760)
days were like, and how their dreams continue to reverberate through the work of our community
日子是怎样的，以及他们的梦想如何继续在我们社区的工作中产生反响
Pamela McCorduck (01:19.200)
today. I often don't know where the conversation may take us, but I jump in and see. Having no
今天。我常常不知道谈话会把我们带向何方，但我会跳进去看看。没有
Pamela McCorduck (01:25.600)
constraints, rules, or goals is a wonderful way to discover new ideas. This is the Artificial
约束、规则或目标是发现新想法的好方法。这就是人工
Pamela McCorduck (01:31.760)
Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes,
情报播客。如果您喜欢它，请在 YouTube 上订阅，在 iTunes 上给它五颗星，
Pamela McCorduck (01:37.840)
support it on Patreon, or simply connect with me on Twitter, at Lex Friedman, spelled F R I D M
在 Patreon 上支持它，或者直接在 Twitter 上与我联系，地址为 Lex Friedman（拼写为 F R I D M）
Pamela McCorduck (01:44.720)
A N. And now, here's my conversation with Pamela McCordick. In 1979, your book Machines Who Think
A N. 现在，这是我与帕梅拉·麦考迪克的对话。 1979 年，您的著作《思考的机器》
Pamela McCorduck (01:55.040)
was published. In it, you interview some of the early AI pioneers and explore the idea that
已发布。在其中，您采访了一些早期的人工智能先驱，并探讨了这样的想法：
Pamela McCorduck (02:00.720)
AI was born not out of maybe math and computer science, but out of myth and legend. So, tell me
人工智能的诞生可能不是数学和计算机科学，而是神话和传说。所以告诉我
Pamela McCorduck (02:10.400)
if you could the story of how you first arrived at the book, the journey of beginning to write it.
Pamela McCorduck (02:19.040)
I had been a novelist. I'd published two novels, and I was sitting under the portal at Stanford
Pamela McCorduck (02:29.120)
one day, the house we were renting for the summer. And I thought, I should write a novel about these
Pamela McCorduck (02:33.920)
weird people in AI, I know. And then I thought, ah, don't write a novel, write a history. Simple.
Pamela McCorduck (02:41.360)
Just go around, interview them, splice it together, voila, instant book. Ha, ha, ha. It was
Pamela McCorduck (02:48.240)
much harder than that. But nobody else was doing it. And so, I thought, well, this is a great
Pamela McCorduck (02:54.400)
opportunity. And there were people who, John McCarthy, for example, thought it was a nutty
Pamela McCorduck (03:03.760)
idea. The field had not evolved yet, so on. And he had some mathematical thing he thought I should
Pamela McCorduck (03:11.040)
write instead. And I said, no, John, I am not a woman in search of a project. This is what I want
Pamela McCorduck (03:17.840)
to do. I hope you'll cooperate. And he said, oh, mutter, mutter, well, okay, it's your time.
Lex Fridman (03:24.560)
What was the pitch for the, I mean, such a young field at that point. How do you write
Pamela McCorduck (03:30.800)
a personal history of a field that's so young? I said, this is wonderful. The founders of the
Pamela McCorduck (03:37.040)
field are alive and kicking and able to talk about what they're doing. Did they sound or feel like
Lex Fridman (03:42.720)
founders at the time? Did they know that they have founded something?
Pamela McCorduck (03:48.000)
Oh, yeah. They knew what they were doing was very important. Very. What I now see in retrospect
Pamela McCorduck (03:56.160)
is that they were at the height of their research careers. And it's humbling to me that they took
Pamela McCorduck (04:04.320)
time out from all the things that they had to do as a consequence of being there. And to talk to
Pamela McCorduck (04:11.440)
this woman who said, I think I'm going to write a book about you. No, it was amazing. Just amazing.
Lex Fridman (04:17.040)
So who stands out to you? Maybe looking 63 years ago, the Dartmouth conference,
Lex Fridman (04:26.480)
so Marvin Minsky was there, McCarthy was there, Claude Shannon, Alan Newell, Herb Simon,
Pamela McCorduck (04:32.960)
some of the folks you've mentioned. Then there's other characters, right? One of your coauthors
Pamela McCorduck (04:40.080)
He wasn't at Dartmouth.
Lex Fridman (04:43.120)
He wasn't at Dartmouth.
Pamela McCorduck (04:43.920)
No. He was, I think, an undergraduate then.
Lex Fridman (04:47.680)
And of course, Joe Traub. All of these are players, not at Dartmouth, but in that era.
Pamela McCorduck (04:56.000)
Right.
Pamela McCorduck (04:57.600)
CMU and so on. So who are the characters, if you could paint a picture, that stand out to you
Pamela McCorduck (05:02.960)
from memory? Those people you've interviewed and maybe not, people that were just in the
Lex Fridman (05:08.400)
In the atmosphere.
Pamela McCorduck (05:09.920)
In the atmosphere.
Lex Fridman (05:11.840)
Of course, the four founding fathers were extraordinary guys. They really were.
Lex Fridman (05:15.920)
Who are the founding fathers?
Pamela McCorduck (05:18.560)
Alan Newell, Herbert Simon, Marvin Minsky, John McCarthy. They were the four who were not only
Pamela McCorduck (05:24.800)
at the Dartmouth conference, but Newell and Simon arrived there with a working program
Pamela McCorduck (05:29.600)
called The Logic Theorist. Everybody else had great ideas about how they might do it, but
Lex Fridman (05:34.960)
But they weren't going to do it yet.
Lex Fridman (05:41.040)
And you mentioned Joe Traub, my husband. I was immersed in AI before I met Joe
Pamela McCorduck (05:50.080)
because I had been Ed Feigenbaum's assistant at Stanford. And before that,
Pamela McCorduck (05:55.040)
I had worked on a book edited by Feigenbaum and Julian Feldman called Computers and Thought.
Pamela McCorduck (06:04.320)
It was the first textbook of readings of AI. And they only did it because they were trying to teach
Pamela McCorduck (06:10.480)
AI to people at Berkeley. And there was nothing, you'd have to send them to this journal and that
Pamela McCorduck (06:15.040)
journal. This was not the internet where you could go look at an article. So I was fascinated from
Pamela McCorduck (06:22.240)
the get go by AI. I was an English major. What did I know? And yet I was fascinated. And that's
Lex Fridman (06:30.960)
why you saw that historical, that literary background, which I think is very much a part
Pamela McCorduck (06:38.080)
of the continuum of AI, that AI grew out of that same impulse. That traditional, what was,
Lex Fridman (06:47.600)
what drew you to AI? How did you even think of it back then? What was the possibilities,
Pamela McCorduck (06:54.880)
the dreams? What was interesting to you? The idea of intelligence outside the human cranium,
Pamela McCorduck (07:03.200)
this was a phenomenal idea. And even when I finished Machines Who Think,
Pamela McCorduck (07:08.960)
I didn't know if they were going to succeed. In fact, the final chapter is very wishy washy,
Pamela McCorduck (07:15.120)
frankly. Succeed, the field did. Yeah. So was there the idea that AI began with the wish to
Pamela McCorduck (07:25.760)
forge the gods? So the spiritual component that we crave to create this other thing greater than
Pamela McCorduck (07:33.760)
ourselves. For those guys, I don't think so. Newell and Simon were cognitive psychologists.
Lex Fridman (07:42.320)
What they wanted was to simulate aspects of human intelligence,
Lex Fridman (07:49.040)
and they found they could do it on the computer. Minsky just thought it was a really cool thing
Pamela McCorduck (07:57.280)
to do. Likewise, McCarthy. McCarthy had got the idea in 1949 when he was a Caltech student.
Lex Fridman (08:06.160)
And he listened to somebody's lecture. It's in my book. I forget who it was. And he thought,
Pamela McCorduck (08:15.520)
oh, that would be fun to do. How do we do that? And he took a very mathematical approach.
Pamela McCorduck (08:21.520)
Minsky was hybrid, and Newell and Simon were very much cognitive psychology. How can we simulate
Pamela McCorduck (08:29.440)
various things about human cognition? What happened over the many years is, of course,
Pamela McCorduck (08:37.120)
our definition of intelligence expanded tremendously. These days, biologists are
Pamela McCorduck (08:44.800)
comfortable talking about the intelligence of the cell, the intelligence of the brain,
Pamela McCorduck (08:49.240)
not just human brain, but the intelligence of any kind of brain. Cephalopods, I mean, an octopus is
Pamela McCorduck (09:00.560)
really intelligent by any amount. We wouldn't have thought of that in the 60s, even the 70s.
Lex Fridman (09:06.880)
So all these things have worked in. And I did hear one behavioral primatologist, Franz De Waal,
Pamela McCorduck (09:16.320)
say, AI taught us the questions to ask. Yeah, this is what happens, right? When you try to build it,
Pamela McCorduck (09:26.240)
is when you start to actually ask questions. It puts a mirror to ourselves. Yeah, right. So you
Pamela McCorduck (09:32.400)
were there in the middle of it. It seems like not many people were asking the questions that
Pamela McCorduck (09:38.880)
you were, or just trying to look at this field the way you were. I was so low. When I went to
Pamela McCorduck (09:45.920)
get funding for this because I needed somebody to transcribe the interviews and I needed travel
Pamela McCorduck (09:53.800)
expenses, I went to everything you could think of, the NSF, the DARPA. There was an Air Force
Pamela McCorduck (10:07.160)
place that doled out money. And each of them said, well, that's a very interesting idea.
Lex Fridman (10:15.480)
But we'll think about it. And the National Science Foundation actually said to me in plain English,
Pamela McCorduck (10:23.960)
hey, you're only a writer. You're not a historian of science. And I said, yeah, that's true. But
Pamela McCorduck (10:30.480)
the historians of science will be crawling all over this field. I'm writing for the general
Pamela McCorduck (10:35.400)
audience, so I thought. And they still wouldn't budge. I finally got a private grant without
Pamela McCorduck (10:43.880)
knowing who it was from, from Ed Fredkin at MIT. He was a wealthy man, and he liked what he called
Pamela McCorduck (10:51.400)
crackpot ideas. And he considered this a crackpot idea, and he was willing to support it. I am ever
Pamela McCorduck (10:58.680)
grateful, let me say that. Some would say that a history of science approach to AI, or even just a
Pamela McCorduck (11:06.720)
history, or anything like the book that you've written, hasn't been written since. Maybe I'm
Pamela McCorduck (11:13.760)
not familiar, but it's certainly not many. If we think about bigger than just these couple of
Pamela McCorduck (11:20.240)
decades, few decades, what are the roots of AI? Oh, they go back so far. Yes, of course, there's
Pamela McCorduck (11:30.640)
all the legendary stuff, the Golem and the early robots of the 20th century. But they go back much
Pamela McCorduck (11:41.240)
further than that. If you read Homer, Homer has robots in the Iliad. And a classical scholar was
Pamela McCorduck (11:49.680)
pointing out to me just a few months ago, well, you said you just read the Odyssey. The Odyssey
Pamela McCorduck (11:54.120)
is full of robots. It is, I said? Yeah. How do you think Odysseus's ship gets from one place to
Pamela McCorduck (12:00.800)
another? He doesn't have the crew people to do that, the crewmen. Yeah, it's magic. It's robots.
Pamela McCorduck (12:07.320)
Oh, I thought, how interesting. So we've had this notion of AI for a long time. And then toward the
Pamela McCorduck (12:17.240)
end of the 19th century, the beginning of the 20th century, there were scientists who actually
Pamela McCorduck (12:23.080)
tried to make this happen some way or another, not successfully. They didn't have the technology for
Pamela McCorduck (12:29.520)
it. And of course, Babbage in the 1850s and 60s, he saw that what he was building was capable of
Pamela McCorduck (12:40.080)
intelligent behavior. And when he ran out of funding, the British government finally said,
Pamela McCorduck (12:47.080)
that's enough. He and Lady Lovelace decided, oh, well, why don't we play the ponies with this? He
Pamela McCorduck (12:55.880)
had other ideas for raising money too. But if we actually reach back once again, I think people
Pamela McCorduck (13:02.400)
don't actually really know that robots do appear and ideas of robots. You talk about the Hellenic
Lex Fridman (13:09.160)
and the Hebraic points of view. Oh, yes. Can you tell me about each? I defined it this way. The
Pamela McCorduck (13:16.760)
Hellenic point of view is robots are great. They are party help. They help this guy Hephaestus,
Pamela McCorduck (13:25.160)
this god Hephaestus in his forge. I presume he made them to help him and so on and so forth.
Lex Fridman (13:32.560)
And they welcome the whole idea of robots. The Hebraic view has to do with, I think it's the
Pamela McCorduck (13:40.120)
second commandment, thou shalt not make any graven image. In other words, you better not
Pamela McCorduck (13:47.280)
start imitating humans because that's just forbidden. It's the second commandment. And
Pamela McCorduck (13:55.200)
a lot of the reaction to artificial intelligence has been a sense that this is somehow wicked,
Pamela McCorduck (14:08.800)
this is somehow blasphemous. We shouldn't be going there. Now, you can say, yeah, but there are going
Pamela McCorduck (14:17.600)
to be some downsides. And I say, yes, there are, but blasphemy is not one of them.
Lex Fridman (14:21.840)
You know, there is a kind of fear that feels to be almost primal. Is there religious roots to that?
Pamela McCorduck (14:29.800)
Because so much of our society has religious roots. And so there is a feeling of, like you
Pamela McCorduck (14:36.280)
said, blasphemy of creating the other, of creating something, you know, it doesn't have to be
Pamela McCorduck (14:43.800)
artificial intelligence. It's creating life in general. It's the Frankenstein idea.
Pamela McCorduck (14:48.640)
There's the annotated Frankenstein on my coffee table. It's a tremendous novel. It really is just
Pamela McCorduck (14:56.080)
beautifully perceptive. Yes, we do fear this and we have good reason to fear it,
Lex Fridman (15:03.880)
but because it can get out of hand. Maybe you can speak to that fear,
Pamela McCorduck (15:08.760)
the psychology, if you've thought about it. You know, there's a practical set of fears,
Pamela McCorduck (15:12.960)
concerns in the short term. You can think if we actually think about artificial intelligence
Pamela McCorduck (15:17.800)
systems, you can think about bias of discrimination in algorithms. You can think about their social
Pamela McCorduck (15:29.160)
networks have algorithms that recommend the content you see, thereby these algorithms control
Pamela McCorduck (15:35.520)
the behavior of the masses. There's these concerns. But to me, it feels like the fear
Lex Fridman (15:40.320)
that people have is deeper than that. So have you thought about the psychology of it?
Pamela McCorduck (15:46.280)
I think in a superficial way I have. There is this notion that if we produce a machine that
Pamela McCorduck (15:57.240)
can think, it will outthink us and therefore replace us.
Pamela McCorduck (16:01.240)
I guess that's a primal fear of almost kind of a kind of mortality. So around the time you said
Pamela McCorduck (16:11.960)
you worked at Stanford with Ed Feigenbaum. So let's look at that one person. Throughout his
Pamela McCorduck (16:21.760)
history, clearly a key person, one of the many in the history of AI. How has he changed in general
Lex Fridman (16:31.240)
around him? How has Stanford changed in the last, how many years are we talking about here?
Lex Fridman (16:36.440)
Oh, since 65.
Pamela McCorduck (16:38.400)
65. So maybe it doesn't have to be about him. It could be bigger. But because he was a key
Pamela McCorduck (16:45.000)
person in expert systems, for example, how is that, how are these folks who you've interviewed in the
Lex Fridman (16:54.160)
70s, 79 changed through the decades?
Pamela McCorduck (16:58.360)
In Ed's case, I know him well. We are dear friends. We see each other every month or so. He told me
Pamela McCorduck (17:12.240)
that when Machines Who Think first came out, he really thought all the front matter was kind of
Pamela McCorduck (17:17.040)
bologna. And 10 years later, he said, no, I see what you're getting at. Yes, this is an impulse
Pamela McCorduck (17:27.040)
that has been a human impulse for thousands of years to create something outside the human
Pamela McCorduck (17:34.800)
cranium that has intelligence. I think it's very hard when you're down at the algorithmic level,
Lex Fridman (17:46.000)
and you're just trying to make something work, which is hard enough to step back and think of
Pamela McCorduck (17:53.000)
the big picture. It reminds me of when I was in Santa Fe, I knew a lot of archaeologists,
Pamela McCorduck (17:59.720)
which was a hobby of mine. And I would say, yeah, yeah, well, you can look at the shards and say,
Pamela McCorduck (18:07.920)
oh, this came from this tribe and this came from this trade route and so on. But what about the big
Pamela McCorduck (18:14.080)
picture? And a very distinguished archaeologist said to me, they don't think that way. No,
Pamela McCorduck (18:21.840)
they're trying to match the shard to where it came from. Where did the remainder of this corn
Pamela McCorduck (18:30.520)
come from? Was it grown here? Was it grown elsewhere? And I think this is part of any
Pamela McCorduck (18:37.360)
scientific field. You're so busy doing the hard work, and it is hard work, that you don't step
Pamela McCorduck (18:46.800)
back and say, oh, well, now let's talk about the general meaning of all this. Yes.
Lex Fridman (18:53.120)
So none of the even Minsky and McCarthy, they...
Pamela McCorduck (18:58.320)
Oh, those guys did. Yeah. The founding fathers did.
Lex Fridman (19:01.840)
Early on or later?
Pamela McCorduck (19:03.920)
Pretty early on. But in a different way from how I looked at it. The two cognitive psychologists,
Pamela McCorduck (19:11.200)
Newell and Simon, they wanted to imagine reforming cognitive psychology so that we would really,
Pamela McCorduck (19:20.960)
really understand the brain. Minsky was more speculative. And John McCarthy saw it as,
Pamela McCorduck (19:32.960)
I think I'm doing him right by this, he really saw it as a great boon for human beings to have
Pamela McCorduck (19:40.320)
this technology. And that was reason enough to do it. And he had wonderful, wonderful
Pamela McCorduck (19:48.880)
fables about how if you do the mathematics, you will see that these things are really good for
Pamela McCorduck (19:56.800)
human beings. And if you had a technological objection, he had an answer, a technological
Pamela McCorduck (20:03.440)
answer. But here's how we could get over that and then blah, blah, blah. And one of his favorite things
Pamela McCorduck (20:10.320)
was what he called the literary problem, which of course he presented to me several times.
Pamela McCorduck (20:16.400)
That is everything in literature, there are conventions in literature. One of the conventions
Pamela McCorduck (20:23.680)
is that you have a villain and a hero. And the hero in most literature is human,
Lex Fridman (20:36.160)
and the villain in most literature is a machine. And he said, that's just not the way it's going
Pamela McCorduck (20:41.680)
to be. But that's the way we're used to it. So when we tell stories about AI, it's always
Pamela McCorduck (20:47.600)
with this paradigm. I thought, yeah, he's right. Looking back, the classics RUR is certainly the
Pamela McCorduck (20:57.040)
machines trying to overthrow the humans. Frankenstein is different. Frankenstein is
Pamela McCorduck (21:06.400)
a creature. He never has a name. Frankenstein, of course, is the guy who created him, the human,
Pamela McCorduck (21:13.440)
Dr. Frankenstein. This creature wants to be loved, wants to be accepted. And it is only when
Pamela McCorduck (21:22.320)
Frankenstein turns his head, in fact, runs the other way. And the creature is without love,
Pamela McCorduck (21:34.480)
that he becomes the monster that he later becomes.
Lex Fridman (21:38.560)
So who's the villain in Frankenstein? It's unclear, right?
Pamela McCorduck (21:43.840)
Oh, it is unclear, yeah.
Pamela McCorduck (21:45.520)
It's really the people who drive him. By driving him away, they bring out the worst.
Pamela McCorduck (21:54.240)
That's right. They give him no human solace. And he is driven away, you're right.
Pamela McCorduck (22:00.800)
He becomes, at one point, the friend of a blind man. And he serves this blind man,
Lex Fridman (22:08.160)
and they become very friendly. But when the sighted people of the blind man's family come in,
Pamela McCorduck (22:14.880)
ah, you've got a monster here. So it's very didactic in its way. And what I didn't know
Pamela McCorduck (22:23.040)
is that Mary Shelley and Percy Shelley were great readers of the literature surrounding abolition
Pamela McCorduck (22:31.120)
in the United States, the abolition of slavery. And they picked that up wholesale. You are making
Pamela McCorduck (22:38.720)
monsters of these people because you won't give them the respect and love that they deserve.
Lex Fridman (22:44.000)
Do you have, if we get philosophical for a second, do you worry that once we create
Pamela McCorduck (22:52.000)
machines that are a little bit more intelligent, let's look at Roomba, the vacuums, the cleaner,
Pamela McCorduck (22:58.080)
that this darker part of human nature where we abuse the other, the somebody who's different,
Lex Fridman (23:08.800)
will come out?
Pamela McCorduck (23:09.600)
I don't worry about it. I could imagine it happening. But I think that what AI has to offer
Pamela McCorduck (23:18.560)
the human race will be so attractive that people will be won over.
Lex Fridman (23:25.760)
So you have looked deep into these people, had deep conversations, and it's interesting to get
Pamela McCorduck (23:32.480)
a sense of stories of the way they were thinking and the way it was changed, the way your own
Pamela McCorduck (23:42.720)
thinking about AI has changed. So you mentioned McCarthy. What about the years at CMU, Carnegie
Pamela McCorduck (23:51.840)
Mellon, with Joe? Sure. Joe was not in AI. He was in algorithmic complexity.
Lex Fridman (24:03.440)
Was there always a line between AI and computer science, for example?
Lex Fridman (24:07.280)
Is AI its own place of outcasts? Was that the feeling?
Pamela McCorduck (24:10.880)
There was a kind of outcast period for AI. For instance, in 1974, the new field was hardly 10
Pamela McCorduck (24:24.560)
years old. The new field of computer science was asked by the National Science Foundation,
Lex Fridman (24:31.680)
I believe, but it may have been the National Academies, I can't remember,
Pamela McCorduck (24:34.400)
to tell your fellow scientists where computer science is and what it means.
Lex Fridman (24:44.160)
And they wanted to leave out AI. And they only agreed to put it in because Don Knuth said,
Pamela McCorduck (24:53.520)
hey, this is important. You can't just leave that out.
Lex Fridman (24:57.280)
Really? Don, dude?
Pamela McCorduck (24:58.240)
Don Knuth, yes.
Lex Fridman (24:59.680)
I talked to him recently, too. Out of all the people.
Pamela McCorduck (25:02.960)
Yes. But you see, an AI person couldn't have made that argument. He wouldn't have been believed.
Lex Fridman (25:08.640)
But Knuth was believed. Yes.
Lex Fridman (25:10.800)
So Joe Traub worked on the real stuff.
Pamela McCorduck (25:15.200)
Joe was working on algorithmic complexity. But he would say in plain English again and again,
Pamela McCorduck (25:22.160)
the smartest people I know are in AI.
Lex Fridman (25:24.720)
Really?
Pamela McCorduck (25:25.280)
Oh, yes. No question. Anyway, Joe loved these guys. What happened was that I guess it was
Pamela McCorduck (25:35.760)
as I started to write Machines Who Think, Herb Simon and I became very close friends.
Pamela McCorduck (25:41.360)
He would walk past our house on Northumberland Street every day after work. And I would just
Lex Fridman (25:47.200)
be putting my cover on my typewriter. And I would lean out the door and say,
Pamela McCorduck (25:52.160)
Herb, would you like a sherry? And Herb almost always would like a sherry. So he'd stop in
Lex Fridman (25:59.440)
and we'd talk for an hour, two hours. My journal says we talked this afternoon for three hours.
Lex Fridman (26:06.720)
What was on his mind at the time in terms of on the AI side of things?
Lex Fridman (26:11.680)
Oh, we didn't talk too much about AI. We talked about other things.
Pamela McCorduck (26:14.640)
Just life.
Pamela McCorduck (26:15.680)
We both love literature. And Herb had read Proust in the original French twice all the
Pamela McCorduck (26:24.000)
way through. I can't. I've read it in English in translation. So we talked about literature.
Pamela McCorduck (26:30.480)
We talked about languages. We talked about music because he loved music. We talked about
Pamela McCorduck (26:36.240)
art because he was actually enough of a painter that he had to give it up because he was afraid
Pamela McCorduck (26:44.960)
it was interfering with his research and so on. So no, it was really just chat, chat.
Lex Fridman (26:51.520)
But it was very warm. So one summer I said to Herb, my students have all the really
Pamela McCorduck (26:59.360)
interesting conversations. I was teaching at the University of Pittsburgh then in the English
Lex Fridman (27:03.920)
department. They get to talk about the meaning of life and that kind of thing. And what do I have?
Pamela McCorduck (27:09.920)
I have university meetings where we talk about the photocopying budget and whether the course
Pamela McCorduck (27:17.040)
on romantic poetry should be one semester or two. So Herb laughed. He said, yes, I know what you
Pamela McCorduck (27:23.040)
mean. He said, but you could do something about that. Dot, that was his wife, Dot and I used to
Pamela McCorduck (27:30.640)
have a salon at the University of Chicago every Sunday night. And we would have essentially an
Pamela McCorduck (27:38.560)
open house and people knew. It wasn't for a small talk. It was really for some topic of
Pamela McCorduck (27:47.600)
depth. He said, but my advice would be that you choose the topic ahead of time. Fine, I said.
Lex Fridman (27:54.480)
So we exchanged mail over the summer. That was US Post in those days because
Pamela McCorduck (28:01.680)
you didn't have personal email. And I decided I would organize it and there would be eight of us,
Pamela McCorduck (28:12.000)
Alan Noland, his wife, Herb Simon and his wife Dorothea. There was a novelist in town,
Pamela McCorduck (28:21.200)
a man named Mark Harris. He had just arrived and his wife Josephine. Mark was most famous then for
Pamela McCorduck (28:29.680)
a novel called Bang the Drum Slowly, which was about baseball. And Joe and me, so eight people.
Lex Fridman (28:36.720)
And we met monthly and we just sank our teeth into really hard topics and it was great fun.
Lex Fridman (28:45.760)
TK How have your own views around artificial intelligence changed
Lex Fridman (28:53.600)
through the process of writing Machines Who Think and afterwards, the ripple effects?
Pamela McCorduck (28:57.440)
RL I was a little skeptical that this whole thing would work out. It didn't matter. To me,
Pamela McCorduck (29:04.160)
it was so audacious. AI generally. And in some ways, it hasn't worked out the way I expected
Lex Fridman (29:16.800)
so far. That is to say, there's this wonderful lot of apps, thanks to deep learning and so on.
Lex Fridman (29:26.880)
But those are algorithmic. And in the part of symbolic processing, there's very little yet.
Lex Fridman (29:39.120)
And that's a field that lies waiting for industrious graduate students.
Pamela McCorduck (29:45.600)
TK Maybe you can tell me some figures that popped up in your life in the 80s with expert systems
Pamela McCorduck (29:53.040)
where there was the symbolic AI possibilities of what most people think of as AI,
Pamela McCorduck (30:00.960)
if you dream of the possibilities of AI, it's really expert systems. And those hit a few walls
Lex Fridman (30:07.520)
and there was challenges there. And I think, yes, they will reemerge again with some new
Pamela McCorduck (30:12.080)
breakthroughs and so on. But what did that feel like, both the possibility and the winter that
Pamela McCorduck (30:17.760)
followed the slowdown in research? BG Ah, you know, this whole thing about AI winter is to me
Pamela McCorduck (30:25.040)
a crock. TK Snow winters.
Pamela McCorduck (30:26.960)
BG Because I look at the basic research that was being done in the 80s, which is supposed to be,
Pamela McCorduck (30:34.480)
my God, it was really important. It was laying down things that nobody had thought about before,
Lex Fridman (30:40.320)
but it was basic research. You couldn't monetize it. Hence the winter.
Pamela McCorduck (30:44.880)
TK That's the winter. BG You know, research,
Lex Fridman (30:49.120)
scientific research goes and fits and starts. It isn't this nice smooth,
Pamela McCorduck (30:54.240)
oh, this follows this follows this. No, it just doesn't work that way.
Pamela McCorduck (30:59.040)
TK The interesting thing, the way winters happen, it's never the fault of the researchers.
Pamela McCorduck (31:05.760)
It's the some source of hype over promising. Well, no, let me take that back. Sometimes it
Pamela McCorduck (31:12.000)
is the fault of the researchers. Sometimes certain researchers might over promise the
Pamela McCorduck (31:17.200)
possibilities. They themselves believe that we're just a few years away. Sort of just recently
Pamela McCorduck (31:23.520)
talked to Elon Musk and he believes he'll have an autonomous vehicle, will have autonomous vehicles
Lex Fridman (31:28.160)
in a year. And he believes it. BG A year?
Lex Fridman (31:30.640)
TK A year. Yeah. With mass deployment of a time.
Pamela McCorduck (31:33.360)
BG For the record, this is 2019 right now. So he's talking 2020.
Pamela McCorduck (31:38.640)
TK To do the impossible, you really have to believe it. And I think what's going to happen
Pamela McCorduck (31:44.480)
when you believe it, because there's a lot of really brilliant people around him,
Pamela McCorduck (31:48.240)
is some good stuff will come out of it. Some unexpected brilliant breakthroughs will come out
Pamela McCorduck (31:53.840)
of it when you really believe it, when you work that hard. BG I believe that. And I believe
Lex Fridman (31:58.480)
autonomous vehicles will come. I just don't believe it'll be in a year. I wish.
Pamela McCorduck (32:02.640)
TK But nevertheless, there's, autonomous vehicles is a good example. There's a feeling
Pamela McCorduck (32:09.120)
many companies have promised by 2021, by 2022, Ford, GM, basically every single automotive
Pamela McCorduck (32:16.640)
company has promised they'll have autonomous vehicles. So that kind of over promise is what
Pamela McCorduck (32:21.440)
leads to the winter. Because we'll come to those dates, there won't be autonomous vehicles.
Pamela McCorduck (32:26.720)
BG And there'll be a feeling, well, wait a minute, if we took your word at that time,
Pamela McCorduck (32:32.080)
that means we just spent billions of dollars, had made no money, and there's a counter response to
Pamela McCorduck (32:39.680)
where everybody gives up on it. Sort of intellectually, at every level, the hope just
Pamela McCorduck (32:46.880)
dies. And all that's left is a few basic researchers. So you're uncomfortable with
Pamela McCorduck (32:52.960)
some aspects of this idea. TK Well, it's the difference between science and commerce.
Lex Fridman (32:58.400)
BG So you think science goes on the way it does?
Pamela McCorduck (33:04.160)
TK Oh, science can really be killed by not getting proper funding or timely funding.
Lex Fridman (33:14.160)
I think Great Britain was a perfect example of that. The Lighthill report in,
Pamela McCorduck (33:19.440)
I can't remember the year, essentially said, there's no use Great Britain putting any money
Pamela McCorduck (33:26.560)
into this, it's going nowhere. And this was all about social factions in Great Britain.
Pamela McCorduck (33:37.040)
Edinburgh hated Cambridge and Cambridge hated Manchester. Somebody else can write that story.
Lex Fridman (33:44.720)
But it really did have a hard effect on research there. Now, they've come roaring back with Deep
Pamela McCorduck (33:54.400)
Mind. But that's one guy and his visionaries around him. BG But just to push on that,
Lex Fridman (34:03.760)
it's kind of interesting. You have this dislike of the idea of an AI winter.
Pamela McCorduck (34:08.320)
Where's that coming from? Where were you? TK Oh, because I just don't think it's true.
Lex Fridman (34:15.440)
BG There was a particular period of time. It's a romantic notion, certainly.
Pamela McCorduck (34:21.280)
TK Yeah, well. No, I admire science, perhaps more than I admire commerce. Commerce is fine. Hey,
Pamela McCorduck (34:33.280)
you know, we all gotta live. But science has a much longer view than commerce and continues
Pamela McCorduck (34:46.720)
almost regardless. It can't continue totally regardless, but almost regardless of what's
Pamela McCorduck (34:56.400)
saleable and what's not, what's monetizable and what's not. BG So the winter is just something
Pamela McCorduck (35:01.680)
that happens on the commerce side, and the science marches. That's a beautifully optimistic
Lex Fridman (35:10.960)
and inspiring message. I agree with you. I think if we look at the key people that work in AI,
Pamela McCorduck (35:16.400)
that work in key scientists in most disciplines, they continue working out of the love for science.
Pamela McCorduck (35:22.160)
You can always scrape up some funding to stay alive, and they continue working diligently.
Lex Fridman (35:31.680)
But there certainly is a huge amount of funding now, and there's a concern on the AI side and
Pamela McCorduck (35:38.080)
deep learning. There's a concern that we might, with over promising, hit another slowdown in
Pamela McCorduck (35:44.160)
funding, which does affect the number of students, you know, that kind of thing.
Lex Fridman (35:47.520)
RG Yeah, it does. BG So the kind of ideas you had in Machines Who Think,
Lex Fridman (35:52.640)
did you continue that curiosity through the decades that followed?
Pamela McCorduck (35:56.240)
RG Yes, I did. BG And what was your view, historical view of how AI community evolved,
Lex Fridman (36:03.840)
the conversations about it, the work? Has it persisted the same way from its birth?
Pamela McCorduck (36:09.280)
RG No, of course not. It's just as we were just talking, the symbolic AI really kind of dried up
Lex Fridman (36:19.760)
and it all became algorithmic. I remember a young AI student telling me what he was doing,
Lex Fridman (36:27.200)
and I had been away from the field long enough. I'd gotten involved with complexity at the Santa
Pamela McCorduck (36:33.200)
Fe Institute. I thought, algorithms, yeah, they're in the service of, but they're not the main event.
Pamela McCorduck (36:41.680)
No, they became the main event. That surprised me. And we all know the downside of this. We all
Pamela McCorduck (36:49.440)
know that if you're using an algorithm to make decisions based on a gazillion human decisions,
Pamela McCorduck (36:58.240)
baked into it are all the mistakes that humans make, the bigotries, the short sightedness,
Lex Fridman (37:05.440)
and so on and so on. BG So you mentioned Santa Fe Institute. So you've written the novel
Pamela McCorduck (37:13.280)
Edge of Chaos, but it's inspired by the ideas of complexity, a lot of which have been extensively
Pamela McCorduck (37:20.720)
explored at the Santa Fe Institute. It's another fascinating topic, just sort of emergent
Pamela McCorduck (37:31.200)
complexity from chaos. Nobody knows how it happens really, but it seems to where all the interesting
Pamela McCorduck (37:37.440)
stuff does happen. So how did first, not your novel, but just complexity in general and the
Pamela McCorduck (37:44.480)
work at Santa Fe, fit into the bigger puzzle of the history of AI? Or maybe even your personal
Pamela McCorduck (37:51.600)
journey through that? RG One of the last projects I did
Pamela McCorduck (37:57.760)
concerning AI in particular was looking at the work of Harold Cohen, the painter. And Harold was
Pamela McCorduck (38:06.080)
deeply involved with AI. He was a painter first. And what his project, ARIN, which was a lifelong
Pamela McCorduck (38:17.920)
project, did was reflect his own cognitive processes. Okay. Harold and I, even though I wrote
Pamela McCorduck (38:30.480)
a book about it, we had a lot of friction between us. And I went, I thought, this is it. The book
Pamela McCorduck (38:39.120)
died. It was published and fell into a ditch. This is it. I'm finished. It's time for me to
Pamela McCorduck (38:47.760)
do something different. By chance, this was a sabbatical year for my husband. And we spent two
Pamela McCorduck (38:55.840)
months at the Santa Fe Institute and two months at Caltech. And then the spring semester in Munich,
Pamela McCorduck (39:03.120)
Germany. Okay. Those two months at the Santa Fe Institute were so restorative for me. And I began
Pamela McCorduck (39:15.040)
to, the Institute was very small then. It was in some kind of office complex on old Santa Fe trail.
Pamela McCorduck (39:22.560)
Everybody kept their door open. So you could crack your head on a problem. And if you finally didn't
Pamela McCorduck (39:29.840)
get it, you could walk in to see Stuart Kaufman or any number of people and say, I don't get this.
Lex Fridman (39:39.040)
Can you explain? And one of the people that I was talking to about complex adaptive systems
Pamela McCorduck (39:46.880)
was Murray Gelman. And I told Murray what Harold Cohen had done. And I said, you know,
Lex Fridman (39:55.200)
this sounds to me like a complex adaptive system. And he said, yeah, it is. Well, what do you know?
Pamela McCorduck (40:02.240)
Harold Aaron had all these kids and cousins all over the world in science and in economics and
Lex Fridman (40:09.120)
so on and so forth. I was so relieved. I thought, okay, your instincts are okay. You're doing the
Pamela McCorduck (40:16.480)
right thing. I didn't have the vocabulary. And that was one of the things that the Santa Fe
Pamela McCorduck (40:21.760)
Institute gave me. If I could have rewritten that book, no, it had just come out. I couldn't rewrite
Pamela McCorduck (40:26.880)
it. I would have had a vocabulary to explain what Aaron was doing. Okay. So I got really interested
Pamela McCorduck (40:34.480)
in what was going on at the Institute. The people were, again, bright and funny and willing to
Pamela McCorduck (40:44.080)
explain anything to this amateur. George Cowan, who was then the head of the Institute, said he
Pamela McCorduck (40:51.600)
thought it might be a nice idea if I wrote a book about the Institute. And I thought about it and I
Pamela McCorduck (40:58.800)
had my eye on some other project, God knows what. And I said, I'm sorry, George. Yeah, I'd really
Pamela McCorduck (41:05.920)
love to do it, but just not going to work for me at this moment. He said, oh, too bad. I think it
Pamela McCorduck (41:11.440)
would make an interesting book. Well, he was right and I was wrong. I wish I'd done it. But that's
Pamela McCorduck (41:17.120)
interesting. I hadn't thought about that, that that was a road not taken that I wish I'd taken.
Pamela McCorduck (41:22.080)
Well, you know what? Just on that point, it's quite brave for you as a writer, as sort of
Pamela McCorduck (41:31.680)
coming from a world of literature and the literary thinking and historical thinking. I mean, just
Pamela McCorduck (41:37.120)
from that world and bravely talking to quite, I assume, large egos in AI or in complexity.
Pamela McCorduck (41:49.600)
Yeah, in AI or in complexity and so on. How'd you do it? I mean, I suppose they could be
Lex Fridman (41:59.040)
intimidated of you as well because it's two different worlds coming together.
Pamela McCorduck (42:03.120)
I never picked up that anybody was intimidated by me.
Lex Fridman (42:06.080)
But how were you brave enough? Where did you find the guts to sort of...
Pamela McCorduck (42:08.640)
God, just dumb luck. I mean, this is an interesting rock to turn over. I'm going
Pamela McCorduck (42:14.000)
to write a book about it. And you know, people have enough patience with writers
Pamela McCorduck (42:18.880)
if they think they're going to end up in a book that they let you flail around and so on.
Lex Fridman (42:24.800)
Well, but they also look if the writer has,
Pamela McCorduck (42:28.320)
if there's a sparkle in their eye, if they get it.
Lex Fridman (42:31.120)
Yeah, sure.
Lex Fridman (42:32.640)
When were you at the Santa Fe Institute?
Pamela McCorduck (42:35.920)
The time I'm talking about is 1990, 1991, 1992. But we then, because Joe was an external faculty
Pamela McCorduck (42:46.240)
member, were in Santa Fe every summer. We bought a house there and I didn't have that much to do
Pamela McCorduck (42:52.640)
with the Institute anymore. I was writing my novels. I was doing whatever I was doing.
Lex Fridman (43:00.560)
But I loved the Institute and I loved
Lex Fridman (43:08.400)
again, the audacity of the ideas. That really appeals to me.
Pamela McCorduck (43:12.960)
I think that there's this feeling, much like in great institutes of neuroscience, for example,
Pamela McCorduck (43:23.040)
that they're in it for the long game of understanding something fundamental about
Pamela McCorduck (43:29.840)
reality and nature. And that's really exciting. So if we start now to look a little bit more recently,
Pamela McCorduck (43:36.800)
how, you know, AI is really popular today. How is this world, you mentioned algorithmic,
Lex Fridman (43:46.480)
but in general, is the spirit of the people, the kind of conversations you hear through the
Lex Fridman (43:51.680)
grapevine and so on, is that different than the roots that you remember?
Pamela McCorduck (43:55.360)
No. The same kind of excitement, the same kind of, this is really going to make a difference
Pamela McCorduck (44:01.200)
in the world. And it will. It has. You know, a lot of folks, especially young, 20 years old or
Pamela McCorduck (44:07.920)
something, they think we've just found something special here. We're going to change the world
Pamela McCorduck (44:14.000)
tomorrow. On a time scale, do you have a sense of what, of the time scale at which breakthroughs
Pamela McCorduck (44:24.240)
of the time scale at which breakthroughs in AI happen? I really don't. Because look at Deep Learning.
Pamela McCorduck (44:32.240)
That was, Jeffrey Hinton came up with the algorithm in 86. But it took all these years
Pamela McCorduck (44:44.720)
for the technology to be good enough to actually be applicable. So no, I can't predict that at all.
Pamela McCorduck (44:56.400)
I can't. I wouldn't even try. Well, let me ask you to, not to try to predict, but to speak to the,
Pamela McCorduck (45:03.760)
you know, I'm sure in the 60s, as it continues now, there's people that think, let's call it,
Pamela McCorduck (45:09.440)
we can call it this fun word, the singularity. When there's a phase shift, there's some profound
Pamela McCorduck (45:16.160)
feeling where we're all really surprised by what's able to be achieved. I'm sure those dreams are
Pamela McCorduck (45:22.720)
there. I remember reading quotes in the 60s and those continued. How have your own views,
Lex Fridman (45:29.200)
maybe if you look back, about the timeline of a singularity changed?
Lex Fridman (45:34.960)
Well, I'm not a big fan of the singularity as Ray Kurzweil has presented it.
Lex Fridman (45:46.640)
How would you define the Ray Kurzweil? How do you think of singularity in those?
Pamela McCorduck (45:53.120)
If I understand Kurzweil's view, it's sort of, there's going to be this moment when machines
Pamela McCorduck (45:59.280)
are smarter than humans and, you know, game over. However, the game over is. I mean, do they put us
Pamela McCorduck (46:07.120)
on a reservation? Do they, et cetera, et cetera. And first of all, machines are smarter than humans
Pamela McCorduck (46:15.680)
in some ways all over the place. And they have been since adding machines were invented.
Lex Fridman (46:21.440)
So it's not, it's not going to come like some great eatable crossroads, you know, where
Pamela McCorduck (46:29.440)
they meet each other and our offspring, Oedipus says, you're dead. It's just not going to happen.
Pamela McCorduck (46:37.920)
Yeah. So it's already game over with calculators, right? They're already out to do much better at
Pamela McCorduck (46:44.000)
basic arithmetic than us. But you know, there's a human like intelligence. And it's not the ones
Pamela McCorduck (46:51.920)
that destroy us, but you know, somebody that you can have as a, as a friend, you can have deep
Pamela McCorduck (46:57.920)
connections with that kind of passing the touring test and beyond those kinds of ideas. Have you
Pamela McCorduck (47:04.640)
dreamt of those? Oh yes, yes, yes. Those possibilities. In a book I wrote with Ed Feigenbaum,
Pamela McCorduck (47:10.560)
a book I wrote with Ed Feigenbaum, there's a little story called the geriatric robot.
Lex Fridman (47:17.280)
And how I came up with the geriatric robot is a story in itself. But here's what the geriatric
Pamela McCorduck (47:24.880)
robot does. It doesn't just clean you up and feed you and wheel you out into the sun.
Pamela McCorduck (47:29.520)
It's great advantages. It listens. It says, tell me again about the great coup of 73. Tell me again
Pamela McCorduck (47:45.280)
about how awful or how wonderful your grandchildren are and so on and so forth.
Lex Fridman (47:52.960)
And it isn't hanging around to inherit your money. It isn't hanging around because it can't get
Pamela McCorduck (47:59.440)
any other job. This is his job. And so on and so forth. Well, I would love something like that.
Lex Fridman (48:09.120)
Yeah. I mean, for me, that deeply excites me. So I think there's a lot of us.
Pamela McCorduck (48:15.680)
Lex, you gotta know, it was a joke. I dreamed it up because I needed to talk to college students
Lex Fridman (48:20.880)
and I needed to give them some idea of what AI might be. And they were rolling in the aisles as
Pamela McCorduck (48:26.960)
I elaborated and elaborated and elaborated. When it went into the book, they took my hide off
Pamela McCorduck (48:36.320)
in the New York Review of Books. This is just what we have thought about these people in AI.
Pamela McCorduck (48:41.280)
They're inhuman. Come on, get over it. Don't you think that's a good thing for
Lex Fridman (48:47.280)
the world that AI could potentially do? I do. Absolutely. And furthermore,
Pamela McCorduck (48:52.000)
I'm pushing 80 now. By the time I need help like that, I also want it to roll itself in a corner
Lex Fridman (49:02.560)
and shut the fuck up. Let me linger on that point. Do you really though?
Lex Fridman (49:09.360)
Yeah, I do. Here's why. Don't you want it to push back a little bit?
Pamela McCorduck (49:13.360)
A little. But I have watched my friends go through the whole issue around having help
Pamela McCorduck (49:20.240)
in the house. And some of them have been very lucky and had fabulous help. And some of them
Pamela McCorduck (49:28.880)
have had people in the house who want to keep the television going on all day, who want to talk on
Pamela McCorduck (49:34.000)
their phones all day. No. Just roll yourself in the corner and shut the fuck up. Unfortunately,
Pamela McCorduck (49:41.360)
us humans, when we're assistants, we're still, even when we're assisting others,
Pamela McCorduck (49:47.040)
we care about ourselves more. Of course. And so you create more frustration. And a robot AI
Pamela McCorduck (49:54.800)
assistant can really optimize the experience for you. I was just speaking to the point,
Pamela McCorduck (50:01.520)
you actually bring up a very, very good point. But I was speaking to the fact that
Pamela McCorduck (50:05.360)
us humans are a little complicated, that we don't necessarily want a perfect servant.
Pamela McCorduck (50:11.120)
I don't, maybe you disagree with that, but there's a, I think there's a push and pull with humans.
Lex Fridman (50:20.800)
You're right.
Pamela McCorduck (50:21.360)
A little tension, a little mystery that, of course, that's really difficult for AI to get right. But
Pamela McCorduck (50:27.680)
I do sense, especially today with social media, that people are getting more and more lonely,
Pamela McCorduck (50:34.800)
even young folks, and sometimes especially young folks, that loneliness, there's a longing for
Pamela McCorduck (50:42.080)
connection and AI can help alleviate some of that loneliness. Some, just somebody who listens,
Pamela McCorduck (50:50.800)
like in person. So to speak. So to speak, yeah. So to speak. Yeah, that to me is really exciting.
Pamela McCorduck (51:03.200)
That is really exciting. But so if we look at that, that level of intelligence, which is
Pamela McCorduck (51:08.880)
exceptionally difficult to achieve actually, as the singularity or whatever, that's the human level
Pamela McCorduck (51:15.520)
bar, that people have dreamt of that too. Turing dreamt of it. He had a date timeline. Do you have,
Lex Fridman (51:23.920)
how have your own timeline evolved on past?
Lex Fridman (51:27.840)
I don't even think about it.
Lex Fridman (51:28.960)
You don't even think?
Lex Fridman (51:29.680)
No. Just this field has been so full of surprises for me.
Pamela McCorduck (51:38.080)
You're just taking in and see the fun about the basic science.
Pamela McCorduck (51:42.080)
Yeah. I just can't. Maybe that's because I've been around the field long enough to think,
Pamela McCorduck (51:48.960)
you know, don't go that way. Herb Simon was terrible about making these predictions of
Lex Fridman (51:54.720)
when this and that would happen. And he was a sensible guy.
Lex Fridman (52:00.640)
His quotes are often used, right?
Lex Fridman (52:03.360)
As a legend, yeah.
Pamela McCorduck (52:04.880)
Yeah. Do you have concerns about AI, the existential threats that many people
Lex Fridman (52:14.800)
like Elon Musk and Sam Harris and others are thinking about?
Pamela McCorduck (52:18.800)
Yeah. That takes up half a chapter in my book. I call it the male gaze.
Lex Fridman (52:29.600)
Well, you hear me out. The male gaze is actually a term from film criticism.
Lex Fridman (52:36.240)
And I'm blocking on the women who dreamed this up. But she pointed out how most movies were
Pamela McCorduck (52:44.240)
made from the male point of view, that women were objects, not subjects. They didn't have any
Pamela McCorduck (52:53.760)
agency and so on and so forth. So when Elon and his pals Hawking and so on came,
Lex Fridman (53:01.520)
AI is going to eat our lunch and our dinner and our midnight snack too, I thought, what?
Lex Fridman (53:08.000)
And I said to Ed Feigenbaum, oh, this is the first guy. First, these guys have always been
Pamela McCorduck (53:13.120)
the smartest guy on the block. And here comes something that might be smarter. Oh, let's stamp
Pamela McCorduck (53:18.800)
it out before it takes over. And Ed laughed. He said, I didn't think about it that way.
Lex Fridman (53:24.080)
But I did. I did. And it is the male gaze. Okay, suppose these things do have agency.
Pamela McCorduck (53:34.480)
Well, let's wait and see what happens. Can we imbue them with ethics? Can we imbue them
Pamela McCorduck (53:43.920)
with a sense of empathy? Or are they just going to be, I don't know, we've had centuries of guys
Pamela McCorduck (53:54.480)
like that. That's interesting that the ego, the male gaze is immediately threatened. And so you
Pamela McCorduck (54:05.280)
can't think in a patient, calm way of how the tech could evolve. Speaking of which, your 96 book,
Pamela McCorduck (54:16.240)
The Future of Women, I think at the time and now, certainly now, I mean, I'm sorry, maybe at the
Pamela McCorduck (54:23.840)
time, but I'm more cognizant of now, is extremely relevant. You and Nancy Ramsey talk about four
Pamela McCorduck (54:30.800)
possible futures of women in science and tech. So if we look at the decades before and after
Pamela McCorduck (54:38.960)
the book was released, can you tell a history, sorry, of women in science and tech and how it
Pamela McCorduck (54:46.800)
has evolved? How have things changed? Where do we stand? Not enough. They have not changed enough.
Pamela McCorduck (54:54.320)
The way that women are ground down in computing is simply unbelievable. But what are the four
Pamela McCorduck (55:05.840)
possible futures for women in tech from the book? What you're really looking at are various aspects
Pamela McCorduck (55:13.520)
of the present. So for each of those, you could say, oh yeah, we do have backlash. Look at what's
Pamela McCorduck (55:20.880)
happening with abortion and so on and so forth. We have one step forward, one step back.
Pamela McCorduck (55:28.400)
The golden age of equality was the hardest chapter to write. And I used something from
Pamela McCorduck (55:33.440)
the Santa Fe Institute, which is the sandpile effect, that you drop sand very slowly onto a pile
Lex Fridman (55:41.760)
and it grows and it grows and it grows until suddenly it just breaks apart. And
Pamela McCorduck (55:50.240)
in a way, Me Too has done that. That was the last drop of sand that broke everything apart.
Pamela McCorduck (55:58.240)
That was a perfect example of the sandpile effect. And that made me feel good. It didn't
Pamela McCorduck (56:03.760)
change all of society, but it really woke a lot of people up. But are you in general optimistic
Pamela McCorduck (56:10.480)
about maybe after Me Too? I mean, Me Too is about a very specific kind of thing.
Pamela McCorduck (56:17.120)
Boy, solve that and you solve everything.
Lex Fridman (56:19.920)
But are you in general optimistic about the future?
Pamela McCorduck (56:23.200)
Yes. I'm a congenital optimistic. I can't help it.
Lex Fridman (56:28.400)
What about AI? What are your thoughts about the future of AI?
Pamela McCorduck (56:34.560)
Of course, I get asked, what do you worry about? And the one thing I worry about is the things
Pamela McCorduck (56:40.080)
we can't anticipate. There's going to be something out of left field that we will just say,
Pamela McCorduck (56:47.440)
we weren't prepared for that. I am generally optimistic. When I first took up
Pamela McCorduck (56:58.240)
being interested in AI, like most people in the field, more intelligence was like more virtue.
Pamela McCorduck (57:05.760)
You know, what could be bad? And in a way, I still believe that. But I realize that my
Lex Fridman (57:13.520)
notion of intelligence has broadened. There are many kinds of intelligence,
Lex Fridman (57:19.440)
and we need to imbue our machines with those many kinds.
Lex Fridman (57:24.720)
So you've now just finished or in the process of finishing the book that you've been working
Pamela McCorduck (57:32.560)
on, the memoir, how have you changed? I know it's just writing, but how have you changed
Pamela McCorduck (57:39.440)
the process? If you look back, what kind of stuff did it bring up to you that surprised you,
Pamela McCorduck (57:47.600)
looking at the entirety of it all? The biggest thing, and it really wasn't a surprise,
Pamela McCorduck (57:55.840)
is how lucky I was. Oh, my. To have access to the beginning of a scientific field that is going to
Pamela McCorduck (58:07.520)
change the world. How did I luck out? And yes, of course, my view of things has widened a lot.
Lex Fridman (58:20.240)
If I can get back to one feminist part of our conversation. Without knowing it,
Pamela McCorduck (58:28.640)
it really was subconscious. I wanted AI to succeed because I was so tired of hearing
Pamela McCorduck (58:36.320)
that intelligence was inside the male cranium. And I thought if there was something out there
Pamela McCorduck (58:43.280)
that wasn't a male thinking and doing well, then that would put a lie to this whole notion of
Pamela McCorduck (58:53.040)
intelligence resides in the male cranium. I did not know that until one night Harold Cohen and I
Pamela McCorduck (59:01.600)
were having a glass of wine, maybe two, and he said, what drew you to AI? And I said, oh,
Pamela McCorduck (59:09.600)
you know, smartest people I knew, great project, blah, blah, blah. And I said, and I wanted
Lex Fridman (59:14.720)
something besides male smarts. And it just bubbled up out of me like, what?
Pamela McCorduck (59:24.160)
It's kind of brilliant, actually. So AI really humbles all of us and humbles the people that
Pamela McCorduck (59:32.000)
need to be humbled the most. Let's hope.
Pamela McCorduck (59:35.360)
Wow. That is so beautiful. Pamela, thank you so much for talking to me. It's really a huge honor.
Pamela McCorduck (59:40.800)
It's been a great pleasure.
Lex Fridman (59:41.840)
Thank you.
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