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Tea. That's p i q u e. I have had so

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>> Optimal minimal >> At this
altitude [music] I can run flat

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out for a half mile before
my hands start shaking.

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>> Can I ask you a personal question?

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>> No, I just ate my breakfast time.

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>> What if I did the opposite?

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>> I'm a cybernetic organism living this
year over middle [music] impulse power.

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>> Hello boys and girls, ladies and germs.

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This is Tim Ferriss. Welcome to another
episode of The Tim Ferriss Show. My

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guest today is Eric Schmidt. Eric

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Schmidt, that's s c h m i d t on Twitter

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@ericschmidt, is a technologist,
entrepreneur, and philanthropist. He

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joined Google in 2001 helping
the company grow from a Silicon Valley

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startup to a global technology leader.

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He served as chief executive officer
and chairman from 2001 to 2011 and as

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executive chairman and technical advisor
thereafter. Under his leadership Google

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dramatically scaled its infrastructure
and diversified its product offerings

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while maintaining a culture of innovation.
In 2017 he co-founded

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Schmidt Futures, a philanthropic
initiative that bets early on

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exceptional people making the world
better. He serves as chair of the Broad

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Institute and formerly served as chair
of the National Security Commission on

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Artificial Intelligence. He's the host
of Reimagine with Eric Schmidt, a

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podcast exploring how society can build
a brighter future after the COVID-19

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pandemic. With co-authors Henry A.

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Kissinger and Daniel Huttenlocher, Eric

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has a new book out titled The Age of AI
and Our Human Future. You can find him

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again on Twitter @ericschmidt
and at ericschmidt.com.

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Eric, welcome back to the show.

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>> Thank you. I really look
forward to this conversation.

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>> I have been looking forward to this and

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I want to confess first and foremost

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that I have tremendous insecurity around

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my lack of clarity on AI. So, I am

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really looking forward to digging into

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many facets, but before we get to that,

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I want to pick out Henry Kissinger. How

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did you come to collaborate with Henry

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Kissinger? >> About 12
years ago, I met him at a

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conference called Bilderberg.

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And my father worked for the Nixon
administration when I was very young.

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And my father

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had Henry as a hero. He said he was the

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most brilliant, hardest working, and he

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was enigmatic because he has both a very

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favorable reputation, but also
a very controversial reputation.

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So, we chatted and he said, "The only

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problem I have with Google is I think
that you're going to destroy the world."

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And I thought, "Well, that's
a challenge from Henry Kissinger."

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So, we invited him to Google,
where he gave a speech.

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And he confronted the employees directly
on the manipulation that Google was

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doing in his view of the public discourse.

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And his criticisms were so apt, and the
people enjoyed it so much that we struck

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up a friendship.
And although we're politically very

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different with very different backgrounds,

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I've come to learn that working with
someone this brilliant at any age is

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phenomenal. But when
your co-author is 98, it's a

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special treat. >> I looked
up the age. I'm glad you

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mentioned it. 98.

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To what do you attribute him remaining

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cognitively sharp into his late 90s? Is

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that just good hardware out of the box?

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Is there more to it?

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>> He works harder than a 40-year-old.

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I can tell you that he gets up in the
morning and he works all day. He has

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dinner with his wife and his family, and

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then he works at night. And he keeps up

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that pace 7 days a week at 98.

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I am convinced that the secret
to longevity is being a workaholic.

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>> [laughter] >> And and
the reason I say that is that

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Henry Kissinger at the age
of 90 knew nothing about the

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digital world, although he
had a lot of opinions about

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it. But he has mastered the digital world

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and artificial intelligence

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with the alacrity and the speed of

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people who are just getting into it now.

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That's unique to him. That's a gift. And

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that's why his analysis
of our world is so incredibly

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interesting to me. >> All right,
we're going to spend a little

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more time on on Henry because I must

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scratch this itch. So you are very good

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at systematizing thinking from first

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principles, whether it's systematizing

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innovation or hiring, thinking of things

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at scale. There's a method to not the

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madness, but the outcomes.

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Was Henry's ability to learn so quickly

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based on some approach that he has to
first principles or a framework [snorts]

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of any type that you've
seen exhibited in him

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that he applies to new domains?

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>> There've been some studies about the
age at which you are your most productive

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professionally. And as you
know in math and science,

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brilliance tends to show up young,
in their 20s. They tend to get early

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awards. Historians,
however, seem to get better

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with age. Maybe it's
the accumulation of perspective

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and the accumulation of reasoning and

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the depth of wisdom that is represented

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by increasing age. And so

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Dr. Kissinger has both
the benefit of being a brilliant

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historian and also having changed

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history and lived in the moment.

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And today he spends a great deal of his

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time with people talking to him about

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current affairs and judging them with

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his historical principles in mind.

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It is from that basis of insight

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that when he looked at AI, he said,

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"This is a very much bigger thing

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than people think it is." And I said to

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him, "Why?" I honestly didn't know.

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And he said, "Because we're discussing
artificial intelligence as though it's a

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technology. This is like
the beginning of the Renaissance."

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And I said, "Tell me about
the Renaissance. What else do you say to a

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historian who's famous?" And we started
to talk about the Renaissance, and he

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said that the Renaissance is really

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about the age of reason. It's about

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individuals being able to think through

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their systems. It's about society

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allowing experts to criticize other

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people. Before the Renaissance,
decision-making was essentially

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hierarchical and from a king or a

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religious leader.

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That change allowed us to develop

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intellectual thought.
He is arguing that we're entering a new

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epoch similar to the
Renaissance, this age of

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artificial intelligence, because

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humanity has never had a competitive
intelligence similar to itself but not

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human. >> I'd love to hear
you elaborate just a a

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bit, and then we're going to dig into a

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whole slew of questions that I have in

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front of me. How you thought about the

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composition of the co-authors on this

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book, and certainly would love to learn
more about Daniel. I know a little bit

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about Daniel Huttenlocher, but I'd love
to hear more. And we could start with

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Dr. Kissinger. I realize
calling him Henry's probably

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going to give me bad karma, so I'll

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start with Dr. Kissinger.

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Is it his broad familiarity with history

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as well as his knowledge of geopolitics

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and statecraft that you were hoping to

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augment everything else in the book?

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Maybe you could just speak to how you
think about what each party brings to

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this project?
>> In our collaboration, the book

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suggestion was actually from Dr.

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Kissinger. And what he basically said

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is that we have an opportunity

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to architect the questions

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that need to get answered
in the next 10, 20, 30 years. I would

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parenthetically offer that we didn't

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understand when we invented social media

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15 years ago or so,

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the extraordinary and compound benefits

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and costs of social media to our society

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and particular political discourse.

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So, armed with that knowledge that the
tech industry had invented a tool that

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outstripped the governance of it,
at least initially and maybe for a long

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time, Dr. Kissinger said, "This
is an opportunity to ask the right

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questions."

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We recruited Dan Huttenlocher, who is

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the Dean of MIT computer science,
partly because he's a good friend and

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partly because he's such a good scientist,

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he will make sure that our claims are

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accurate.

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And Dan worked very hard to get the path

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of AI correct.
Many of the books about artificial

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intelligence are speculative,

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but I'm not aware of any book

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that has both the geopolitical, social,

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and historical context,
but also has the technology correct.

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>> Just to look at the opposite
of speculative from a first-hand

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perspective, could you tell

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a story or two about what you've seen or

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experienced firsthand with AI?

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>> Well, you use AI today whenever you use

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Google Search, Google Ads, spelling
correction, Google Translate. The story

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on AI

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that's not really well understood is

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that in the 1960s and 70s when I started

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AI was going to happen within a decade.

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And my friends who were AI obsessed got

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their PhDs in this area.
And then everything stopped. It stopped

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working. And there was a
period of about 20 years

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which is known as the AI winter

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where the systems didn't work.

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And then a series of mathematicians
in the 80s and 90s invented what is today

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known as deep learning.
I'll spare you the technical details.

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But the important thing about this deep
learning is it allows the manipulation

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of patterns at scale that allowed these

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algorithms to work.

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And the big breakthrough was in 2011

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with a process called ImageNet

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where there was a contest to see if

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computers could see better than humans.

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And today computers can see better
than humans. Their vision is literally

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better.

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And I didn't realize at the time how

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important sight was for everything.

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A car should be driven by a computer.

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The doctor should use an AI system to

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examine you and then give him
or her recommendations on your care.

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I'd much rather have the computer look

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at my skin rash or my retina in my eye

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because we now know from many many tests

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that humans make observational mistakes,
even the best, but computers when

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properly trained don't.
So it was from this insight

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that you could do vision at scale
that you began to be able to do

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prediction at scale.

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And all of a sudden now we're beginning
to see systems that can predict the next

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thing. And computers have gotten very good
at predicting what will happen next. The

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most recent well there sort of three

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events in the last three years that

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really are the index points. The first
is that and Dr. Kissinger wrote an

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article >> after AlphaGo >>
called the end of history basically

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and inspired by the fact that Go it was a

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game that humans had played
for 2,500 years. It was thought to be

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incomputable. Not only did
a computer solve the game

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but it beat the top humans both in Korea
and China. I know cuz I was physically

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there. Computer against
human and it was great

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fun. But in that process

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the computer invented some new moves
and strategies that had not been known to

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humans for 2,500 years.
Now that's a big deal.

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The next thing that
happened was that at MIT

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a set of synthetic biologists
and computer scientists did a very

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complicated trick involving
going through a hundred

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million different compounds

292
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and figuring out which compounds would

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create a reaction for antibiotic use.

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And they came up with using this
technique a new drug that could not be

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foreseen. It's called Halicin and it
appears to be the next broad scale

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antibiotic. We haven't had one
in roughly 40 years. The third thing that

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happened was that a group
called OpenAI built

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what is are now called

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universal models where they read

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everything they could find on the web

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into something called GPT-3.

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This is called a basically a transformer
and these generative models can generate

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things.

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So, all of a sudden, we have a computer

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that can speak what it knows.

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And these models are interesting because
you train them and you don't know what

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they know. And furthermore,
they can't tell you.

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You have to ask them.
So, it's like a teenager.

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And many people think that these
universal models are going to profoundly

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change our understanding
of language and thought

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because they only get better with scale.

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So, we've now got four or five
companies, couple big ones, couple

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startups that are building what are
called trillion parameter models.

314
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These trillion parameter models cost a

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hundred million dollars or so to make.

316
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That's how exciting this new area is.

317
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So, you've got strategy in the form
of Go, you've got medicine and drug

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discovery, really scientific discovery
in the form of AlphaFold, and now you've

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got language models and learning models
in We believe collectively that in the

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next 10 years, this is going to come
together and transform everything.

321
00:18:29,720 --> 00:18:33,517
>> I'm just taking a breath
to let that settle in.

322
00:18:33,600 --> 00:18:38,237
Uh GPT-3 really got
my attention in part and I

323
00:18:38,320 --> 00:18:39,797
want you to disabuse me of any

324
00:18:39,880 --> 00:18:43,157
misunderstandings, but I saw

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interviews generated between people who

326
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are no longer living. So, I saw Marcus
Aurelius interviewing >> [laughter]

327
00:18:50,760 --> 00:18:53,037
>> Let's just call Mark Twain. Mark Twain

328
00:18:53,120 --> 00:18:55,397
interviewing Abraham Lincoln and I

329
00:18:55,480 --> 00:18:57,997
thought to myself, once we have enough

330
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audio and video online, this will really

331
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simplify my guest recruitment for the
podcast because I won't actually need to

332
00:19:05,120 --> 00:19:08,597
reach out to the living human. It'll be
great. I won't have to keep banging on

333
00:19:08,680 --> 00:19:11,757
the door of Oprah or anyone else. I'll
just be able to generate an interview.

334
00:19:11,840 --> 00:19:14,037
It'll save me recording time, too.

335
00:19:14,120 --> 00:19:17,077
>> You say that in jest,
but we're busy building that.

336
00:19:17,160 --> 00:19:19,917
>> Right. >> And so,
let me just be clear how the Tim

337
00:19:20,000 --> 00:19:22,397
Ferriss Show would work. So, you have an

338
00:19:22,480 --> 00:19:26,917
enormous amount of video and audio data.

339
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So, there's enough to learn to build a

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Tim Ferriss question and answering thing

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where you would have not only your tone

342
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and your the fun that you represent,

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but it would also represent the sum
of your insight. So, it would say, "I was

344
00:19:43,040 --> 00:19:47,477
speaking with so-and-so,
and he or she said this, what do you

345
00:19:47,560 --> 00:19:51,037
think?" Now, in this particular
scenario, this is long after your own

346
00:19:51,120 --> 00:19:54,637
passing and all your guests passing, too.

347
00:19:54,720 --> 00:19:59,797
There's every reason to think
that we'll be able to mimic

348
00:19:59,880 --> 00:20:04,117
your intelligence and charm and wit

349
00:20:04,200 --> 00:20:06,677
and that of your family, your parents,

350
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your grandparents, historical figures.

351
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That will be fun.
The question is, will it really change

352
00:20:14,200 --> 00:20:18,877
society? >> Or how will
it change society? I recall

353
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being in a small meeting,
private meeting, but the content I'm

354
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going to mention is public,

355
00:20:24,400 --> 00:20:27,477
and the discussion centered on the

356
00:20:27,560 --> 00:20:32,117
legal cases that will be forthcoming
related to a lot of this technology, and

357
00:20:32,200 --> 00:20:36,557
there was at the time something related
to Now, I should be clear. I'm I want to

358
00:20:36,640 --> 00:20:39,957
take a backstep in a minute and define
artificial intelligence and what that is

359
00:20:40,040 --> 00:20:42,317
so that it doesn't get
conflated with other things.

360
00:20:42,400 --> 00:20:44,557
But in terms of developing technology,

361
00:20:44,640 --> 00:20:49,757
deep fakes, copyright, defamation,
there's been a lot in the

362
00:20:49,840 --> 00:20:53,437
news, at least in the last few years,
related to deep fakes of Taylor Swift

363
00:20:53,520 --> 00:20:57,677
and lawsuits, and we are
all going to have to contend

364
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with entirely new breeds of legal cases, I

365
00:21:00,920 --> 00:21:03,077
would imagine. So, that's another

366
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uh facet of this that is going to be

367
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incredibly fascinating,
terrifying, and complex, possibly.

368
00:21:10,200 --> 00:21:13,117
I would love for you,
if you if you don't mind, to

369
00:21:13,200 --> 00:21:16,757
just define for me, quite frankly,
artificial intelligence, because as I'm

370
00:21:16,840 --> 00:21:20,277
sure you have seen and can imagine,
there are a lot of terms that kind of

371
00:21:20,360 --> 00:21:23,837
get copied and pasted into startup decks
whenever they're hot. That [laughter]

372
00:21:23,920 --> 00:21:29,317
would be deep learning, machine learning,
AI. What is AI and what is it

373
00:21:29,400 --> 00:21:34,077
not? >> The simplest explanation for AI
is it's a system that gets better through

374
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learning. It is busy learning something.

375
00:21:37,880 --> 00:21:42,317
And that's the probably the easiest
and current definition of it.

376
00:21:42,400 --> 00:21:47,117
When I say AI to my non-technical friends,
they typically think of a movie

377
00:21:47,200 --> 00:21:51,037
that they saw.
And the movie always has a robot, and

378
00:21:51,120 --> 00:21:53,677
the robot goes awry,

379
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and that robot is slain by a female

380
00:21:57,280 --> 00:21:58,837
scientist

381
00:21:58,920 --> 00:22:01,517
who triumphs.

382
00:22:01,600 --> 00:22:04,397
And I propose a variant of that movie

383
00:22:04,480 --> 00:22:07,637
where the computers all conspire against

384
00:22:07,720 --> 00:22:10,077
humans and start killing humans.

385
00:22:10,160 --> 00:22:14,317
The humans notice this,
the computers run away from the humans,

386
00:22:14,400 --> 00:22:19,557
and a female scientist figures out how
to unplug the computers one by one by

387
00:22:19,640 --> 00:22:24,197
one. That's not what AI is. That's a movie

388
00:22:24,280 --> 00:22:27,517
fiction. And it'll be
a very long time, hopefully

389
00:22:27,600 --> 00:22:30,117
never, that we'll have to deal with that.

390
00:22:30,200 --> 00:22:32,997
What AI really is is a system of

391
00:22:33,080 --> 00:22:35,757
knowledge that is implemented inside the

392
00:22:35,840 --> 00:22:38,237
cloud, so it's around you all the time,

393
00:22:38,320 --> 00:22:40,997
and it's very good at looking at large

394
00:22:41,080 --> 00:22:43,197
data sets and predicting things. It's

395
00:22:43,280 --> 00:22:48,157
very good at looking and finding
patterns that humans can't see.

396
00:22:48,240 --> 00:22:52,077
I mentioned earlier that the
computers were very good at vision.

397
00:22:52,160 --> 00:22:54,037
That was the first breakthrough.

398
00:22:54,120 --> 00:22:55,877
But what they're now doing is looking

399
00:22:55,960 --> 00:22:59,037
for patterns of correlation that humans

400
00:22:59,120 --> 00:23:03,637
can't see. So, let's imagine that on
Tuesday you do something and on Friday

401
00:23:03,720 --> 00:23:07,237
someone else does something and it turns
out that you're magically linked in the

402
00:23:07,320 --> 00:23:11,077
universe such that Tuesday causes
Friday, but it's not a pattern that's

403
00:23:11,160 --> 00:23:14,717
apparent. Computers can
discover that pattern,

404
00:23:14,800 --> 00:23:19,197
that needle in a haystack particularly
well. When you operate this stuff at

405
00:23:19,280 --> 00:23:23,357
scale, you end up with systems that look

406
00:23:23,440 --> 00:23:26,717
human-like because they
can aggregate data and they

407
00:23:26,800 --> 00:23:29,837
can think what you think.
They can generate

408
00:23:29,920 --> 00:23:34,037
a solution. There's a technology
called GANs, uh generative adversarial

409
00:23:34,120 --> 00:23:38,677
networks, where the computer can
generate candidates and another network

410
00:23:38,760 --> 00:23:43,277
says not good enough, not good enough,
not good enough until they find it. GANs

411
00:23:43,360 --> 00:23:45,277
have been used for example to build

412
00:23:45,360 --> 00:23:47,597
pictures of actresses and actors that

413
00:23:47,680 --> 00:23:52,637
are fake, but look so real
you're sure you know them.

414
00:23:52,720 --> 00:23:57,117
So one of the concerns, the one
of the real concerns about AI,

415
00:23:57,200 --> 00:24:00,197
is that it's going to be very
difficult to tell the difference between

416
00:24:00,280 --> 00:24:02,637
information and misinformation.

417
00:24:02,720 --> 00:24:04,277
And I'll give you an example. Let's

418
00:24:04,360 --> 00:24:06,957
assume that all of your readers and

419
00:24:07,040 --> 00:24:11,917
listeners are obviously human and that
the standard rules of humans apply to

420
00:24:12,000 --> 00:24:15,197
all of us. There's something called
anchoring bias, there's something called

421
00:24:15,280 --> 00:24:19,637
recency bias. You know, people aren't
completely rational computers nor should

422
00:24:19,720 --> 00:24:22,397
they. We don't want them to be.
We love humans.

423
00:24:22,480 --> 00:24:26,757
But let's imagine the computer gets
enough of such people and it figures out

424
00:24:26,840 --> 00:24:28,717
that if I say the following outrageous

425
00:24:28,800 --> 00:24:32,357
thing first, you'll always believe me.

426
00:24:32,440 --> 00:24:34,277
And the computer discovers this and so

427
00:24:34,360 --> 00:24:36,957
all of a sudden everything it does boom,

428
00:24:37,040 --> 00:24:39,437
boom, boom. I thought a lot about the

429
00:24:39,520 --> 00:24:44,477
way politicians speak. If you watch
carefully, they take a set of phrases

430
00:24:44,560 --> 00:24:48,357
and they repeat them over and over again.
They're simple phrases. That's

431
00:24:48,440 --> 00:24:52,357
anchoring. They're trying to get
the audience, their voters, to start with

432
00:24:52,440 --> 00:24:54,597
this fact and then judge past it. Well,

433
00:24:54,680 --> 00:24:57,597
computers will be incredibly good

434
00:24:57,680 --> 00:25:02,197
at exploiting that.
That means that the world, our social

435
00:25:02,280 --> 00:25:04,597
world around us within the next decade,

436
00:25:04,680 --> 00:25:09,237
will become impossibly confusing
because there's so many actors that will

437
00:25:09,320 --> 00:25:11,477
want to misinform us. Businesses,

438
00:25:11,560 --> 00:25:14,797
politicians, our opponents, for fun, God

439
00:25:14,880 --> 00:25:17,637
knows. We don't know how to manage that.

440
00:25:17,720 --> 00:25:21,677
>> When you mentioned things coming
together in some fashion in the next 10

441
00:25:21,760 --> 00:25:25,877
years, could you speak to

442
00:25:25,960 --> 00:25:28,597
if and how generalized or general

443
00:25:28,680 --> 00:25:31,637
artificial intelligence fits into that?

444
00:25:31,720 --> 00:25:34,077
Because I know that's a big question
for a lot of people, including those who

445
00:25:34,160 --> 00:25:36,157
don't really understand the technology,

446
00:25:36,240 --> 00:25:41,237
when generalized artificial
intelligence will arrive, so to speak.

447
00:25:41,320 --> 00:25:44,517
>> I think it's important
to establish some of these terms.

448
00:25:44,600 --> 00:25:47,557
AGI stands for artificial
general intelligence.

449
00:25:47,640 --> 00:25:50,317
And AGI refers to computers that are

450
00:25:50,400 --> 00:25:51,957
human-like

451
00:25:52,040 --> 00:25:55,797
in their strategic and capability.

452
00:25:55,880 --> 00:26:00,077
Today's algorithms are extraordinarily
good at generating content,

453
00:26:00,160 --> 00:26:03,637
misinformation, guidance,
helping you with science, and

454
00:26:03,720 --> 00:26:07,117
so forth. But they're
not self-determinative.

455
00:26:07,200 --> 00:26:08,997
They don't actually have the notion of

456
00:26:09,080 --> 00:26:11,277
who am I and what do I do next? If you

457
00:26:11,360 --> 00:26:15,477
ask GPT-3 who it is, GPT-3 will say,

458
00:26:15,560 --> 00:26:20,757
"I'm a computer."
But it won't give you a philosophical

459
00:26:20,840 --> 00:26:24,477
basis for its existence,
its purpose, and how

460
00:26:24,560 --> 00:26:27,197
it's determining where it goes.

461
00:26:27,280 --> 00:26:29,877
That is the distinction between AI and

462
00:26:29,960 --> 00:26:32,317
AGI, in my view.

463
00:26:32,400 --> 00:26:35,757
Now, within the community, the AGI

464
00:26:35,840 --> 00:26:38,637
optimists think that within 10 years we

465
00:26:38,720 --> 00:26:41,117
will have such computers. The pessimists

466
00:26:41,200 --> 00:26:42,877
think that it will be far longer if

467
00:26:42,960 --> 00:26:46,717
ever. So, let's say 15 years from now,

468
00:26:46,800 --> 00:26:52,277
it may be possible to have computers
that have a sense of self-determination,

469
00:26:52,360 --> 00:26:56,357
that they know roughly what they're
trying to achieve against a broader

470
00:26:56,440 --> 00:26:58,117
objective.

471
00:26:58,200 --> 00:27:00,997
Many people think that this will become

472
00:27:01,080 --> 00:27:04,357
an enormous competition between humans.

473
00:27:04,440 --> 00:27:08,957
Because remember that those computers
will be faster learners than humans.

474
00:27:09,040 --> 00:27:11,877
They'll have access
to more data than humans.

475
00:27:11,960 --> 00:27:15,157
Other people believe that they'll
be fundamentally flawed.

476
00:27:15,240 --> 00:27:18,597
Because they won't have the nuance,
they won't have the background, they won't

477
00:27:18,680 --> 00:27:21,917
have the cultural background of the
countries that we all grew up in and the

478
00:27:22,000 --> 00:27:24,957
cultures we grow in. We don't really know.

479
00:27:25,040 --> 00:27:28,597
My own view is that this will occur.

480
00:27:28,680 --> 00:27:31,077
But that the amount of computation

481
00:27:31,160 --> 00:27:33,837
required to do this will be so great

482
00:27:33,920 --> 00:27:36,677
that there'll only be a few of them.

483
00:27:36,760 --> 00:27:40,197
And furthermore,
they'll become so important

484
00:27:40,280 --> 00:27:43,037
that they'll be like nuclear weapons.

485
00:27:43,120 --> 00:27:46,397
And let me tell you why.
Let's imagine you have a truly evil

486
00:27:46,480 --> 00:27:49,037
person who encounters this AGI. What's

487
00:27:49,120 --> 00:27:50,837
the first question they'll ask them?

488
00:27:50,920 --> 00:27:54,197
Tell me how to kill a million people.

489
00:27:54,280 --> 00:27:57,157
Obviously a terrible
thing to ask and answer.

490
00:27:57,240 --> 00:28:02,157
And the AGI, because it doesn't
have morals, could actually answer.

491
00:28:02,240 --> 00:28:05,917
It could actually say, well, do this,
this, this, and this. And furthermore,

492
00:28:06,000 --> 00:28:09,077
it could articulate something that's
not generally known because it knows

493
00:28:09,160 --> 00:28:11,277
everything.

494
00:28:11,360 --> 00:28:14,557
So I think a fair reading of these AGIs

495
00:28:14,640 --> 00:28:19,197
is that in the most extreme form,
they're going to be so powerful

496
00:28:19,280 --> 00:28:21,997
that they're going
to have to be protected.

497
00:28:22,080 --> 00:28:25,757
We don't want them broadly used. They're
going to have to be used in specialized

498
00:28:25,840 --> 00:28:29,277
scenarios. Now,
such an intelligence will be

499
00:28:29,360 --> 00:28:33,837
enormously valuable for drug
discovery, material science,

500
00:28:33,920 --> 00:28:36,197
climate change, making the world more

501
00:28:36,280 --> 00:28:38,997
efficient, making people more educated.

502
00:28:39,080 --> 00:28:43,957
And imagine with an AGI, you could say,
"Tell me how to teach a million children

503
00:28:44,040 --> 00:28:47,157
English better."
And he could figure that out.

504
00:28:47,240 --> 00:28:51,717
Cuz it could in its own thinking to the
greatest thinking, it could look at all

505
00:28:51,800 --> 00:28:55,197
the patterns, figure out how to do it,
and you could actually ask it to write

506
00:28:55,280 --> 00:28:57,397
the program.

507
00:28:57,480 --> 00:29:00,437
The beginning of this is today there are

508
00:29:00,520 --> 00:29:05,157
companies that are offering tools
which will help you write code.

509
00:29:05,240 --> 00:29:08,677
They don't know what code you're trying
to write, but once you start, it can

510
00:29:08,760 --> 00:29:11,357
fill in a bunch of it for you.

511
00:29:11,440 --> 00:29:14,557
That's the beginning of this phenomena.

512
00:29:14,640 --> 00:29:18,677
In the extreme case, there
are scientists and basically

513
00:29:18,760 --> 00:29:22,877
science fiction around the future
that could use something called

514
00:29:22,960 --> 00:29:26,797
the singularity, which
is the point where the computer

515
00:29:26,880 --> 00:29:29,237
evolution is so much faster than humans.

516
00:29:29,320 --> 00:29:33,757
Now, that's speculation.
When you talk to people in my world,

517
00:29:33,840 --> 00:29:37,757
most people think the singularity will
occur 20 years from whenever you ask

518
00:29:37,840 --> 00:29:44,760
them that question.
>> [laughter] >> So, they would say 2041.

519
00:29:45,160 --> 00:29:50,037
>> Where do you fall, if I may ask your
personal opinion, assuming, and this is

520
00:29:50,120 --> 00:29:53,637
a big assumption, that there are people
on the techno-optimist and pessimist

521
00:29:53,720 --> 00:29:54,997
side who are very technically

522
00:29:55,080 --> 00:29:56,957
sophisticated?

523
00:29:57,040 --> 00:30:00,757
What is your current best guess or

524
00:30:00,840 --> 00:30:04,597
intuitive feel, however you want
to answer it, on the arrival of something

525
00:30:04,680 --> 00:30:08,677
we would consider AGI?
>> The top scientists, the greatest

526
00:30:08,760 --> 00:30:10,797
inventors in this area,

527
00:30:10,880 --> 00:30:13,157
collectively believe that we need one or

528
00:30:13,240 --> 00:30:15,877
two more breakthroughs

529
00:30:15,960 --> 00:30:18,597
to get to volition,

530
00:30:18,680 --> 00:30:22,917
to get to consciousness in the way
that humans do it. When you wake up in the

531
00:30:23,000 --> 00:30:27,157
morning, you have so many choices of how
to spend your time. How do you choose?

532
00:30:27,240 --> 00:30:29,677
How do you handle unplanned situations

533
00:30:29,760 --> 00:30:31,917
and all of that? Most people believe

534
00:30:32,000 --> 00:30:34,477
that the computers that I'm talking

535
00:30:34,560 --> 00:30:38,077
about will become enormously valuable

536
00:30:38,160 --> 00:30:42,277
partners. My physicist friend, I said
to him, "What would you like the computer

537
00:30:42,360 --> 00:30:45,037
to do?" And he says, "It's really simple.

538
00:30:45,120 --> 00:30:49,597
There are so much physics being written
about now that I don't have time to read

539
00:30:49,680 --> 00:30:50,677
it all.

540
00:30:50,760 --> 00:30:53,957
And I want the physics assistant

541
00:30:54,040 --> 00:30:56,757
to go and read everything, figure out

542
00:30:56,840 --> 00:31:01,277
what disagrees with each other,
suggest things for me to think about

543
00:31:01,360 --> 00:31:03,117
while I'm sleeping."

544
00:31:03,200 --> 00:31:06,317
The biologists have similar questions.

545
00:31:06,400 --> 00:31:10,957
People who are philosophers want new
insights. Read everything. Help me think

546
00:31:11,040 --> 00:31:14,317
through this. I believe
that in the next decade that

547
00:31:14,400 --> 00:31:17,837
will be the primary achievement in AI.

548
00:31:17,920 --> 00:31:19,957
And that is extraordinary.

549
00:31:20,040 --> 00:31:22,077
Because it means, for example, that we

550
00:31:22,160 --> 00:31:26,997
can answer questions in physics, math,
medicine, so forth, that have been

551
00:31:27,080 --> 00:31:30,157
unanswerable. We've not
been able to understand the

552
00:31:30,240 --> 00:31:34,757
behavior of subatomic particles.
We can do it now.

553
00:31:34,840 --> 00:31:39,437
The enormous breakthroughs, but that's
not the same thing as real human

554
00:31:39,520 --> 00:31:43,197
intelligence. I think it's going
to take another breakthrough or two.

555
00:31:43,280 --> 00:31:47,077
>> I know this is maybe trying
to look into the crystal ball with too

556
00:31:47,160 --> 00:31:51,717
much intensity, but could you elaborate
on if those breakthroughs are known,

557
00:31:51,800 --> 00:31:55,077
what they are, what like what the problems
are that need to be solved? Are

558
00:31:55,160 --> 00:31:57,957
Are they known problems? >> There
are people who are working really

559
00:31:58,040 --> 00:32:01,637
hard on the question of goals.

560
00:32:01,720 --> 00:32:06,477
And the computer systems have

561
00:32:06,560 --> 00:32:09,437
knowledge that they cannot explain,

562
00:32:09,520 --> 00:32:11,957
which we can think of as intuition.

563
00:32:12,040 --> 00:32:14,517
So, the system gets trained and it knows

564
00:32:14,600 --> 00:32:19,237
things, but if you ask it why it knows it,
it can't tell you. That's intuition.

565
00:32:19,320 --> 00:32:22,957
So, the question here is how much
more computational power and scenario

566
00:32:23,040 --> 00:32:26,877
planning do you have to do to look
at all the different choices that you have

567
00:32:26,960 --> 00:32:31,117
every day? There are
people who believe that it's

568
00:32:31,200 --> 00:32:34,317
perhaps a hundred times
more computing power.

569
00:32:34,400 --> 00:32:37,277
And computing power goes up, it doubles

570
00:32:37,360 --> 00:32:41,477
every 2 to 3 years right now.
And so, that gives you a sense that

571
00:32:41,560 --> 00:32:46,197
within 15 years it's possible
to imagine that amount of

572
00:32:46,280 --> 00:32:49,797
computing power required to do this.

573
00:32:49,880 --> 00:32:53,357
And the reason we use computing power
is one, we don't have a better metric, but

574
00:32:53,440 --> 00:32:56,117
also because the computer doesn't think

575
00:32:56,200 --> 00:33:00,397
the way humans do. The computer looks
at scenarios and eliminates. So, it says,

576
00:33:00,480 --> 00:33:02,157
"Well, what if this? And what if this?

577
00:33:02,240 --> 00:33:06,357
And what if this?"
And the computer itself is eliminating

578
00:33:06,440 --> 00:33:09,997
this choice, this choice, this choice,
this choice, and finally settles on a

579
00:33:10,080 --> 00:33:13,157
good choice. So,
many people believe that the

580
00:33:13,240 --> 00:33:17,917
compounding of knowledge will
take what we say a couple of orders

581
00:33:18,000 --> 00:33:21,557
of more magnitude.
Which is why these computers are likely

582
00:33:21,640 --> 00:33:24,597
at least initially to be few, extremely

583
00:33:24,680 --> 00:33:28,117
expensive, and very, very large.

584
00:33:28,200 --> 00:33:30,357
>> Does the 15-year

585
00:33:30,440 --> 00:33:33,077
hypothetical time horizon

586
00:33:33,160 --> 00:33:35,997
factor in, and And this is me getting

587
00:33:36,080 --> 00:33:40,717
into very slippery territory since I'm
non-technical, but does that factor in

588
00:33:40,800 --> 00:33:43,637
the potential applications
of quantum computing?

589
00:33:43,720 --> 00:33:47,037
>> For at least 20 years, people have been
focusing on this notion of a different

590
00:33:47,120 --> 00:33:49,957
kind of computer called
a quantum computer.

591
00:33:50,040 --> 00:33:54,357
And quantum computers are hard to explain,
but basically think of them as

592
00:33:54,440 --> 00:33:57,237
they do all the computations
at the same time.

593
00:33:57,320 --> 00:34:00,517
So, instead of going ka-chunk, ka-chunk,
ka-chunk, all the ka-chunks go at the

594
00:34:00,600 --> 00:34:02,077
same time.

595
00:34:02,160 --> 00:34:04,917
And the term quantum supremacy means

596
00:34:05,000 --> 00:34:10,437
that everything occurs at once,
rather than taking the computer time to

597
00:34:10,520 --> 00:34:13,317
go through each of the
mathematical calculations.

598
00:34:13,400 --> 00:34:17,437
The reason that this is of such great
interest is that one of the core aspects

599
00:34:17,520 --> 00:34:21,877
of security in the computer age
is the difference between multiplication

600
00:34:21,960 --> 00:34:25,357
and division.
And with quantum computers, you could

601
00:34:25,440 --> 00:34:27,917
break all of the codes and all of the

602
00:34:28,000 --> 00:34:30,117
secrets and all of the keys and all of

603
00:34:30,200 --> 00:34:33,117
that that we all use every day.

604
00:34:33,200 --> 00:34:37,437
So, a lot of people think that national
security groups are busy working hard to

605
00:34:37,520 --> 00:34:42,237
do that. The consensus in the industry
is that we are 8 to 10 years away from

606
00:34:42,320 --> 00:34:45,597
that. And the way they
get there is that the

607
00:34:45,680 --> 00:34:49,157
current quantum computers
have an error rate

608
00:34:49,240 --> 00:34:51,317
because it's not perfect when they

609
00:34:51,400 --> 00:34:56,837
operate. They're essentially
mimicking a natural process digitally.

610
00:34:56,920 --> 00:35:00,557
And Google showed last
year that they could

611
00:35:00,640 --> 00:35:04,557
do this on a computer that would have
taken a million years that took roughly

612
00:35:04,640 --> 00:35:09,037
10 seconds because of it.
So, we we know it's possible.

613
00:35:09,120 --> 00:35:12,877
The question now is how do you
actually build a real one that's useful?

614
00:35:12,960 --> 00:35:15,317
If you had a real one, you could instead

615
00:35:15,400 --> 00:35:18,117
of simulating a physical process, the

616
00:35:18,200 --> 00:35:20,517
typical one is called annealing where

617
00:35:20,600 --> 00:35:23,277
two metals basically merge, and this is

618
00:35:23,360 --> 00:35:28,117
crucial for high-strength steel and
titanium and things like this. And is of

619
00:35:28,200 --> 00:35:31,837
great business interest.
But the same thing would apply to AI if

620
00:35:31,920 --> 00:35:35,757
it worked because the algorithm,
instead of looking at all these different

621
00:35:35,840 --> 00:35:38,877
scenarios, would examine them all
at the same time and pick the best one.

622
00:35:38,960 --> 00:35:41,637
Technically, the one
with the lowest energy state.

623
00:35:41,720 --> 00:35:46,677
The current quantum learning
is not proceeding very quickly.

624
00:35:46,760 --> 00:35:50,437
It's a very hard problem.
My assumption is that quantum learning

625
00:35:50,520 --> 00:35:54,357
will occur in our lifetimes,
but not very soon.

626
00:35:54,440 --> 00:35:59,237
>> Thank you. And uh for people listening,
you want to do a a real deep dive on

627
00:35:59,320 --> 00:36:01,117
quantum learning and quantum computing.

628
00:36:01,200 --> 00:36:04,957
I have a conversation with Steve
Jurvetson that goes very

629
00:36:05,040 --> 00:36:06,677
deeply into this subject matter, and it

630
00:36:06,760 --> 00:36:09,477
really does start to be a mind bender

631
00:36:09,560 --> 00:36:15,640
when you get into the details.
It is quite something.

632
00:36:16,840 --> 00:36:19,477
Just a quick thanks to one of our
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I want to ask you, you mentioned
what you philosophers might ask for in

657
00:37:54,240 --> 00:37:58,157
terms of augmentation or help. You
mentioned the biologist, the physicist.

658
00:37:58,240 --> 00:38:01,157
I am going to ask you,
I'm just planting a seed,

659
00:38:01,240 --> 00:38:05,037
what Eric Schmidt might use AI

660
00:38:05,120 --> 00:38:07,997
technology for in the future. But before

661
00:38:08,080 --> 00:38:11,117
I get there, I want to just look at a

662
00:38:11,200 --> 00:38:15,077
snapshot of current day. What are

663
00:38:15,160 --> 00:38:19,757
some of the coolest or most impressive
things that you've seen AI figure out on

664
00:38:19,840 --> 00:38:21,117
its own?

665
00:38:21,200 --> 00:38:24,517
>> I mentioned this new drug and

666
00:38:24,600 --> 00:38:27,837
the new drug and drug discovery will

667
00:38:27,920 --> 00:38:32,597
accelerate combination
of the mRNA achievements

668
00:38:32,680 --> 00:38:37,997
plus the ability now to essentially
replace the way the drug lab works.

669
00:38:38,080 --> 00:38:41,197
My sort of stereotype is the chemist
wakes up in the morning and says, "Let's

670
00:38:41,280 --> 00:38:43,557
try the following seven compounds." They

671
00:38:43,640 --> 00:38:45,837
try the seven compounds, none of them

672
00:38:45,920 --> 00:38:51,037
work, and at 5:00 they go home to have
dinner and think, watch television, and

673
00:38:51,120 --> 00:38:53,437
the next morning they
think of another seven.

674
00:38:53,520 --> 00:38:57,037
Well, the computer can do,
as I mentioned, 100 million

675
00:38:57,120 --> 00:39:00,637
in a day. That's a huge
accelerant in what they're

676
00:39:00,720 --> 00:39:04,877
doing. I'm very interested
in the development

677
00:39:04,960 --> 00:39:07,077
of humans

678
00:39:07,160 --> 00:39:12,037
together with AI systems.
And the example I would offer is you

679
00:39:12,120 --> 00:39:16,197
have a 2-year-old and the
2-year-old gets a plush toy.

680
00:39:16,280 --> 00:39:18,837
It happens to have AI inside of it.

681
00:39:18,920 --> 00:39:21,437
And by agreement as this child ages

682
00:39:21,520 --> 00:39:23,677
every year, they get a better toy.

683
00:39:23,760 --> 00:39:27,277
And of course, the toy gets smarter.

684
00:39:27,360 --> 00:39:29,917
We don't know at all

685
00:39:30,000 --> 00:39:32,837
what happens when a child's best friend

686
00:39:32,920 --> 00:39:37,037
is not a human or a dog.

687
00:39:37,120 --> 00:39:41,597
We don't know what that does
to the child's bonding to

688
00:39:41,680 --> 00:39:44,917
other children, to their parents.

689
00:39:45,000 --> 00:39:48,317
I mean, you know frustrated parents
and the kid is busy and they give them a

690
00:39:48,400 --> 00:39:51,237
computer and do whatever you want.

691
00:39:51,320 --> 00:39:53,357
But imagine if that computer is

692
00:39:53,440 --> 00:39:56,317
learning, talking, thinking,

693
00:39:56,400 --> 00:40:01,357
educating at the same time.
It's a godsend, right?

694
00:40:01,440 --> 00:40:03,597
But what is it teaching? >> Yeah.

695
00:40:03,680 --> 00:40:05,517
>> What is it teaching?
What are its norms?

696
00:40:05,600 --> 00:40:10,157
What are its values? Will such a child
end up being very stilted with real

697
00:40:10,240 --> 00:40:13,437
humans and really
comfortable with digital?

698
00:40:13,520 --> 00:40:18,037
We honestly just don't know.
We know that people get attached to

699
00:40:18,120 --> 00:40:23,157
inanimate objects. There are many
religions where inanimate objects have

700
00:40:23,240 --> 00:40:26,437
what we would think of as a bit of a soul.

701
00:40:26,520 --> 00:40:28,517
We mentioned this in the book.

702
00:40:28,600 --> 00:40:32,237
But we don't know. I'll give you
another example with elderly. Uh a lot of

703
00:40:32,320 --> 00:40:35,077
studies indicate that the
elderly are very lonely.

704
00:40:35,160 --> 00:40:38,117
It's sort of sad. And

705
00:40:38,200 --> 00:40:42,637
imagine if their best
friend is a digital friend.

706
00:40:42,720 --> 00:40:47,717
What does that do? Does that extend
their lives? Does it make them crankier?

707
00:40:47,800 --> 00:40:51,877
Does it make their loneliness more
perverse? I don't think we know yet.

708
00:40:51,960 --> 00:40:56,597
>> Yeah, or is that digital
friend an emulation of a relative?

709
00:40:56,680 --> 00:40:58,837
>> That's right. So now we get our

710
00:40:58,920 --> 00:41:00,757
grandmother as an example and we

711
00:41:00,840 --> 00:41:03,917
recreate her husband. And what does it

712
00:41:04,000 --> 00:41:08,397
do when she can chat with her
husband who's now passed away?

713
00:41:08,480 --> 00:41:12,397
We honestly don't know.
When I go through and I look at these

714
00:41:12,480 --> 00:41:14,477
technologies, there really four

715
00:41:14,560 --> 00:41:17,477
qualities in AI that are different.

716
00:41:17,560 --> 00:41:22,277
The first is it's imprecise.
It's imprecise in that it can't tell you

717
00:41:22,360 --> 00:41:26,917
exactly what it's doing and it makes
mistakes. Don't use it for life-critical

718
00:41:27,000 --> 00:41:31,757
decisions. You want a human
who can make mistakes

719
00:41:31,840 --> 00:41:35,997
consulting a computer. You don't want
the computer flying the airplane. And

720
00:41:36,080 --> 00:41:37,517
maybe never, but certainly not for a

721
00:41:37,600 --> 00:41:40,557
long time. It's dynamic in the sense

722
00:41:40,640 --> 00:41:43,277
that it's changing. It can learn. It can

723
00:41:43,360 --> 00:41:48,237
assess the situation around it
and change its behavior. This is the AI

724
00:41:48,320 --> 00:41:51,677
now. It has emergent behavior.

725
00:41:51,760 --> 00:41:56,637
Emergent means things that come
out that we don't expect.

726
00:41:56,720 --> 00:42:00,317
Strange things. Now, we've seen
this a bit with social media.

727
00:42:00,400 --> 00:42:03,597
I don't think anyone expected the
government interference in the elections

728
00:42:03,680 --> 00:42:06,117
in 2016. That was an emergent behavior.

729
00:42:06,200 --> 00:42:10,157
It was unexpected by humanity
using these tools. And those

730
00:42:10,240 --> 00:42:14,237
were not AI-powered.
The final point is it's capable of

731
00:42:14,320 --> 00:42:18,557
learning. So, you've got
a system using the child

732
00:42:18,640 --> 00:42:22,437
scenario. You've got a a child that's
got a teddy bear that looks like a teddy

733
00:42:22,520 --> 00:42:26,197
bear, but it's imprecise, dynamic,
emergent, and capable of learning.

734
00:42:26,280 --> 00:42:28,277
What's the teddy bear learning?

735
00:42:28,360 --> 00:42:30,717
So, the teddy bear's watching TV, too.

736
00:42:30,800 --> 00:42:34,557
And the teddy bear says, "Look, I think
this show sucks." And the kid says, "I

737
00:42:34,640 --> 00:42:38,277
agree with you." >> [laughter]

738
00:42:38,360 --> 00:42:43,277
>> Again, we don't understand
the implication, especially on formative

739
00:42:43,360 --> 00:42:46,637
behaviors. There's a whole
'nother set of arguments

740
00:42:46,720 --> 00:42:50,397
about national security and how
governments will work and how dominance

741
00:42:50,480 --> 00:42:53,917
games will play and who will be winners
and losers from this technology that we

742
00:42:54,000 --> 00:42:56,437
don't really understand.
And we talk about that.

743
00:42:56,520 --> 00:43:01,117
>> Well, let's actually touch
on that for a second. And

744
00:43:01,200 --> 00:43:03,837
this is something on the minds of a lot
of folks. Certainly, I know a lot of

745
00:43:03,920 --> 00:43:07,917
investors who are trying to understand

746
00:43:08,000 --> 00:43:10,837
AI in the capacity of acting as an

747
00:43:10,920 --> 00:43:13,277
investor. I'm not saying we go there,

748
00:43:13,360 --> 00:43:16,877
but you have spoken to Congress about,

749
00:43:16,960 --> 00:43:19,717
say, China's announced ambitions with

750
00:43:19,800 --> 00:43:21,437
AI.

751
00:43:21,520 --> 00:43:24,317
10 to 15 years isn't that far away. It's

752
00:43:24,400 --> 00:43:27,717
really close, and certain things

753
00:43:27,800 --> 00:43:31,477
move very slowly. Certain facets of,
say, government move quite slowly,

754
00:43:31,560 --> 00:43:33,397
regulation.

755
00:43:33,480 --> 00:43:36,237
What types of corners are most important

756
00:43:36,320 --> 00:43:40,477
to look around? And I'd love to hear
you speak a little bit more about the

757
00:43:40,560 --> 00:43:44,237
geopolitical components. >> I
was fortunate to be the chairman of an

758
00:43:44,320 --> 00:43:48,597
AI commission for Congress. We just
released our report, very proud of it.

759
00:43:48,680 --> 00:43:53,477
And we studied a lot about where the world
is in AI, not so much on these AGI

760
00:43:53,560 --> 00:43:57,757
questions, but the the more tactical
things that I've been discussing.

761
00:43:57,840 --> 00:44:02,277
We concluded that the United
States is slightly ahead of China

762
00:44:02,360 --> 00:44:06,557
in these areas. That China has
a national program to focus on this.

763
00:44:06,640 --> 00:44:10,997
They're pouring literally billions
and billions of dollar equivalents into

764
00:44:11,080 --> 00:44:15,477
this. They generate four times more
engineers than as we do just because of

765
00:44:15,560 --> 00:44:17,917
population size, and they're extremely

766
00:44:18,000 --> 00:44:21,317
focused on dominance of AI by 2030,

767
00:44:21,400 --> 00:44:24,237
which is soon. In our report, we speak a

768
00:44:24,320 --> 00:44:28,477
great deal about what the government
needs to do to help. It starts with more

769
00:44:28,560 --> 00:44:31,517
research, access to more
data, making sure our

770
00:44:31,600 --> 00:44:35,517
values are represented so we don't end
up with systems that have a prejudice

771
00:44:35,600 --> 00:44:39,477
and so forth and violate both our laws
as well as our morals. We talk about

772
00:44:39,560 --> 00:44:44,397
partnerships and all of this kind
of stuff. The reason this is so important

773
00:44:44,480 --> 00:44:48,197
is that pretty much every national
security issue will be tainted or

774
00:44:48,280 --> 00:44:53,277
controlled by AI in the future.
If you look think about cyber attacks,

775
00:44:53,360 --> 00:44:56,917
the most obvious war
scenario in the future is the

776
00:44:57,000 --> 00:45:01,157
following. North Korea decides
to attack the United States.

777
00:45:01,240 --> 00:45:05,637
It begins its attack.
China decides this is a bad idea

778
00:45:05,720 --> 00:45:07,917
and blocks the attack.

779
00:45:08,000 --> 00:45:11,357
America's defenses are awake, alert.

780
00:45:11,440 --> 00:45:14,637
America announces
a counterattack which stops this.

781
00:45:14,720 --> 00:45:16,917
The entire war

782
00:45:17,000 --> 00:45:22,400
that I just described
took about 10 milliseconds.

783
00:45:22,800 --> 00:45:26,837
Give you another example. In the military,
there's a presumption of human

784
00:45:26,920 --> 00:45:29,557
control, which is very important.

785
00:45:29,640 --> 00:45:33,877
I was part of a team that wrote some
of the AI ethics that are now used by the

786
00:45:33,960 --> 00:45:37,757
US military. Which I just
obviously strongly support.

787
00:45:37,840 --> 00:45:39,637
And they say we want the principle of

788
00:45:39,720 --> 00:45:43,037
human control, human authorization.

789
00:45:43,120 --> 00:45:45,037
So, let me give you an example.

790
00:45:45,120 --> 00:45:48,837
You're on a ship and a new
kind of missile, let's say a

791
00:45:48,920 --> 00:45:53,237
very fast hypersonic missile,
is coming in, which people are developing.

792
00:45:53,320 --> 00:45:56,517
Countries are. And it's
coming in so fast that the ship

793
00:45:56,600 --> 00:45:58,597
can't see it, the humans can't see it,

794
00:45:58,680 --> 00:46:00,837
but the AI has figured it out.

795
00:46:00,920 --> 00:46:04,957
So, the AI says to the commander,

796
00:46:05,040 --> 00:46:08,117
"In 15 seconds, a missile is going to be

797
00:46:08,200 --> 00:46:12,997
showing up and it's going to destroy you
and your entire crew. I recommend that

798
00:46:13,080 --> 00:46:16,957
you press this button
to launch the counterattack."

799
00:46:17,040 --> 00:46:18,677
And the human says,

800
00:46:18,760 --> 00:46:22,157
"14, 13, 12, 10,

801
00:46:22,240 --> 00:46:25,077
what do I do?" And at 3 seconds, that

802
00:46:25,160 --> 00:46:28,237
human's going to press that button.

803
00:46:28,320 --> 00:46:31,277
So, the compression of time, the amount

804
00:46:31,360 --> 00:46:35,397
of data, and the potential for error

805
00:46:35,480 --> 00:46:38,117
creates a whole set of problems around

806
00:46:38,200 --> 00:46:40,837
military doctrine.

807
00:46:40,920 --> 00:46:46,197
Now, everything that we live in today,
deterrence, all of the other things that

808
00:46:46,280 --> 00:46:49,677
we are all of us are familiar
with, great power competition,

809
00:46:49,760 --> 00:46:53,237
are concepts that were invented
over the last 100 years ago.

810
00:46:53,320 --> 00:46:57,797
And Dr. Kissinger actually invented much
of the containment strategy in the '50s

811
00:46:57,880 --> 00:47:02,797
and '60s before he was in government
as part of a team that sort of invented

812
00:47:02,880 --> 00:47:06,197
all this work. So, I asked
him, "What does this look

813
00:47:06,280 --> 00:47:10,717
like now? How would you address this now?"

814
00:47:10,800 --> 00:47:15,237
And his answer is, "Let's get
an equivalent team of people and try to

815
00:47:15,320 --> 00:47:20,077
figure these things out."
Containment, for example, doesn't work.

816
00:47:20,160 --> 00:47:23,917
Containment is about keeping another
country from getting something

817
00:47:24,000 --> 00:47:25,917
because these algorithms and this

818
00:47:26,000 --> 00:47:31,237
software is pervasive.
It leaks and it leaks through ideas and

819
00:47:31,320 --> 00:47:34,237
through discovery,
not just from criminal leaking.

820
00:47:34,320 --> 00:47:38,557
It's not like Los Alamos
where you could keep a secret.

821
00:47:38,640 --> 00:47:41,237
So, the way to maintain competitive

822
00:47:41,320 --> 00:47:45,757
dominance, that is national security,
is to invest in these areas, both in

823
00:47:45,840 --> 00:47:49,077
terms of data and algorithms,
and to be excellent,

824
00:47:49,160 --> 00:47:53,557
but also to begin some kind of dialogue

825
00:47:53,640 --> 00:47:57,637
about what the limitations
of automatic war are.

826
00:47:57,720 --> 00:47:59,877
So, another example, and I'll make one

827
00:47:59,960 --> 00:48:02,477
up now. So, the scenario I described of

828
00:48:02,560 --> 00:48:06,317
the 10 millisecond war

829
00:48:06,400 --> 00:48:09,477
So, let's say that China in this case

830
00:48:09,560 --> 00:48:13,517
develops an AGI ahead of everyone else.

831
00:48:13,600 --> 00:48:16,917
And this AGI is thought to be so powerful

832
00:48:17,000 --> 00:48:20,957
that it could defeat any of our defenses.

833
00:48:21,040 --> 00:48:25,397
Then, the logic on the American side
would be to do a preemptive attack to

834
00:48:25,480 --> 00:48:29,597
prevent that possibility.
And that's destabilizing of great power

835
00:48:29,680 --> 00:48:31,197
competition.

836
00:48:31,280 --> 00:48:35,037
So, you want to avoid an arms race.

837
00:48:35,120 --> 00:48:39,877
An arms race in AI could look a lot like
the arms race that we went through in

838
00:48:39,960 --> 00:48:44,117
the '50s and '60s.
And people have forgotten how much of

839
00:48:44,200 --> 00:48:46,837
our military-industrial complex, how

840
00:48:46,920 --> 00:48:51,917
much money and so forth, was devoted
to build more than 30,000 nuclear weapons,

841
00:48:52,000 --> 00:48:56,237
all of which could destroy the world many,
many times over. Many, many rounds

842
00:48:56,320 --> 00:49:00,557
of negotiation got those numbers down
to 3,000, 4,000 such weapons, which are

843
00:49:00,640 --> 00:49:05,037
still plenty to destroy everything.
It's an example of overreach.

844
00:49:05,120 --> 00:49:07,117
And so, I worry that because we don't

845
00:49:07,200 --> 00:49:11,037
have an agreement on even what the rules

846
00:49:11,120 --> 00:49:14,517
are, what the landscape
of limitations are,

847
00:49:14,600 --> 00:49:18,757
we don't have diplomats who
can have the conversations.

848
00:49:18,840 --> 00:49:24,037
And no single national security group,
no single country is going to self-limit

849
00:49:24,120 --> 00:49:26,957
and say, "Oh, we're not going to do that."
This is not Costa Rica, which

850
00:49:27,040 --> 00:49:28,917
doesn't have a military.

851
00:49:29,000 --> 00:49:32,157
So, the natural course of logic will be

852
00:49:32,240 --> 00:49:34,957
the development of these incredibly fast

853
00:49:35,040 --> 00:49:37,357
and potentially destabilizing weapons,

854
00:49:37,440 --> 00:49:40,197
for which we don't have a language.

855
00:49:40,280 --> 00:49:44,077
>> I think I'll just act
as a stand-in for listeners.

856
00:49:44,160 --> 00:49:47,677
That sounds very terrifying. It does sound

857
00:49:47,760 --> 00:49:50,517
not just terrifying, but challenging to

858
00:49:50,600 --> 00:49:54,277
address. And I I may come back to that

859
00:49:54,360 --> 00:49:58,437
and questions of policy and geopolitics.

860
00:49:58,520 --> 00:50:02,677
I want to ask you the personal question
that I alluded to earlier before I let

861
00:50:02,760 --> 00:50:04,757
that go, which is

862
00:50:04,840 --> 00:50:09,917
what could you achieve or what would
you want to achieve or ask of AI

863
00:50:10,000 --> 00:50:11,717
in the future that would allow you to do

864
00:50:11,800 --> 00:50:14,157
things you cannot do today?

865
00:50:14,240 --> 00:50:19,277
>> Almost every hard
problem in our society

866
00:50:19,360 --> 00:50:23,077
is based on either
the computers can't figure it

867
00:50:23,160 --> 00:50:25,597
out, we don't have enough data,

868
00:50:25,680 --> 00:50:28,397
we honestly don't know how to solve it.

869
00:50:28,480 --> 00:50:33,037
I'd like to get some breakthroughs.
So, I'd like for example to get better

870
00:50:33,120 --> 00:50:36,877
climate models.
In my philanthropy, I funded a group at

871
00:50:36,960 --> 00:50:38,357
Caltech

872
00:50:38,440 --> 00:50:40,477
which figured out a way to predict

873
00:50:40,560 --> 00:50:44,037
climate better using an AI system that

874
00:50:44,120 --> 00:50:48,077
would model clouds. I didn't know this,
but it turns out clouds are really

875
00:50:48,160 --> 00:50:51,277
complicated. And so,
they used an AI system to

876
00:50:51,360 --> 00:50:55,277
approximate how clouds
would behave, which allowed

877
00:50:55,360 --> 00:50:57,997
them to solve the prediction problem.

878
00:50:58,080 --> 00:51:03,317
It's called Clima, c l i m a. Over
and over again, I would like the AI system

879
00:51:03,400 --> 00:51:07,837
to educate me and entertain me

880
00:51:07,920 --> 00:51:12,237
and keep me curious about
the dynamism of the world.

881
00:51:12,320 --> 00:51:16,117
Speaking personally, when I
look at the news feeds, we're

882
00:51:16,200 --> 00:51:20,477
obsessed about politics
and President Trump and so forth,

883
00:51:20,560 --> 00:51:24,637
to the point where you get the impression
that there's nothing else going on.

884
00:51:24,720 --> 00:51:28,477
But one of the great things about
humanity and our world is it's

885
00:51:28,560 --> 00:51:32,477
incredibly dynamic. We never
hear what those people are doing.

886
00:51:32,560 --> 00:51:36,757
I'd like to see if we could figure out
a way to advance against these really hard

887
00:51:36,840 --> 00:51:40,077
problems. Let's get some solutions
around mental health. Let's get some

888
00:51:40,160 --> 00:51:44,997
solutions around drug abuse. Let's
get some solutions around the rise of

889
00:51:45,080 --> 00:51:49,917
inequality. And let's have our computers
help us with those solutions.

890
00:51:50,000 --> 00:51:52,437
>> And let's just talk about this [clears
throat] is something you know a

891
00:51:52,520 --> 00:51:55,677
lot more about than I do, but how

892
00:51:55,760 --> 00:51:59,317
programming may be able or

893
00:51:59,400 --> 00:52:01,997
incapable of addressing

894
00:52:02,080 --> 00:52:06,517
morals and ethics. And I'll
give an example, probably a bad

895
00:52:06,600 --> 00:52:08,357
example and not technically accurate,

896
00:52:08,440 --> 00:52:10,637
but it seems like we're already at a

897
00:52:10,720 --> 00:52:13,837
point with say the development of

898
00:52:13,920 --> 00:52:16,717
autonomous vehicles where

899
00:52:16,800 --> 00:52:18,957
questions that might have been presented

900
00:52:19,040 --> 00:52:22,877
in a freshman philosophy class, like the

901
00:52:22,960 --> 00:52:25,157
trolley problem, actually need to be

902
00:52:25,240 --> 00:52:27,597
programmed on some level in the sense

903
00:52:27,680 --> 00:52:31,037
that cars need to make decisions if

904
00:52:31,120 --> 00:52:33,357
there is an accident. They need to say

905
00:52:33,440 --> 00:52:35,997
choose between going on the sidewalk at

906
00:52:36,080 --> 00:52:39,077
high speed and hitting three

907
00:52:39,160 --> 00:52:43,677
elderly or swerving right and hitting
one child, let's just say. Not that we

908
00:52:43,760 --> 00:52:45,957
would ever want to be in that type of

909
00:52:46,040 --> 00:52:48,957
situation, but these things happen.

910
00:52:49,040 --> 00:52:51,517
How do you foresee computer scientists

911
00:52:51,600 --> 00:52:54,157
attempting to, if this is even going to

912
00:52:54,240 --> 00:52:57,037
be an objective, instill ethics and

913
00:52:57,120 --> 00:53:01,317
morals into AI? And does it just require

914
00:53:01,400 --> 00:53:06,517
a level of self-awareness that perhaps
we don't have? I'm curious how you might

915
00:53:06,600 --> 00:53:09,557
think about that. >> There are
many, many computer scientists

916
00:53:09,640 --> 00:53:13,437
working on this. Every major computer
science program I'm aware of has a

917
00:53:13,520 --> 00:53:16,357
computer science
and ethics research project.

918
00:53:16,440 --> 00:53:18,117
There are a lot of problems. One of the

919
00:53:18,200 --> 00:53:20,277
first problems is the computer science

920
00:53:20,360 --> 00:53:25,597
and AI are based on learning
data, literally learning,

921
00:53:25,680 --> 00:53:26,797
and therefore the information that

922
00:53:26,880 --> 00:53:29,197
they're learning has biases.

923
00:53:29,280 --> 00:53:32,677
So, whatever prejudice and bias and

924
00:53:32,760 --> 00:53:34,757
religious problems that society has

925
00:53:34,840 --> 00:53:37,437
around it, the computer will absorb.

926
00:53:37,520 --> 00:53:42,237
So, the research is how to identify
those biases, cuz remember in many cases

927
00:53:42,320 --> 00:53:45,357
these systems cannot
tell you what they know

928
00:53:45,440 --> 00:53:49,557
and how to mediate them.
It's pretty clear to me that there's

929
00:53:49,640 --> 00:53:53,557
going to end up being the system that
knows everything, and then there's going

930
00:53:53,640 --> 00:53:57,157
to be a supervisory system that limits it.

931
00:53:57,240 --> 00:54:00,677
So, two different systems. One will be
the knowledge system, and another one

932
00:54:00,760 --> 00:54:04,197
which will keep it within some guardrails.

933
00:54:04,280 --> 00:54:08,597
So, the question that was asked is not
a permissible question, don't send it to

934
00:54:08,680 --> 00:54:12,477
the system. And you're
going to have all sorts of

935
00:54:12,560 --> 00:54:15,317
problems. My favorite
self-driving car problem

936
00:54:15,400 --> 00:54:19,797
is here in New York. Eventually,

937
00:54:19,880 --> 00:54:24,077
all the cars are self-driving
because it's such a crowded grid, and

938
00:54:24,160 --> 00:54:28,317
traffic moves perfectly.
The engineers at Google and everywhere

939
00:54:28,400 --> 00:54:33,077
else have figured out exactly how to
optimize under a set of assumptions, the

940
00:54:33,160 --> 00:54:37,197
aggregate and average delivery time
of a human from place to place. It's a

941
00:54:37,280 --> 00:54:39,477
perfect computer science solution.

942
00:54:39,560 --> 00:54:42,197
So, now we've got a woman
who's going into labor

943
00:54:42,280 --> 00:54:44,317
who needs to get there faster.

944
00:54:44,400 --> 00:54:48,037
Is there a button in the car that says,

945
00:54:48,120 --> 00:54:52,837
"I'm pregnant, I'm about to give birth,
and I need to get there faster." Okay,

946
00:54:52,920 --> 00:54:56,037
so she presses the button,
and somehow it works.

947
00:54:56,120 --> 00:54:58,397
How do we make sure that a gentleman

948
00:54:58,480 --> 00:55:00,917
who's lying

949
00:55:01,000 --> 00:55:03,637
cannot press the same button?

950
00:55:03,720 --> 00:55:08,077
In the trolley problem, all of these are
of the form, how do you choose one life

951
00:55:08,160 --> 00:55:11,917
for the other?
The correct answer is, don't kill

952
00:55:12,000 --> 00:55:15,157
anything. And so, we're
going to have to find ways

953
00:55:15,240 --> 00:55:18,917
to avoid being in the situation where
you have to choose between three old

954
00:55:19,000 --> 00:55:22,997
people and one child.
And these are the great debates of

955
00:55:23,080 --> 00:55:26,637
philosophers, and how do we value life,
and so forth. But, I think we should

956
00:55:26,720 --> 00:55:30,317
start with the premise that the system
should be designed such that it

957
00:55:30,400 --> 00:55:32,717
optimizes overall happiness and overall

958
00:55:32,800 --> 00:55:35,837
wealth, in the societal sense of wealth.

959
00:55:35,920 --> 00:55:39,797
Uh as an example,
we tolerate double parking.

960
00:55:39,880 --> 00:55:42,477
We tolerate people speeding. We don't

961
00:55:42,560 --> 00:55:46,877
track every car and give them
an automatic ticket every time they go

962
00:55:46,960 --> 00:55:50,277
above the 30 mile an hour
speed limit by 1 mile.

963
00:55:50,360 --> 00:55:52,677
But technically that would be easy.

964
00:55:52,760 --> 00:55:56,477
If you want to eliminate
the vast majority of crime

965
00:55:56,560 --> 00:55:59,357
in our society, put cameras in every

966
00:55:59,440 --> 00:56:02,637
public space with face recognition.

967
00:56:02,720 --> 00:56:05,157
It's by the way illegal to do so.

968
00:56:05,240 --> 00:56:06,877
But if you really care about crime to

969
00:56:06,960 --> 00:56:09,117
the exclusion of personal freedom and

970
00:56:09,200 --> 00:56:14,357
the freedom of of not being surveilled,
then we could do it. So the technology

971
00:56:14,440 --> 00:56:17,517
gives you these choices and those are
not choices that computer scientists

972
00:56:17,600 --> 00:56:20,997
should make. Those are
choices for society. I use the

973
00:56:21,080 --> 00:56:24,157
surveillance cameras
as an example to say that

974
00:56:24,240 --> 00:56:26,877
in Britain they're very widely accepted.

975
00:56:26,960 --> 00:56:30,317
When you're in Britain on a street,
you're on camera. In the United States,

976
00:56:30,400 --> 00:56:33,917
it's partial. Sometimes you are,
sometimes you're not. But in Germany

977
00:56:34,000 --> 00:56:38,957
with a long history of the Stasi,
they are very violently opposed to such

978
00:56:39,040 --> 00:56:42,317
surveillance. These are three different
democracies that have made the choices

979
00:56:42,400 --> 00:56:45,957
in different ways. So I don't think
that computer scientists and the tech

980
00:56:46,040 --> 00:56:49,037
industry should make these decisions,
but I do think what we should tell

981
00:56:49,120 --> 00:56:52,717
people is our tools give
you this range of choices.

982
00:56:52,800 --> 00:56:56,517
If you look at leadership in China,
China is a couple generations ahead in

983
00:56:56,600 --> 00:57:00,037
surveillance. They can
actually spot you in your gate

984
00:57:00,120 --> 00:57:04,157
now, the way you walk, not just your face
recognition. This is not something

985
00:57:04,240 --> 00:57:08,877
we want to lead in. >> I'm just
letting that all sink in for a second.

986
00:57:08,960 --> 00:57:12,197
>> [laughter] >> This is one of those
conversations for me. It's great.

987
00:57:12,280 --> 00:57:14,877
There's so much to chew on and I'm going

988
00:57:14,960 --> 00:57:17,637
to take a 90 degree turn

989
00:57:17,720 --> 00:57:19,557
back to

990
00:57:19,640 --> 00:57:22,677
the physicist and the biologist

991
00:57:22,760 --> 00:57:26,997
and others who will be able to

992
00:57:27,080 --> 00:57:29,677
consult AI in the way I think it was

993
00:57:29,760 --> 00:57:34,077
presented to help assimilate
new information, new

994
00:57:34,160 --> 00:57:37,637
developments, get up to speed.
They can't possibly

995
00:57:37,720 --> 00:57:42,317
even with physical constraints, keep up
or digest the amount they would like to

996
00:57:42,400 --> 00:57:45,517
digest. Now, many people, Dr. Kissinger

997
00:57:45,600 --> 00:57:49,437
certainly over decades
and many, many others,

998
00:57:49,520 --> 00:57:54,717
spend [snorts] a lot of their time
ingesting information. And that could be

999
00:57:54,800 --> 00:57:56,157
in the form of reading, it could be in

1000
00:57:56,240 --> 00:57:59,837
the form of conversations like this.

1001
00:57:59,920 --> 00:58:02,797
I suppose there are two questions. One is,

1002
00:58:02,880 --> 00:58:05,157
how do you think

1003
00:58:05,240 --> 00:58:07,477
thought workers or humans will spend

1004
00:58:07,560 --> 00:58:09,877
their time once that ingestion is

1005
00:58:09,960 --> 00:58:12,437
dramatically reduced or removed? And

1006
00:58:12,520 --> 00:58:17,837
along with that, if we get
to the point where that is possible,

1007
00:58:17,920 --> 00:58:22,597
and there's a question of how it
would be conveyed to the human,

1008
00:58:22,680 --> 00:58:25,237
how far are we from there simply being a

1009
00:58:25,320 --> 00:58:28,877
direct brain-computer interface where

1010
00:58:28,960 --> 00:58:33,477
that information is somehow seamlessly

1011
00:58:33,560 --> 00:58:38,957
integrated into our consciousness
without being spoken or imparted to us

1012
00:58:39,040 --> 00:58:42,837
externally? >> To answer
the the last part first,

1013
00:58:42,920 --> 00:58:45,597
we are in our industry, we're working on

1014
00:58:45,680 --> 00:58:50,437
direct brain connections of one kind
or another. They're all in startups.

1015
00:58:50,520 --> 00:58:52,277
They're all speculative at this point.

1016
00:58:52,360 --> 00:58:55,597
They've shown some gains.

1017
00:58:55,680 --> 00:58:59,557
If you think about 200 years from now,

1018
00:58:59,640 --> 00:59:03,437
to pick a random number,
it's probable that we'll know the

1019
00:59:03,520 --> 00:59:05,757
complete details of the human brain, how

1020
00:59:05,840 --> 00:59:08,477
it's wired, how it works.

1021
00:59:08,560 --> 00:59:10,517
So, if you think far enough in advance,

1022
00:59:10,600 --> 00:59:13,877
well past our lifetimes, it's probable

1023
00:59:13,960 --> 00:59:17,717
that we'll know a great deal about how
to manipulate the brain externally to

1024
00:59:17,800 --> 00:59:21,397
the brain. We'll understand how it
works, we'll understand the wiring,

1025
00:59:21,480 --> 00:59:25,277
maybe there'll be some attachment and so
forth. Most people think that that will

1026
00:59:25,360 --> 00:59:27,917
occur. No one has any idea when. When

1027
00:59:28,000 --> 00:59:32,917
you go back to the the gains, you want
to get the basis of what the next 20

1028
00:59:33,000 --> 00:59:34,917
years look like. And I think it's fair

1029
00:59:35,000 --> 00:59:37,837
to say that we're going to be awash in

1030
00:59:37,920 --> 00:59:40,637
information and misinformation

1031
00:59:40,720 --> 00:59:42,997
at a scale that is overwhelming and it's

1032
00:59:43,080 --> 00:59:48,157
already overwhelming.
So, the most likely scenario

1033
00:59:48,240 --> 00:59:52,117
is that each of us will have
the equivalent of an AI communications

1034
00:59:52,200 --> 00:59:56,397
assistant that will watch,
like while you and I

1035
00:59:56,480 --> 01:00:00,717
are speaking, my AI assistant
is watching what's going on,

1036
01:00:00,800 --> 01:00:03,877
and it knows my preferences, it knows
what I care about, and it has a good

1037
01:00:03,960 --> 01:00:06,117
sense of judgment.

1038
01:00:06,200 --> 01:00:08,237
And when we're finished speaking, it'll

1039
01:00:08,320 --> 01:00:13,317
say, "By the way, over here in Arkansas,
the following thing happened that you

1040
01:00:13,400 --> 01:00:18,397
might want to check out."
More importantly, this AI assistant will

1041
01:00:18,480 --> 01:00:23,317
battle with the misinformation assistants,
and it'll say, "Prove to me that you're

1042
01:00:23,400 --> 01:00:27,837
a human before I expose you to my human."

1043
01:00:27,920 --> 01:00:32,077
And so, you can imagine a scenario
where the solution to the misinformation

1044
01:00:32,160 --> 01:00:34,357
problem and the solution to this

1045
01:00:34,440 --> 01:00:36,877
information space problem is that each

1046
01:00:36,960 --> 01:00:41,757
of us has our own AI assistant
that think of it as the equivalent of a

1047
01:00:41,840 --> 01:00:44,957
phone, although in practice it's
a supercomputer that's accessed through

1048
01:00:45,040 --> 01:00:49,037
your phone or equivalent,
that sort of keeps you sane.

1049
01:00:49,120 --> 01:00:52,077
If you go back to my earlier
comments about children,

1050
01:00:52,160 --> 01:00:57,597
we have no idea what the rule should be
for that assistant. So, let me give you

1051
01:00:57,680 --> 01:01:00,997
an example. We've learned,
unfortunately, in the last few years

1052
01:01:01,080 --> 01:01:03,797
that there are still horrific racial

1053
01:01:03,880 --> 01:01:08,077
prejudice, horrifically hateful people.

1054
01:01:08,160 --> 01:01:11,477
Well, they get an assistant, too.

1055
01:01:11,560 --> 01:01:15,917
Is their assistant going
to pattern their racism

1056
01:01:16,000 --> 01:01:19,917
or their misogyny or their
violence against children or

1057
01:01:20,000 --> 01:01:23,957
all these sort of hateful behaviors, cuz
these are part of humanity too. Or will

1058
01:01:24,040 --> 01:01:27,357
there be some regulation that says
that your assistant has to be politically

1059
01:01:27,440 --> 01:01:31,237
correct? It has to say,
are you a he, a she, or

1060
01:01:31,320 --> 01:01:35,357
you know, in other words,
how will society resolve that?

1061
01:01:35,440 --> 01:01:39,677
And my prediction will be that each
government and each culture will adopt

1062
01:01:39,760 --> 01:01:41,757
different rules about them.

1063
01:01:41,840 --> 01:01:45,117
But they're not going to be unregulated.

1064
01:01:45,200 --> 01:01:48,677
What we've learned, and I've
learned really the hard way,

1065
01:01:48,760 --> 01:01:51,557
is that the technology that I helped

1066
01:01:51,640 --> 01:01:55,757
work on and that is being invented now
is no longer optional. 15 years ago I

1067
01:01:55,840 --> 01:02:00,077
used to give this speech saying, "Look,
you hate the internet, turn your phone

1068
01:02:00,160 --> 01:02:04,117
off. Have dinner with your family. Do

1069
01:02:04,200 --> 01:02:07,877
whatever you're going to do, but get off."

1070
01:02:07,960 --> 01:02:10,437
And that's not a practical

1071
01:02:10,520 --> 01:02:15,037
answer today. The internet
is no longer optional. It's

1072
01:02:15,120 --> 01:02:18,637
essential, partly because of the pandemic,
but because of e-commerce and

1073
01:02:18,720 --> 01:02:21,357
business and knowledge and so forth.

1074
01:02:21,440 --> 01:02:23,237
So, it's going to get regulated, and the

1075
01:02:23,320 --> 01:02:25,957
question is how and under what terms.

1076
01:02:26,040 --> 01:02:30,797
>> I've I believe read you use the analogy

1077
01:02:30,880 --> 01:02:35,357
of the telephone. Maybe I'm making
that up, but in the sense that

1078
01:02:35,440 --> 01:02:37,437
just because there are bad actors who

1079
01:02:37,520 --> 01:02:40,317
can use the telephone for

1080
01:02:40,400 --> 01:02:42,677
wrongdoing, for crime, [snorts] etc., it

1081
01:02:42,760 --> 01:02:45,357
doesn't mean we eliminate the telephone.

1082
01:02:45,440 --> 01:02:47,437
It means that we have means of

1083
01:02:47,520 --> 01:02:50,957
regulation and enforcement and so on. I

1084
01:02:51,040 --> 01:02:54,717
guess the telephone
by comparison seems to be such a

1085
01:02:54,800 --> 01:02:58,037
clean, although increasingly, maybe not,

1086
01:02:58,120 --> 01:03:00,197
discrete system.

1087
01:03:00,280 --> 01:03:02,757
What are the most important next steps

1088
01:03:02,840 --> 01:03:06,037
from your perspective with respect to

1089
01:03:06,120 --> 01:03:10,957
even thinking about regulation, the best
questions to ask, or just concrete

1090
01:03:11,040 --> 01:03:13,837
steps? >> I always like
to use self-driving cars,

1091
01:03:13,920 --> 01:03:17,077
cuz everyone can relate to this. So,

1092
01:03:17,160 --> 01:03:22,237
in California, there's a concept
called a rolling stop where you

1093
01:03:22,320 --> 01:03:25,117
>> [laughter] >> The California roll, yes.

1094
01:03:25,200 --> 01:03:28,957
>> And when you come to the stop sign,
you sort of forget to fully stop. You roll

1095
01:03:29,040 --> 01:03:32,277
through. So, the policeman comes over
and says, "You did the rolling stop."

1096
01:03:32,360 --> 01:03:35,957
And I say to the policeman,
"Sir, I did not."

1097
01:03:36,040 --> 01:03:40,357
And then it said, "Who did?"
And then the car says, "I did, sir."

1098
01:03:40,440 --> 01:03:45,157
And the policeman says, "Why?"
And the car says, "I don't know."

1099
01:03:45,240 --> 01:03:48,037
>> [laughter] >> Now, >> Very
frustrating for the police officer.

1100
01:03:48,120 --> 01:03:51,037
>> Yes, so So, who gets the ticket?

1101
01:03:51,120 --> 01:03:56,117
So, your choices are the human,
the car itself, the manufacturer of the

1102
01:03:56,200 --> 01:03:59,477
car, or the data that the car was trained

1103
01:03:59,560 --> 01:04:03,437
with. So, that's the debate to have.

1104
01:04:03,520 --> 01:04:08,077
Give you another example. I feel very
strongly in favor of free speech for

1105
01:04:08,160 --> 01:04:11,477
humans, but I don't feel very strongly for

1106
01:04:11,560 --> 01:04:15,477
amplification by computers.
And so, what we're seeing now is we're

1107
01:04:15,560 --> 01:04:18,277
seeing humans who have wacky, false,

1108
01:04:18,360 --> 01:04:23,157
conspiratorial ideas, what have you,
get picked up and amplified in these

1109
01:04:23,240 --> 01:04:26,797
systems. That drives
everyone crazy because we

1110
01:04:26,880 --> 01:04:28,957
can't tell the difference between a

1111
01:04:29,040 --> 01:04:32,277
genuine social movement and concern

1112
01:04:32,360 --> 01:04:34,757
versus a single crazy person who has an

1113
01:04:34,840 --> 01:04:39,357
amplified idea that seems plausible,
but is basically false. We have no way of

1114
01:04:39,440 --> 01:04:42,557
falsifying such things.
That's something that's got to get

1115
01:04:42,640 --> 01:04:44,597
sorted out. We can't live in an

1116
01:04:44,680 --> 01:04:47,317
information space

1117
01:04:47,400 --> 01:04:50,597
that is so full of misinformation

1118
01:04:50,680 --> 01:04:54,597
and manipulation that we
can't get through the day.

1119
01:04:54,680 --> 01:04:58,197
When we go back in the book to talk
about the Renaissance, we say this is a

1120
01:04:58,280 --> 01:05:02,597
new epoch because in addition to this
misinformation that we've been speaking

1121
01:05:02,680 --> 01:05:06,997
about, we also have never had a situation

1122
01:05:07,080 --> 01:05:11,277
in our human experience where there
was an intelligence that was similar to

1123
01:05:11,360 --> 01:05:14,437
ours, but not the same,
that was non-human.

1124
01:05:14,520 --> 01:05:19,157
And so, imagine a situation where these
intelligences exist and they can be

1125
01:05:19,240 --> 01:05:24,037
consulted. Well, who gets to consult them?
What happens to their answers?

1126
01:05:24,120 --> 01:05:27,717
So, for example, if it's an oracle,
do you have a rule that every answer from

1127
01:05:27,800 --> 01:05:30,357
the oracle is published to the world?

1128
01:05:30,440 --> 01:05:33,837
Because it's presumably beneficial.
But, what if it's a private question or a

1129
01:05:33,920 --> 01:05:37,197
secret? What if it's being used
in national security? Again, these are

1130
01:05:37,280 --> 01:05:39,797
questions that we have not resolved. So,

1131
01:05:39,880 --> 01:05:41,957
what we say is, these are really hard

1132
01:05:42,040 --> 01:05:44,757
questions. What happens when the AI

1133
01:05:44,840 --> 01:05:47,437
perceives aspects of reality that humans

1134
01:05:47,520 --> 01:05:48,997
do not?

1135
01:05:49,080 --> 01:05:52,437
That it sees a connection. There are

1136
01:05:52,520 --> 01:05:56,517
physicists who talk about
new universes and new worlds.

1137
01:05:56,600 --> 01:05:58,957
And you can imagine a situation where

1138
01:05:59,040 --> 01:06:03,797
there's some thing that we
as humans cannot conceive of

1139
01:06:03,880 --> 01:06:08,157
because of our limited intelligence, but
the computer detects it and then we say,

1140
01:06:08,240 --> 01:06:11,917
"Oh my god." In math, there's a

1141
01:06:12,000 --> 01:06:14,557
long story about an object that lives in

1142
01:06:14,640 --> 01:06:18,997
a two-dimensional world and the
third dimension appears, but if

1143
01:06:19,080 --> 01:06:22,077
you're in a two-dimensional world, you
never see the third dimension, so you're

1144
01:06:22,160 --> 01:06:26,237
always confused. So,
what if this AI can find a

1145
01:06:26,320 --> 01:06:30,157
dimensionality of the world that we
as humans, not a single one of us can

1146
01:06:30,240 --> 01:06:34,197
understand? And we're now confused.

1147
01:06:34,280 --> 01:06:38,677
We don't know how to handle that.
What happens, another example is

1148
01:06:38,760 --> 01:06:42,317
Dr. Kissinger believes that

1149
01:06:42,400 --> 01:06:47,037
I'll paraphrase.
When something is not understandable by

1150
01:06:47,120 --> 01:06:48,597
humans,

1151
01:06:48,680 --> 01:06:52,197
they will perceive it as an act of God.

1152
01:06:52,280 --> 01:06:55,557
Or they will resist it.

1153
01:06:55,640 --> 01:06:59,637
And you can imagine a situation
where you end up with nativists

1154
01:06:59,720 --> 01:07:01,717
who decide that this world that I'm

1155
01:07:01,800 --> 01:07:05,437
describing is so impossibly unpleasant

1156
01:07:05,520 --> 01:07:10,117
that they turn it all off and they go
to the equivalent of uh the woods of

1157
01:07:10,200 --> 01:07:13,637
Pennsylvania and they say leave me alone.

1158
01:07:13,720 --> 01:07:16,637
And you have other people who learn to

1159
01:07:16,720 --> 01:07:21,357
drive it and manipulate
it for good and evil.

1160
01:07:21,440 --> 01:07:26,397
>> You'll have a choice and then
one final scenario to think about

1161
01:07:26,480 --> 01:07:28,237
goes like this.

1162
01:07:28,320 --> 01:07:33,597
Let's say you're older, kids are grown
and it's time for you to take a break

1163
01:07:33,680 --> 01:07:37,037
from the world. So, you put on headphones

1164
01:07:37,120 --> 01:07:41,397
and VR glasses and in those
VR glasses and headphones

1165
01:07:41,480 --> 01:07:44,597
you have a life of you
as a much younger person.

1166
01:07:44,680 --> 01:07:49,477
A much more beautiful, handsome,
wealthier, stronger, whatever

1167
01:07:49,560 --> 01:07:53,197
with the friends that you remember
of the time recreated even though they may

1168
01:07:53,280 --> 01:07:57,117
have passed away.
That might be a more fun life for you

1169
01:07:57,200 --> 01:08:01,877
every day than the life
that you have in this scenario.

1170
01:08:01,960 --> 01:08:06,277
What happens when we lose people?
I call that crossing to the other side.

1171
01:08:06,360 --> 01:08:09,797
When they wake up in the morning,
they just want to be over there.

1172
01:08:09,880 --> 01:08:11,717
That will happen, too.

1173
01:08:11,800 --> 01:08:14,517
>> It strikes me that

1174
01:08:14,600 --> 01:08:17,437
it is science fiction can be

1175
01:08:17,520 --> 01:08:22,117
prescient in some instances and it
doesn't make it future fiction, it just

1176
01:08:22,200 --> 01:08:24,957
makes it current day fiction, but there's
[clears throat] I don't want to

1177
01:08:25,040 --> 01:08:29,757
say predictive power, but I think
of really good science fiction

1178
01:08:29,840 --> 01:08:33,157
of course subjective, but Snow
Crash, the description of the

1179
01:08:33,240 --> 01:08:36,477
metaverse or you have some
of William Gibson's work.

1180
01:08:36,560 --> 01:08:40,717
I'm just curious, do you or have you
read science fiction much yourself?

1181
01:08:40,800 --> 01:08:42,797
>> Well, Neuromancer is particularly good.

1182
01:08:42,880 --> 01:08:46,477
If you look at Seven
Eves which is a good book.

1183
01:08:46,560 --> 01:08:51,477
It's an extraordinary composition of of
the importance of humanity surviving the

1184
01:08:51,560 --> 01:08:56,397
destruction of the earth.
And in Seven Eves toward the end

1185
01:08:56,480 --> 01:08:58,357
in their science fiction, they have

1186
01:08:58,440 --> 01:09:01,037
assistants

1187
01:09:01,120 --> 01:09:03,477
that have a funny name that serve this

1188
01:09:03,560 --> 01:09:08,397
function that I'm describing.
So, as usual, science fiction

1189
01:09:08,480 --> 01:09:10,277
anticipates many of the things in

1190
01:09:10,360 --> 01:09:14,037
technology. But, if you think about it,

1191
01:09:14,120 --> 01:09:18,637
we believe today, from the Reformation,

1192
01:09:18,720 --> 01:09:20,957
that we have the sole power of

1193
01:09:21,040 --> 01:09:26,117
understanding reality. But,
at some point, that's not going to

1194
01:09:26,200 --> 01:09:29,837
be true. When that happens, what will our

1195
01:09:29,920 --> 01:09:33,677
self-conception look like?

1196
01:09:33,760 --> 01:09:38,197
How will we conceive of ourselves?
How will we organize ourselves?

1197
01:09:38,280 --> 01:09:41,917
>> How will we value ourselves?
Let me ask you

1198
01:09:42,000 --> 01:09:44,197
some follow-up questions on this word

1199
01:09:44,280 --> 01:09:47,797
reality and perception because it makes

1200
01:09:47,880 --> 01:09:51,837
me think, this conversation makes me
think of, and maybe getting the the full

1201
01:09:51,920 --> 01:09:55,037
name wrong, so I'll I'll correct it in the

1202
01:09:55,120 --> 01:09:57,477
show notes if I do, but I believe

1203
01:09:57,560 --> 01:10:00,757
his name is Donald Hoffman, who is a

1204
01:10:00,840 --> 01:10:05,517
cognitive scientist, also computer
scientist at UC Irvine, and

1205
01:10:05,600 --> 01:10:09,357
he has a book that's called, I believe,
The Case Against Reality, and also a TED

1206
01:10:09,440 --> 01:10:10,557
Talk,

1207
01:10:10,640 --> 01:10:14,837
and the general exploration focuses on

1208
01:10:14,920 --> 01:10:17,757
how easy it is to prove and demonstrate

1209
01:10:17,840 --> 01:10:22,597
that we are optimized for very few
things, right? Reproduction principal

1210
01:10:22,680 --> 01:10:23,677
among them,

1211
01:10:23,760 --> 01:10:26,957
and that what we perceive is not some

1212
01:10:27,040 --> 01:10:31,597
objective reality, and that if you were
a mantis shrimp, for instance, you would

1213
01:10:31,680 --> 01:10:35,077
see things very differently. They have
these incredible optic systems, and so

1214
01:10:35,160 --> 01:10:36,477
on and so forth.

1215
01:10:36,560 --> 01:10:39,637
What does the word reality mean to you,

1216
01:10:39,720 --> 01:10:43,077
and how do you think, personally, that

1217
01:10:43,160 --> 01:10:47,597
might change once we are
deeper into the era of

1218
01:10:47,680 --> 01:10:52,477
well-developed AI? >> 50 years
ago, reality was television and

1219
01:10:52,560 --> 01:10:54,517
normal life.

1220
01:10:54,600 --> 01:10:58,197
Today, reality is this online world that

1221
01:10:58,280 --> 01:11:01,077
is constantly demanding attention,

1222
01:11:01,160 --> 01:11:05,797
constantly full of stressors of one kind
or another, constantly demanding your

1223
01:11:05,880 --> 01:11:08,597
engagement because
that's the way it's built.

1224
01:11:08,680 --> 01:11:12,557
The engagement is around monetization,
uh spreading information and

1225
01:11:12,640 --> 01:11:14,797
misinformation, and so forth.

1226
01:11:14,880 --> 01:11:17,997
Everyone I know is being driven crazy by

1227
01:11:18,080 --> 01:11:19,957
the explosion of that.

1228
01:11:20,040 --> 01:11:22,797
I think that in the next decade,

1229
01:11:22,880 --> 01:11:25,837
the explosion will continue and the

1230
01:11:25,920 --> 01:11:28,997
solutions will need to to be developed

1231
01:11:29,080 --> 01:11:31,597
because more and more the digital world

1232
01:11:31,680 --> 01:11:36,877
becomes the real world.
An example that I used, which is uh for

1233
01:11:36,960 --> 01:11:39,757
example, you can see it
in the movie Ready Player One,

1234
01:11:39,840 --> 01:11:41,637
where people cross over and they spend

1235
01:11:41,720 --> 01:11:46,957
most of their time in a virtual world,
is true for many, many teenagers.

1236
01:11:47,040 --> 01:11:49,837
And there's every reason to believe
in the next 10 or 20 years those worlds

1237
01:11:49,920 --> 01:11:53,397
will become extraordinarily sophisticated.

1238
01:11:53,480 --> 01:11:56,437
So, I'll give you a simple example.

1239
01:11:56,520 --> 01:11:59,037
At Google, because there
was so much going on, we

1240
01:11:59,120 --> 01:12:02,357
developed a pattern where people would
be in meetings, but they would also be

1241
01:12:02,440 --> 01:12:04,917
doing their email at the same time.

1242
01:12:05,000 --> 01:12:07,877
And we became very good at doing two

1243
01:12:07,960 --> 01:12:12,677
things at once, and this was a cultural
norm. But I had to put in a rule that

1244
01:12:12,760 --> 01:12:16,237
when you had outsiders in the room,
you couldn't do this

1245
01:12:16,320 --> 01:12:20,237
because it was seen as so incredibly rude,

1246
01:12:20,320 --> 01:12:21,677
which it is,

1247
01:12:21,760 --> 01:12:24,117
but it was a cultural norm that we

1248
01:12:24,200 --> 01:12:27,357
adopted and invented and worked well.

1249
01:12:27,440 --> 01:12:31,357
So, you can see that the addiction cycle

1250
01:12:31,440 --> 01:12:34,717
in our world is largely now locked
into addiction cycles, whether it's

1251
01:12:34,800 --> 01:12:38,117
drug-related or whether it's
technology-related or it's

1252
01:12:38,200 --> 01:12:39,997
attention-related. I mean, again, humans

1253
01:12:40,080 --> 01:12:43,397
are like this. I am very, very concerned

1254
01:12:43,480 --> 01:12:46,157
that we will lose perspective on what

1255
01:12:46,240 --> 01:12:51,437
reality really is.
Humans are not built for the kind of

1256
01:12:51,520 --> 01:12:54,557
stressors that occur every day.
We just aren't

1257
01:12:54,640 --> 01:12:58,277
organized. We're organized around
the campfire and the lion and that sort of

1258
01:12:58,360 --> 01:13:00,677
thing, which didn't occur at warp speed.

1259
01:13:00,760 --> 01:13:03,877
And so, I'm assuming that this pressure

1260
01:13:03,960 --> 01:13:05,797
on human development,

1261
01:13:05,880 --> 01:13:08,277
this sort of craziness, this constant

1262
01:13:08,360 --> 01:13:11,557
anxiety, will lead to more neuroses,

1263
01:13:11,640 --> 01:13:14,917
more paranoia, not less.

1264
01:13:15,000 --> 01:13:19,677
And that people will then have to figure
out a way, just in the same way that

1265
01:13:19,760 --> 01:13:23,717
parents are trying to keep their kids
offline some of the time, cuz kids are

1266
01:13:23,800 --> 01:13:27,677
online from the moment they wake up
to the moment they go to sleep, kids want

1267
01:13:27,760 --> 01:13:31,037
them go play ball for an hour,
I'm taking your phone away. We're going to

1268
01:13:31,120 --> 01:13:32,877
have to do the same thing for adults.

1269
01:13:32,960 --> 01:13:36,357
>> What rules or

1270
01:13:36,440 --> 01:13:39,317
constraints do you have for yourself

1271
01:13:39,400 --> 01:13:43,277
around social media or other types of

1272
01:13:43,360 --> 01:13:47,197
digital stimuli?
>> One of my friends said that he stopped

1273
01:13:47,280 --> 01:13:51,877
watching television because
he reads all his news online.

1274
01:13:51,960 --> 01:13:55,237
And I thought, okay, well, that's
a reasonable time trade-off. Of course,

1275
01:13:55,320 --> 01:13:58,117
you're you're changing
one stressor for another,

1276
01:13:58,200 --> 01:14:00,037
but that says, I only have time for one,

1277
01:14:00,120 --> 01:14:03,197
I've chosen the online world.

1278
01:14:03,280 --> 01:14:07,077
And so, I think the first question
is there's limited time. And then the

1279
01:14:07,160 --> 01:14:11,757
second thing is you've got to have some
rules. So, for me, I'm online all the

1280
01:14:11,840 --> 01:14:15,037
time, but I try to turn
it off during dinner.

1281
01:14:15,120 --> 01:14:17,757
I can usually get it done for about an

1282
01:14:17,840 --> 01:14:21,757
hour. So, the question is, when you go

1283
01:14:21,840 --> 01:14:25,637
without it for a while,
give you another example, in 2012,

1284
01:14:25,720 --> 01:14:29,877
a group of us went to North Korea and we
went from Beijing. And this was at a

1285
01:14:29,960 --> 01:14:34,517
time it was legal to do so
as an American, and we left our

1286
01:14:34,600 --> 01:14:38,237
phones in the Beijing
airport in a trusted person.

1287
01:14:38,320 --> 01:14:41,077
And we sat in the lounge as the plane

1288
01:14:41,160 --> 01:14:45,597
was about to take us to Pyongyang
without our phones, and it's It's

1289
01:14:45,680 --> 01:14:50,757
feeling. And by the time we got there and
got settled in the hotel, it's a group of

1290
01:14:50,840 --> 01:14:54,157
maybe 10, we started
talking to each other, which

1291
01:14:54,240 --> 01:14:56,317
we would never have done.

1292
01:14:56,400 --> 01:14:59,517
And within 3 days, we were best friends.

1293
01:14:59,600 --> 01:15:04,397
The moment we got back to Beijing
and got our phones, we were on them.

1294
01:15:04,480 --> 01:15:09,557
We lost all context of what we were
doing, and we were back in the soup.

1295
01:15:09,640 --> 01:15:13,237
So, there's going to be some in the same

1296
01:15:13,320 --> 01:15:17,437
sense that people go to spa vacations,
there's going to have to be some

1297
01:15:17,520 --> 01:15:21,237
equivalent of a spa
vacation from your devices.

1298
01:15:21,320 --> 01:15:23,517
>> Yeah, I'm wondering what what type of

1299
01:15:23,600 --> 01:15:28,917
agency humans will be able to harness to

1300
01:15:29,000 --> 01:15:32,277
position themselves competitively in the

1301
01:15:32,360 --> 01:15:36,117
world of AI. It brings up so many
questions. I mean, such as the AI

1302
01:15:36,200 --> 01:15:39,917
assistant, will there be
tiered assistants, and will

1303
01:15:40,000 --> 01:15:44,077
the well-off be able to afford better
assistants? I mean, certainly, the

1304
01:15:44,160 --> 01:15:48,477
better-off have different types
of access now that help them to separate

1305
01:15:48,560 --> 01:15:52,837
signal from noise better than
the majority. So, that will probably

1306
01:15:52,920 --> 01:15:55,957
continue to be the case.
Do you think there And there's no right

1307
01:15:56,040 --> 01:15:59,877
answer here, by the way. Do you think
there is anything uniquely human that

1308
01:15:59,960 --> 01:16:01,477
ultimately

1309
01:16:01,560 --> 01:16:03,237
we will be able to

1310
01:16:03,320 --> 01:16:07,357
find value in in a world of

1311
01:16:07,440 --> 01:16:09,357
of AGI, for instance?

1312
01:16:09,440 --> 01:16:12,717
>> A lot of people are speculating

1313
01:16:12,800 --> 01:16:16,357
that the eventual future is a much

1314
01:16:16,440 --> 01:16:21,197
richer world where
people are largely idle,

1315
01:16:21,280 --> 01:16:25,317
and that the units of production are
so efficient, this is food production,

1316
01:16:25,400 --> 01:16:29,117
buildings, and so forth,
that everyone can live like a millionaire,

1317
01:16:29,200 --> 01:16:31,997
which means they don't have to work.
And a lot of people would prefer not to

1318
01:16:32,080 --> 01:16:35,717
work. Many of the jobs they find not
that interesting, and they have hobbies

1319
01:16:35,800 --> 01:16:38,717
that are more interesting
to them, and so forth.

1320
01:16:38,800 --> 01:16:42,997
It's possible that will could true.
It's also possible that that world is

1321
01:16:43,080 --> 01:16:47,397
dystopian because humans
need meaning. So, I think

1322
01:16:47,480 --> 01:16:49,357
the answer to your question has a lot to

1323
01:16:49,440 --> 01:16:52,397
do with whether the systems produce more

1324
01:16:52,480 --> 01:16:54,837
meaning for humans

1325
01:16:54,920 --> 01:16:59,597
or less meaning.
If the computer replaces me, that's less

1326
01:16:59,680 --> 01:17:03,237
meaning. If the computer
augments me, it's more

1327
01:17:03,320 --> 01:17:07,477
meaning. This is true
at every level of society.

1328
01:17:07,560 --> 01:17:10,797
So, there will be a small
number of countries.

1329
01:17:10,880 --> 01:17:14,077
The US will be one, China will be another,
there will be others which will

1330
01:17:14,160 --> 01:17:16,557
be the leaders in these technologies.

1331
01:17:16,640 --> 01:17:20,677
And because the way network platforms
work, those leaders will get far ahead

1332
01:17:20,760 --> 01:17:22,877
of the other countries.

1333
01:17:22,960 --> 01:17:25,037
So, there is going to be a division

1334
01:17:25,120 --> 01:17:28,077
between the AI-enabled

1335
01:17:28,160 --> 01:17:30,037
powerhouse countries

1336
01:17:30,120 --> 01:17:32,277
and the following countries who are

1337
01:17:32,360 --> 01:17:35,677
using it but not inventing it.

1338
01:17:35,760 --> 01:17:38,437
That divide will lead to enormous

1339
01:17:38,520 --> 01:17:43,077
societal and economic changes
which we don't fully understand. Put

1340
01:17:43,160 --> 01:17:46,317
another way, if you don't have a leading
university in your country that's doing

1341
01:17:46,400 --> 01:17:49,757
this kind of stuff,
you're going to be left out.

1342
01:17:49,840 --> 01:17:52,917
And so, at the human level,

1343
01:17:53,000 --> 01:17:55,157
some people will be comfortable in this

1344
01:17:55,240 --> 01:17:58,197
new and very, very curiosity-driven,

1345
01:17:58,280 --> 01:18:03,277
very interesting age, but an awful
lot of people will feel displaced.

1346
01:18:03,360 --> 01:18:06,197
Will they be less
motivated or more motivated?

1347
01:18:06,280 --> 01:18:10,677
Another example. We should
be able, using these tools, to

1348
01:18:10,760 --> 01:18:14,837
build learning systems that teach in
the most efficient way possible each and

1349
01:18:14,920 --> 01:18:18,197
every person.
We know people learn differently,

1350
01:18:18,280 --> 01:18:20,717
but the old rear ends and seats 30

1351
01:18:20,800 --> 01:18:23,397
people in front of a chalkboard is an

1352
01:18:23,480 --> 01:18:27,837
outmoded concept. So, there will be
a completely different way for kids to

1353
01:18:27,920 --> 01:18:31,797
learn and grow up, which has got
to be good because it'll maximize their

1354
01:18:31,880 --> 01:18:35,317
potential. So, you've got a person who's
been maximized their potential, will the

1355
01:18:35,400 --> 01:18:39,917
economic system give them opportunity
to be maximally potentialized? Give you

1356
01:18:40,000 --> 01:18:43,397
another example. I use science examples,
but let's imagine that you really want

1357
01:18:43,480 --> 01:18:46,397
to be a painter or a musician.

1358
01:18:46,480 --> 01:18:48,117
Well, in the future you'll say to the AI

1359
01:18:48,200 --> 01:18:50,757
system, I'm imagining a song about a

1360
01:18:50,840 --> 01:18:55,517
woman and a riverboat in New Orleans
and it's a sad song, but it has willows in

1361
01:18:55,600 --> 01:19:00,917
the background. Or something like that and
the computer will generate a song for you.

1362
01:19:01,000 --> 01:19:03,317
Which won't be as good as what you can do.

1363
01:19:03,400 --> 01:19:07,317
But you'll listen to it and you'll say,
oh, that then stimulates your idea.

1364
01:19:07,400 --> 01:19:10,517
So, I want to invent
a form of cubism that's

1365
01:19:10,600 --> 01:19:14,437
different from Picasso. So, the computer
will then go through a series of

1366
01:19:14,520 --> 01:19:18,597
scenarios of cubism that doesn't look
like Picasso and I'll say, I can do

1367
01:19:18,680 --> 01:19:21,237
better and then I'll be stimulated. So,

1368
01:19:21,320 --> 01:19:23,797
the people who can engage in that, I

1369
01:19:23,880 --> 01:19:26,277
used musicians and painters and

1370
01:19:26,360 --> 01:19:31,197
scientists and thinkers and writers are
going to be the economic winners. But

1371
01:19:31,280 --> 01:19:35,397
what about everyone else? >> Yeah,
it's a really great question. I

1372
01:19:35,480 --> 01:19:38,917
also immediately start thinking,
this just shows you how boring I am, but

1373
01:19:39,000 --> 01:19:42,437
about questions of copyright
and intellectual property. You know, will

1374
01:19:42,520 --> 01:19:44,797
you have some type of blockchain

1375
01:19:44,880 --> 01:19:47,117
identified

1376
01:19:47,200 --> 01:19:53,267
and verified assistant who is kind
of one-to-one correlated with your

1377
01:19:53,350 --> 01:19:55,597
>> [laughter] >> your identity
and social security

1378
01:19:55,680 --> 01:19:58,397
number, therefore you can copyright and

1379
01:19:58,480 --> 01:20:02,877
own anything that AI helps you
to generate or generates itself for that

1380
01:20:02,960 --> 01:20:05,957
matter. It's going to raise
all sorts of questions.

1381
01:20:06,040 --> 01:20:08,717
>> Yeah, I think we should build that
company immediately, you and I. Let's

1382
01:20:08,800 --> 01:20:11,637
found it right now. >> [laughter]

1383
01:20:11,720 --> 01:20:16,437
>> The use of blockchain to do
authentication is going to be central in

1384
01:20:16,520 --> 01:20:20,237
this world. Cuz otherwise,
where do you know the source?

1385
01:20:20,320 --> 01:20:22,837
Who invented this?
How did it actually happen?

1386
01:20:22,920 --> 01:20:24,697
>> Yeah, we'll should talk about it.

1387
01:20:24,780 --> 01:20:26,917
>> [laughter] >> We're
going to need source

1388
01:20:27,000 --> 01:20:30,317
authentication very, very much in this.

1389
01:20:30,400 --> 01:20:34,557
>> I was looking back at my notes
from our last conversation. We

1390
01:20:34,640 --> 01:20:37,157
covered a lot of ground. I recommend
everyone also listen to the last

1391
01:20:37,240 --> 01:20:41,437
conversation because we went so deeply
into your your background, your history,

1392
01:20:41,520 --> 01:20:44,997
the trajectory, different mentors.
It was a great conversation. I really

1393
01:20:45,080 --> 01:20:48,637
enjoyed it. And we spoke
a lot about Bill Joy. And

1394
01:20:48,720 --> 01:20:53,517
when in the notes at least, if I'm
remembering correctly, once he became a

1395
01:20:53,600 --> 01:20:56,717
venture capitalist, he would read
research papers, figure out who the best

1396
01:20:56,800 --> 01:20:59,557
authors or participants were, and then
call them and ask, "What's the most

1397
01:20:59,640 --> 01:21:01,637
interesting thing in your field?"

1398
01:21:01,720 --> 01:21:05,117
And I would love to hear

1399
01:21:05,200 --> 01:21:08,477
any examples of startups, bigger

1400
01:21:08,560 --> 01:21:11,717
companies, academics, particular teams

1401
01:21:11,800 --> 01:21:14,117
at universities, anyone or any groups

1402
01:21:14,200 --> 01:21:16,117
that stand out to you as doing very very

1403
01:21:16,200 --> 01:21:20,157
interesting things in the sphere of AI.

1404
01:21:20,240 --> 01:21:22,317
>> There are two well-known examples in

1405
01:21:22,400 --> 01:21:25,157
AGI. One is called DeepMind, which is in

1406
01:21:25,240 --> 01:21:29,437
the UK. It's owned by Google.
I've been heavily involved with them.

1407
01:21:29,520 --> 01:21:33,917
And another one is OpenAI,
which is the inventor of GPT-3,

1408
01:21:34,000 --> 01:21:36,877
uh which has a big
partnership with Microsoft.

1409
01:21:36,960 --> 01:21:42,197
Those two are probably the largest
focuses in these new areas.

1410
01:21:42,280 --> 01:21:45,917
So-called reinforcement learning,
so-called generative learning.

1411
01:21:46,000 --> 01:21:47,997
And there are a couple of other labs.

1412
01:21:48,080 --> 01:21:49,957
There's a series of university projects.

1413
01:21:50,040 --> 01:21:51,637
I've been funding

1414
01:21:51,720 --> 01:21:54,677
AI applied science in the leading

1415
01:21:54,760 --> 01:21:58,517
universities. And the AI science

1416
01:21:58,600 --> 01:22:00,357
goes something like this.

1417
01:22:00,440 --> 01:22:03,317
The physicists know how something works,

1418
01:22:03,400 --> 01:22:05,717
but our computers can't calculate it.

1419
01:22:05,800 --> 01:22:08,037
It's too complicated a calculation.

1420
01:22:08,120 --> 01:22:10,397
But they can make an approximation.

1421
01:22:10,480 --> 01:22:14,477
So often in science, a AI system is used

1422
01:22:14,560 --> 01:22:19,997
to approximate something good enough
so that we can understand how the system

1423
01:22:20,080 --> 01:22:22,917
works. The most obvious
area where this will

1424
01:22:23,000 --> 01:22:27,277
play out will be in biology.
Another friend of mine said that math is

1425
01:22:27,360 --> 01:22:29,877
to physics what AI will be to biology.

1426
01:22:29,960 --> 01:22:33,317
You needed math to understand how
physics worked. You'll need AI to

1427
01:22:33,400 --> 01:22:35,557
understand how biology works cuz it's so

1428
01:22:35,640 --> 01:22:38,437
incredibly complicated. We still don't

1429
01:22:38,520 --> 01:22:42,717
understand how to model a cell.
We still don't understand how the brain is

1430
01:22:42,800 --> 01:22:46,677
organized. There are so many basic
things that you would think as humans we

1431
01:22:46,760 --> 01:22:51,397
would want to know that have not been
calculable for us and that's where all

1432
01:22:51,480 --> 01:22:52,837
the great discoveries will be.

1433
01:22:52,920 --> 01:22:54,917
>> You know, I have
to share something just

1434
01:22:55,000 --> 01:22:58,517
because it's on this topic in a sense. I

1435
01:22:58,600 --> 01:23:02,757
have a set of papers from the late

1436
01:23:02,840 --> 01:23:05,517
Richard Feynman on which he drew the

1437
01:23:05,600 --> 01:23:09,677
Krebs cycle and I would just found that

1438
01:23:09,760 --> 01:23:14,917
crossover so to speak so fascinating
and we don't have to go deeply into a

1439
01:23:15,000 --> 01:23:18,557
Feynman but certainly one of the people
I've paid a lot of attention to.

1440
01:23:18,640 --> 01:23:22,757
Biology's incredibly complex and I
was thinking of the examples you've given

1441
01:23:22,840 --> 01:23:27,197
and thinking of say protein
folding or trying to identify

1442
01:23:27,280 --> 01:23:31,957
receptors and the shapes of receptors or
even structure the and modify the shapes

1443
01:23:32,040 --> 01:23:36,717
of receptors. The process
as you've already said is so

1444
01:23:36,800 --> 01:23:40,077
incredibly labor intensive and we've
tried all sorts of things to try to pick

1445
01:23:40,160 --> 01:23:42,077
up the slack using idle computers in a

1446
01:23:42,160 --> 01:23:43,717
distributed fashion

1447
01:23:43,800 --> 01:23:48,237
but once you have AI as a player on the

1448
01:23:48,320 --> 01:23:52,957
field, I mean that could change things
so fundamentally as you mentioned with

1449
01:23:53,040 --> 01:23:56,677
that one example. I think Halicin
was the example that you mentioned. It's a

1450
01:23:56,760 --> 01:23:59,437
big big deal. I wonder how AI may

1451
01:23:59,520 --> 01:24:04,197
augment natural prospecting
since nature often

1452
01:24:04,280 --> 01:24:07,877
times the molecules that we identify
in nature are just so beyond the wildest

1453
01:24:07,960 --> 01:24:09,717
imaginations of anyone who would start

1454
01:24:09,800 --> 01:24:15,517
from scratch with a say ground-up
synthetic approach. It raises so many

1455
01:24:15,600 --> 01:24:19,237
interesting questions.
>> It's worth noting that there was a

1456
01:24:19,320 --> 01:24:23,557
competition between two groups. One
a group called Rosetta at University of

1457
01:24:23,640 --> 01:24:24,917
Washington,

1458
01:24:25,000 --> 01:24:28,437
and another one in DeepMind to develop

1459
01:24:28,520 --> 01:24:31,197
proteins, protein folding algorithms.

1460
01:24:31,280 --> 01:24:35,717
And this year, both have reported their
results in the open source, and they've

1461
01:24:35,800 --> 01:24:37,997
published how proteins, the most common

1462
01:24:38,080 --> 01:24:41,677
proteins that are part of biology, fold.

1463
01:24:41,760 --> 01:24:45,157
The reason this is important is the way
that they fold determines the way they

1464
01:24:45,240 --> 01:24:47,357
interact with other cells.

1465
01:24:47,440 --> 01:24:49,917
And it is the basis, again, of drug

1466
01:24:50,000 --> 01:24:52,277
discovery, medicine, how our bodies

1467
01:24:52,360 --> 01:24:54,757
work, genetic expression, and so forth.

1468
01:24:54,840 --> 01:24:57,437
These proteins are super important.

1469
01:24:57,520 --> 01:25:01,957
These are the kinds of discoveries that,
if they were done by humans, would merit

1470
01:25:02,040 --> 01:25:03,597
Nobel Prizes.

1471
01:25:03,680 --> 01:25:06,397
And this is happening right now.

1472
01:25:06,480 --> 01:25:09,317
The way they do them is the same as I

1473
01:25:09,400 --> 01:25:12,277
described, which is they generate

1474
01:25:12,360 --> 01:25:17,277
many, many different candidates,
and they evaluate them using AI, and

1475
01:25:17,360 --> 01:25:21,797
then they choose the one that has the best
fit, most optimal outcome. And then

1476
01:25:21,880 --> 01:25:24,317
they release it, and then that technology
[snorts] will be used for the

1477
01:25:24,400 --> 01:25:28,277
next ones, and so forth. >> What
do you hope the impact of this book

1478
01:25:28,360 --> 01:25:31,117
will be? It's so all-encompassing in

1479
01:25:31,200 --> 01:25:35,397
some respects, this topic. What is the

1480
01:25:35,480 --> 01:25:39,997
the hope with this book in terms
of impact, or what people will do, or how

1481
01:25:40,080 --> 01:25:44,797
they will change their assumptions
or beliefs after being

1482
01:25:44,880 --> 01:25:48,997
exposed to it? >> 20 years
ago, when we started the

1483
01:25:49,080 --> 01:25:53,037
internet as you currently know it,
uh the social media world, many of the

1484
01:25:53,120 --> 01:25:54,717
other tools,

1485
01:25:54,800 --> 01:25:57,637
no one debated what the impact on

1486
01:25:57,720 --> 01:26:01,437
society would be. We were way busy

1487
01:26:01,520 --> 01:26:04,477
building these systems to great success

1488
01:26:04,560 --> 01:26:07,237
without understanding the impact.

1489
01:26:07,320 --> 01:26:10,877
Artificial intelligence
is much more powerful

1490
01:26:10,960 --> 01:26:13,397
than any of the technologies up till now.

1491
01:26:13,480 --> 01:26:18,357
Because, as I mentioned,
it's imprecise, it's emergent, it's

1492
01:26:18,440 --> 01:26:21,437
learning. and insightful.

1493
01:26:21,520 --> 01:26:25,557
We need to understand how we're going
to deal with these things ahead of their

1494
01:26:25,640 --> 01:26:29,157
development. Over and over again,
technologists build these technologies

1495
01:26:29,240 --> 01:26:32,757
without understanding how
they'll be used and misused.

1496
01:26:32,840 --> 01:26:37,557
The goal of the book is to lay
out the fundamental questions

1497
01:26:37,640 --> 01:26:41,717
that society has to decide around
these emergent technologies,

1498
01:26:41,800 --> 01:26:45,917
which will happen, and they
will happen over the next 5 to

1499
01:26:46,000 --> 01:26:48,997
10 years. If our book

1500
01:26:49,080 --> 01:26:51,597
turns out to be the index case

1501
01:26:51,680 --> 01:26:53,837
where after reading this book and after

1502
01:26:53,920 --> 01:26:59,157
its publication, people say,
"Holy crap. I've got to get ahead of

1503
01:26:59,240 --> 01:27:03,197
this. I've got to figure out a philosophy

1504
01:27:03,280 --> 01:27:07,717
around this. I have to figure out a way
where humans can coexist with these new

1505
01:27:07,800 --> 01:27:10,117
systems that doesn't drive humans crazy

1506
01:27:10,200 --> 01:27:12,637
and makes the world better not worse."

1507
01:27:12,720 --> 01:27:15,157
That's a great outcome from our book.

1508
01:27:15,240 --> 01:27:19,977
>> The age of AI and uh
what a powerhouse of

1509
01:27:20,060 --> 01:27:23,957
>> [snorts] >> the trio,
the co-authors involved. It's

1510
01:27:24,040 --> 01:27:26,357
tremendously important and I'm thrilled

1511
01:27:26,440 --> 01:27:29,077
that we've had a chance to

1512
01:27:29,160 --> 01:27:34,517
deep dive into so many facets of this
subject that has been of great interest

1513
01:27:34,600 --> 01:27:38,357
to me, but has come along with great
insecurity because I come at it from a

1514
01:27:38,440 --> 01:27:42,797
lay perspective. Before we
go, I must ask, how has it

1515
01:27:42,880 --> 01:27:45,277
been to start your own podcast?

1516
01:27:45,360 --> 01:27:48,797
>> I enjoyed it. It turns out
to be harder than I thought.

1517
01:27:48,880 --> 01:27:50,677
>> [laughter] >> Because I
actually had to prepare and I

1518
01:27:50,760 --> 01:27:54,597
had to get context and so forth, but it
has had an enough of an impact that I

1519
01:27:54,680 --> 01:27:57,077
will continue. >> Reimagine
with Eric Schmidt. You're an

1520
01:27:57,160 --> 01:28:00,757
excellent conversationalist.
I'm continually impressed. I don't need to

1521
01:28:00,840 --> 01:28:05,157
do much. That's the key to good
interviewing is pick your subject.

1522
01:28:05,240 --> 01:28:07,117
>> That's [laughter] right.
It's all about the subject, though.

1523
01:28:07,200 --> 01:28:10,997
>> I think it's all about
the the the It's a dual dual process.

1524
01:28:11,080 --> 01:28:14,277
>> But [laughter] I think it's
worth it's worth thinking about

1525
01:28:14,360 --> 01:28:17,117
in terms of what you and I do.

1526
01:28:17,200 --> 01:28:20,837
You're a fan of Richard Feynman.
When will there be a computer as smart as

1527
01:28:20,920 --> 01:28:26,157
Richard Feynman? And the answer
is a very long time from now.

1528
01:28:26,240 --> 01:28:29,477
And so we always like to focus on the
lawyers who will lose their jobs and the

1529
01:28:29,560 --> 01:28:33,557
politicians who will lose their jobs,
but that's not how it actually works.

1530
01:28:33,640 --> 01:28:35,917
What really happens is AI is going to be

1531
01:28:36,000 --> 01:28:39,517
used to eliminate repetitive jobs,

1532
01:28:39,600 --> 01:28:43,597
jobs which are boring and so forth.
I mentioned vision.

1533
01:28:43,680 --> 01:28:47,357
Most of the military's
activities are watching things.

1534
01:28:47,440 --> 01:28:49,797
I'd much rather have
the computer watching,

1535
01:28:49,880 --> 01:28:53,077
and then when there's an exception, say,
"Hey, something happened." and alert a

1536
01:28:53,160 --> 01:28:57,277
human to take a look at. It's a better
use of both the human and the computer.

1537
01:28:57,360 --> 01:29:00,877
And so the good news
is that what you do and

1538
01:29:00,960 --> 01:29:05,437
what I do is not going to be
replaced by computers soon.

1539
01:29:05,520 --> 01:29:08,677
>> [laughter] >> I'll take it.
I will absolutely take it

1540
01:29:08,760 --> 01:29:13,157
and I encourage people to read this book.

1541
01:29:13,240 --> 01:29:17,797
The Age of AI, pick it up. You can find
Eric on Twitter @ericschmidt and then

1542
01:29:17,880 --> 01:29:21,597
certainly @ericschmidt.com. We'll
link to everything including the book

1543
01:29:21,680 --> 01:29:25,277
and all resources, companies,
technologies mentioned in the show notes

1544
01:29:25,360 --> 01:29:28,480
at tim.blog/podcast.

1545
01:29:28,720 --> 01:29:33,637
Eric, thank you so much. This has
been extremely, extremely enjoyable and

1546
01:29:33,720 --> 01:29:36,517
educational for me. So,
I appreciate you taking the time.

1547
01:29:36,600 --> 01:29:40,807
>> Thank you, Tim. >> Hey guys,
this is Tim again. Just one

1548
01:29:40,890 --> 01:29:45,477
[music] more thing before you take off
and that is Five Bullet Friday. Would

1549
01:29:45,560 --> 01:29:49,277
you enjoy getting a short email from me
every Friday that provides a little fun

1550
01:29:49,360 --> 01:29:53,117
before the weekend? Between 1 and 1/2
and 2 million people subscribe to my

1551
01:29:53,200 --> 01:29:57,157
free newsletter, my super short
newsletter called Five Bullet Friday.

1552
01:29:57,240 --> 01:29:59,147
Easy to sign up, easy to cancel.

1553
01:29:59,230 --> 01:30:02,357
>> [music] >> It is basically
a half page that I send

1554
01:30:02,440 --> 01:30:06,277
out every Friday to share the coolest
things I've found or discovered or have

1555
01:30:06,360 --> 01:30:10,117
started exploring over that week. It's
kind of like my diary of cool things. It

1556
01:30:10,200 --> 01:30:14,517
often includes articles I'm reading,
books I'm reading, albums perhaps,

1557
01:30:14,600 --> 01:30:18,797
gadgets, gizmos, all sorts of tech
tricks and so on that get sent to me

1558
01:30:18,880 --> 01:30:23,477
[music] by my friends, including a lot
of podcast guests. And these strange

1559
01:30:23,560 --> 01:30:27,837
esoteric things end up [music] in my
field, and then I test them, and then I

1560
01:30:27,920 --> 01:30:32,597
share them with you. So, if that sounds
fun, again, it's very short, a little

1561
01:30:32,680 --> 01:30:36,037
tiny bite [music] of goodness before you
head off for the weekend, something to

1562
01:30:36,120 --> 01:30:40,077
think about. If you'd like to try it out,
just go to tim.blog/friday. [music]

1563
01:30:40,160 --> 01:30:43,520
Type that into your browser,
tim.blog/friday.

1564
01:30:44,120 --> 01:30:48,437
Drop in your email, and you'll get
the very next one. Thanks for listening.

1565
01:30:48,520 --> 01:30:52,217
This episode is brought to you by
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This episode is brought to you by Pique

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I've lived in China and Japan. I've done
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a ton of time and hassle.

1622
01:34:16,440 --> 01:34:20,357
So, Pique is offering 15% off their
Purity Teas for the very first time

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exclusive to you, my listeners. This is

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a sweet offer. Simply visit pique

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01:34:25,080 --> 01:34:28,877
tea.com/tim. [music] That's p i q u e t

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e a dot com forward slash tim. This
promotion is only available to listeners

1627
01:34:33,560 --> 01:34:37,437
of this podcast. That's pique tea.com/tim.

1628
01:34:37,520 --> 01:34:40,717
The discount is automatically applied
when you use that URL. You also have a

1629
01:34:40,800 --> 01:34:44,437
30-day satisfaction guarantee, so
your purchase is risk-free. One more time,

1630
01:34:44,520 --> 01:34:46,477
check it out. Pique tea.com/tim. That's

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01:34:46,560 --> 01:34:52,120
p i q u e t e a dot com forward slash tim.