Speaker 1: Bloomberg Audio Studios, podcasts, radio news.
Speaker 2: A master's and computer science from Stanford nineteen eighty eight.
Speaker 3: An artificial intelligence.
Speaker 2: I was a new partner at a law firm called
Speaker 2: lower Color and Pickering in Washington during National trade? What
Speaker 2: did you see in artificial intelligence?
Speaker 1: As on It's honored to be with you all, I
Speaker 1: wish I had been a behavioral economist. That was my
Speaker 1: only real big regret in life. And so what did
Speaker 1: I see in AI? Which is sort of related, what's
Speaker 1: the nature of intelligence? I think I saw a dream
Speaker 1: of understanding ourselves and our society a little better, and
Speaker 1: that was sort of the primary motivator. I will say
Speaker 1: that the AI that I studied was the equivalent of
Speaker 1: the sun goes around the earth field. So we had
Speaker 1: a fundamental theory in the nineteen eighties that was completely
Speaker 1: false and didn't work, but we didn't know it at
Speaker 1: the time. So me and many other people then fled
Speaker 1: to all kinds of other fields. And it's exciting now
Speaker 1: to see a new set of techniques really be transformative.
Speaker 1: And to Mike's reference on the news this week, you know,
Speaker 1: you know that I'm enamored with subscription models and now
Speaker 1: I've become more aware about tender offers and I like
Speaker 1: TV channels. So we're announcing today my tender offer for Bloomberg.
Speaker 1: We hope you will consider it appropriately. Your board members
Speaker 1: are willing to debate the transaction. But unfortunately, as you
Speaker 1: would suspect as a board member, that's all I can
Speaker 1: say on the news of the week.
Speaker 3: So you're not going to answer my bosses question, who's going.
Speaker 1: To I think it is all answered.
Speaker 2: So looking back on AI as you saw it then
Speaker 2: and whatever you saw then, and comparing it to now,
Speaker 2: I hear a range of things being said. As extreme
Speaker 2: as this is, as big an invention as the industrial
Speaker 2: evolution sometimes say is the discovery of fire. Are we
Speaker 2: overestimating or underestimating the effect generative A.
Speaker 1: I will have us, Well, let's think back thirty forty
Speaker 1: thousand years ago, and we're a bunch of Neanderthals and
Speaker 1: we're in the entrance to our cave, and you know,
Speaker 1: we've been the dominant human humanoid species for a couple
Speaker 1: hundred thousand years. And the two of us look down
Speaker 1: and we see Homo sapiens. We're like, look at those guys,
Speaker 1: they're so skinny. Hairless, but they're pitiful. But those guys
Speaker 1: were really intelligent, and ultimately those homelostapiens dominated the earth
Speaker 1: and killed off us neandervals. So I would say intelligence
Speaker 1: per species has been highly selected for, and that Homo
Speaker 1: sapiens intelligence has allowed us to become the dominant species
Speaker 1: on Earth because we use our intelligence to make tools
Speaker 1: and do other things. So I think it's a lot
Speaker 1: different than say, mechanizing muscle power. So if you think
Speaker 1: of bulldozers and how did that transform you know, society,
Speaker 1: it did a lot, but it did it over one
Speaker 1: hundred years. And although muscles are important, they're not the
Speaker 1: core human attribute. Thus the dislocation of the end with
Speaker 1: the Neanderthals, which were much stronger than humans. So if
Speaker 1: AI develops to actually be super intelligence, then it will
Speaker 1: be a lot more profound, I think, than anything else,
Speaker 1: and that we will have actually real species threats because
Speaker 1: the AI will keep getting smarter and smarter and smarter
Speaker 1: without limit. A natural selection works quite slowly in terms
Speaker 1: of making humans more intelligent, so then we have to
Speaker 1: sort of say, okay, how fast and how you know?
Speaker 1: Will the computer is really thank Obviously when we all
Speaker 1: use AI as consumers we can find. You know, it's
Speaker 1: pretty miraculous in some cases, but in other cases it's
Speaker 1: not very effective. But you know, we're understanding more and
Speaker 1: more of the techniques. And again, one theory is it'll
Speaker 1: be like Moore's law and just AI will get better
Speaker 1: and better and better. But the other theory is it's
Speaker 1: sort of like the War on cancer, where cancer developed
Speaker 1: over a very long time. It has lots of different etiologies,
Speaker 1: and we keep coming up with a solution for one
Speaker 1: cancer but not another, and our overall progress and society
Speaker 1: against cancer has been you know, pretty steady but flat.
Speaker 1: It definitely not exponential, and so you know, it may
Speaker 1: be that as AI gets better, it hits various walls
Speaker 1: and that we've got some time to deal with it.
Speaker 1: Or it may be that it stays on this exponential
Speaker 1: So we're just going to have to watch. But I
Speaker 1: think we need to be prepared for it to be
Speaker 1: on the exponential, in which case we're going to have
Speaker 1: a lot of societal stress over the next twenty years.
Speaker 2: So your analogy is very helpful, but a little disturbing
Speaker 2: because I don't see many Neanderthals around anymore.
Speaker 3: Right, we have a lot of.
Speaker 2: Homo saviens in your analogy, What can we do to
Speaker 2: make sure that we survive, that that this thing we're
Speaker 2: creating doesn't become so smart and perhaps I can have
Speaker 2: our best interests so are well.
Speaker 1: It's a big challenge. It's hard to slow down because
Speaker 1: unlike chemical weapons, like we're kind of in a war
Speaker 1: with a West in Russia and yet no one using
Speaker 1: chemical weapons and no one's using nuclear weapons. So even
Speaker 1: in this incredible state of war, we're able to put
Speaker 1: some limits on what happens. The problem with AI is
Speaker 1: it's very continuous. You know, your thermostat is an AI thermostat.
Speaker 1: So there's no good way or even the major powers
Speaker 1: to agree not to use AI because it's so integrated
Speaker 1: through everything else that we do. So there's no real
Speaker 1: practical scenario to take a break as human society, even
Speaker 1: if we could get the politics to work on that.
Speaker 1: So instead we're in the situation where we in America
Speaker 1: better well damn win the race, and so everyone acknowledges that,
Speaker 1: and so all the companies are going full out, both
Speaker 1: for their own you know, competitive reasons, and so you know,
Speaker 1: it is a race, hopefully to the top of what
Speaker 1: can AI do for us? And there will be amazing
Speaker 1: positive scenarios. You know, all kinds of medical yours, all
Speaker 1: kinds of productivity. I certainly six years ago, AI was
Speaker 1: very good at image of analysis. That was one of
Speaker 1: the kind of workloads that it first got good at,
Speaker 1: and in particular in radiology, it got significantly better than
Speaker 1: the typical radiologists pretty quickly and has been better than
Speaker 1: the typical radiologist for at least five years. And so
Speaker 1: I would say, you know, weddings and with friends who
Speaker 1: are radiologists, what's good that your kids are not going
Speaker 1: in the business, because radiology is going to be the
Speaker 1: first profession that's wrecked by AI. Good for humanity, but
Speaker 1: not good for radiologists. Well, what happened is as radiology
Speaker 1: got better because of AI analysis that helped radiologists, the
Speaker 1: price of scans went down, and the number of scans
Speaker 1: turned out to be hugely elastic. Now you walk in,
Speaker 1: you've got a cough, boom, you get a scan, okay.
Speaker 1: And so what's happened now is there's about thirty four
Speaker 1: thousand radiologists in the US, which is a shortage. We
Speaker 1: now have a labor shortage of radiologists okay, by about
Speaker 1: five thousand. So it's an incredible story. Of of course,
Speaker 1: elasticity of demand to improve lives, i e. More scans,
Speaker 1: and so we may well see with AI that it
Speaker 1: makes Wall Street analysts more productive and makes software engineers
Speaker 1: more productive, and that in fact the elasticity and that
Speaker 1: we grows and that we grow the economy. And when
Speaker 1: people ask, you know, we're spending collectively as an industry
Speaker 1: at half a trillion dollars on AI data center, how
Speaker 1: is that ever going to get paid back? Well, you know,
Speaker 1: add one or two points to GDP growth and it
Speaker 1: gets paid back fast. So you know, I don't want
Speaker 1: to like guarantee that it's always going to be like radiology.
Speaker 1: I do think software engineering is particularly fascinating because all
Speaker 1: the major AI companies are working on it, and so
Speaker 1: it is the white collar canary in the coal mine.
Speaker 1: If software engineering engineering jobs go down a lot over
Speaker 1: the next five years, then that's probably going to happen
Speaker 1: to law on architecture and many other things. If in fact,
Speaker 1: because of the increased productivity, people are building a lot
Speaker 1: more software, sort of the radiology example, then I think
Speaker 1: in many professions we will see a big expansion and
Speaker 1: we can be more confident of the high productivity. None
Speaker 1: of that really answers the long term question that you asked,
Speaker 1: which is how are we not the Neanderthals? So I
Speaker 1: think reasonable chance high productivity rather than mass unemployment. Okay,
Speaker 1: but then ultimately, what if they're smarter and smarter and
Speaker 1: smarter than us. We're going to have to find ways,
Speaker 1: and I don't know what they are, to both continue
Speaker 1: to insist on alignment, and that's where you train the
Speaker 1: AIS to care about human beings so they are aligned
Speaker 1: with our values. Okay, but if somebody doesn't train, somebody
Speaker 1: programs their AI to try to take over the world,
Speaker 1: we're going to have to enlist the other AIS on
Speaker 1: our defense to protect us. Okay. So you know there's
Speaker 1: a number of scenarios out there, and probably for ten
Speaker 1: twenty years, we're not going to know how serious the
Speaker 1: threat is, but we will have tools. It's not just
Speaker 1: that the AI biological species we have been selected for
Speaker 1: dominance to try to grow our species. So AI is
Speaker 1: not naturally trying to expand, not naturally it could be
Speaker 1: programmed for that, but it can be also programmed to
Speaker 1: keep humans on top. So it's not as scary as
Speaker 1: a super powerful human, which we all kind of into it.
Speaker 1: A super powerful human would be hard to hold back
Speaker 1: from taking over the world. It's not as dire as that.
Speaker 2: Insofar as we do make progress on trying to reshape
Speaker 2: general of AI in a more positive direction. Does that
Speaker 2: come from outside the industry or inside the industry? Does
Speaker 2: that come from government regulation and agreement or does it
Speaker 2: have to come from inside? Because as I talk to
Speaker 2: many people in the business, they're much more focused on
Speaker 2: the race you talk about than they are on the
Speaker 2: safety part.
Speaker 3: They don't want to get slowed down in that.
Speaker 2: I mean, you're on the border anthropic, which I know
Speaker 2: is trying to make a move in the other direction.
Speaker 2: But can we do it from the outside or does
Speaker 2: the industry itself somehow have to internalize the risk.
Speaker 1: Well, I think lots of the industry is working on it.
Speaker 1: So there's different sides of safety. So there's when you're
Speaker 1: treating AI like a counselor and you know it, you
Speaker 1: know helps you tie a news that's not a good thing.
Speaker 1: And so those cases across the industry are getting you know,
Speaker 1: more and more watched for it eliminated, So there's inevitable
Speaker 1: safety bumps as any technology grows, so then there's more
Speaker 1: macro safety, like none of the major AIS can be
Speaker 1: used to design chemical weapons or biological weapons. But those
Speaker 1: defenses in the AIS you know, aren't perfect, and we
Speaker 1: have to constantly and best in them to prevent people
Speaker 1: from using this super powerful technology plus some crisper to
Speaker 1: do some really bad things. So there's active work across
Speaker 1: the whole industry on those scenarios. Because from a commercial standpoint,
Speaker 1: nobody wants their AI brand to be the brand that
Speaker 1: develops some bad virus, so there is an incentive there
Speaker 1: to protect against the negative cases. But the sort of
Speaker 1: big long term case is that the AIS get so
Speaker 1: smart that then we have to do things to make
Speaker 1: sure that they are aligned with human values, that they
Speaker 1: are programmed so that success is humans flourishing.
Speaker 3: Give us your view, but we are likely to see
Speaker 3: the biggest effect. You mentioned biomedicine. You mentioned computer software progners.
Speaker 3: Let's talk turning the news.
Speaker 2: Today with the deal between Disney and Open AI and
Speaker 2: the entertainment space that you know well, I mean you
Speaker 2: manage transition from my perspective, least from more traditional TV
Speaker 2: cable broadcast.
Speaker 3: Through to streaming.
Speaker 2: What does the transition look like from streaming through the AI.
Speaker 1: So just as an example, we can look at video
Speaker 1: creation storytelling and sort of say, let's look at what
Speaker 1: AI is going to do and the mechanics of generating
Speaker 1: video and frankly, whether that's a news channel trying to
Speaker 1: illustrate a concept or entertainers trying to do amazing special effects,
Speaker 1: we're going to have higher quality special effects and that
Speaker 1: will shift to be AI generated instead of manually generated
Speaker 1: with sort of overseas visual effects companies. So there is
Speaker 1: a shift there, But the core thing of storytelling is
Speaker 1: very hard. How do you do long form character development,
Speaker 1: creating tension, resolving tension. That's not a case that the
Speaker 1: AI does well today. Eventually, ten twenty years, the AI
Speaker 1: may win the Booker Prize, okay, and then if it does,
Speaker 1: it's going to be able to do a movie script all. So,
Speaker 1: but for now, the AI is really helping on sort
Speaker 1: of industrial aspects of what we do, like an amazing
Speaker 1: visual effects shot, and so it's you know, important, and
Speaker 1: we want to stay on the front as Disney does,
Speaker 1: but it's not doing the core thing, which is which
Speaker 1: story is going to captivate human attention.
Speaker 2: I'm not sure it says much about my job, about
Speaker 2: whether I keep my job in the AI world, because
Speaker 2: there's a lot of things that are done on television
Speaker 2: with news and other things that frankly, are not creating
Speaker 2: the next Lion King.
Speaker 1: Well, I think interpreting the world in your case is
Speaker 1: a broad general wisdom, and so I think you'll have
Speaker 1: a relatively longstanding role in your success.
Speaker 3: Given my age, I'm good.
Speaker 1: Given your age, you're good. But you know, it is
Speaker 1: a very big change. Again, you know, people want to
Speaker 1: compare it to the Industrial revolution that happened over two
Speaker 1: hundred years. This is going to happen over ten or twenty.
Speaker 1: And it might be that what's caused political polarization in
Speaker 1: the last decade or two is rate of change. So
Speaker 1: think about you know, since NAFTA, you know, sort of
Speaker 1: the rise of globalization, the redefining of marriage equality, immigration,
Speaker 1: all kinds of change in society. And one view is
Speaker 1: enough of our fellow Americans, it's just too much, and
Speaker 1: it radicalizes them and they're willing to vote for things
Speaker 1: they wouldn't normally vote for. And if that's fundamentally what's
Speaker 1: going on in US society as well as you know,
Speaker 1: Brexit and a couple other places. Then we're in for
Speaker 1: a pretty big storm because the rate of change is
Speaker 1: not going to slow down. The rate of change of society,
Speaker 1: you know, partially or maybe largely driven by AI, is
Speaker 1: going to be large. And so that may be that
Speaker 1: you know, how everyone today is nostalgic for Reagan, you know,
Speaker 1: there may be a day when we're nostalgic for Trump.
Speaker 1: That our polarization has really continued to increase because the
Speaker 1: rate of change has continued to increase. So that's why
Speaker 1: I think it's so important that leaders like all of
Speaker 1: you are thinking about how do we build bonds, how
Speaker 1: do we have people of Americans care about each other
Speaker 1: so that we can keep the society coherent and caring
Speaker 1: despite the rapid amounts of change in generated by technology.
Speaker 2: I want to come back to something you referred to
Speaker 2: just explore a bit more, and that is how are
Speaker 2: we going to pay for it? There is so much
Speaker 2: money going into data center's investment right now, and to
Speaker 2: something said, I think it's been supporting the markets because
Speaker 2: there's been so much investment.
Speaker 3: How do you get a.
Speaker 2: Return on that investment without laying off an awful lot
Speaker 2: of people.
Speaker 1: With GDP growth, so you can either automate away the job.
Speaker 1: That's one theory, and the other is that people will
Speaker 1: produce more and I'm sure it'll be a mix, but
Speaker 1: efficiency often generates more growth. I mean, we did the
Speaker 1: radiology example, so it's sort of that at larger scale.
Speaker 1: So the way we pay for it is more GDP growth.
Speaker 2: You can do GDP growth with fewer people. And so
Speaker 2: what happens to the people who are out of work
Speaker 2: or have to take much more menial jobs than they
Speaker 2: had before because it's the knowledge workers.
Speaker 1: Well, I think it's a great question. Compared to globalization.
Speaker 1: Probably this is a room full of globalists. We believe
Speaker 1: in the benefits of trade, and yet despite that that
Speaker 1: really did deliver in terms of the overall economy. There
Speaker 1: was enough dislocation and enough of the countries that our
Speaker 1: politics has been shifted. So I think there probably will
Speaker 1: be things like that because of AI, But at least
Speaker 1: it's not again, it's not a mass layoff scenario. Most likely,
Speaker 1: it's much more likely that there's a growth response. We
Speaker 1: also see significant GDP growth, you know, increased beyond what
Speaker 1: we typically see because of the productivity of AI.
Speaker 2: What I hear from you is AI has enormous potential,
Speaker 2: a lot of it for good, some of for decidedly
Speaker 2: not good. It's very complicated, it's coming very very fast.
Speaker 2: Where will the leadership in directing AI come from? Are
Speaker 2: there people who understand this, who get it, who have
Speaker 2: the right values, who can help us go in the
Speaker 2: right direction, particularly given how fast it's coming.
Speaker 1: I would say that's an emerging area. I mean, I
Speaker 1: think this was likely to be a big political issue
Speaker 1: in the next couple cycles because many Americans will be
Speaker 1: concerned about world changing too fast and too much, and
Speaker 1: I think it's up to our politicians to sort of
Speaker 1: understand that and channel it in some productive way. There's
Speaker 1: leaders in the industry like Jeffrey Hinton that spends full
Speaker 1: time now on these how do we keep humans at
Speaker 1: the center of the system. So there definitely are emerging
Speaker 1: leaders in that way. But again it's a new area.
Speaker 1: Like you know, nuclear energy you know, or other DNA
Speaker 1: for long time is very controversial.
Speaker 2: Timing is everything, and it comes. The develops you talk
Speaker 2: about come at a time when there's a decided rise
Speaker 2: in populism in the United States as well as in
Speaker 2: much of the Western world. Right now, the early things
Speaker 2: I'm hearing this but on political from the people is
Speaker 2: it increases our energy costs and it reduces our jobs.
Speaker 2: We're against it, and some politicians are showing signs now
Speaker 2: of trading on that and saying we should be against
Speaker 2: Actually data centers, we should be against them. How do
Speaker 2: you put together the rise of populism with the likely
Speaker 2: effects of general AI.
Speaker 1: Well, you know, the heart of democracy is we're going
Speaker 1: to live in this country together and we're going to
Speaker 1: have different views, and so you want a system that's
Speaker 1: not civil war to work out those views. And I
Speaker 1: think I think a lot of people will have those concerns.
Speaker 1: They'll be those effects, and we have to take them
Speaker 1: thoughtfully and seriously. And arguably during the era of globalization,
Speaker 1: there was sort of lip service to retraining, but we
Speaker 1: didn't really understand or take seriously the devastation of a
Speaker 1: lot of communities. So I think, you know, the elites
Speaker 1: in this room as an example of do a better
Speaker 1: job at that, which is, you know, where is AI
Speaker 1: really providing benefits to people's healthcare, to their day to
Speaker 1: day lives, and if we can do that, then there's
Speaker 1: more toleration of the dislocation, which is as you said,
Speaker 1: cost of electricity, data centers, those things.
Speaker 3: Are we over investing.
Speaker 1: It's unlikely, but you know it's definitely possible. But again,
Speaker 1: you know the Telkom boom in two thousand, I mean,
Speaker 1: you know it's a slight over investment, you know, so
Speaker 1: it could. But if you look at the in the
Speaker 1: in the telecom one, everyone got so excited about the
Speaker 1: Internet that they forward invested and were disappointed for a while,
Speaker 1: but ultimately the Internet really did deliver. But if you
Speaker 1: look at the mobile phone, it never had a bubble.
Speaker 1: It came out and just grew and grew and grew
Speaker 1: in impact. So you can get both things that live
Speaker 1: up to the hype and things where the hype gets
Speaker 1: bigger than the actual technology in the short term. And
Speaker 1: you know, the market's a good way to work that out.
Speaker 3: On AI, does it matter who gets their first?
Speaker 2: I mean, is this like beta and VHS where the
Speaker 2: point that gets their first gets to really set this up.
Speaker 1: You're in countries, it matters.
Speaker 3: A lot, So US versus China take that correct.
Speaker 1: If you're talking companies you know, I care a lot
Speaker 1: because I'm on the board of Entropic. But from a
Speaker 1: society standpoint, it probably just matters that the technology is
Speaker 1: developed and deployed in great ways.
Speaker 3: But it does matter in the US versus China.
Speaker 1: Yeah, absolutely. I mean, if another country doesn't have to
Speaker 1: be China right gets ahead of us. There are significant
Speaker 1: scenarios referred to in a class of the singularity where
Speaker 1: the AI gets so good that it rights the next
Speaker 1: DAI and that AI is much better, and then that
Speaker 1: writes the next day I And so you know, being
Speaker 1: first by even just a year gives you an enormous advantage.
Speaker 1: So that's the exponential. But again that's a theory that's
Speaker 1: not yet proven, but even its slight possibility means we
Speaker 1: better don't get there first. And I think we're on
Speaker 1: a good bathroom.
Speaker 3: Well that's my question.
Speaker 2: If that were your one goal in the United States,
Speaker 2: what are the policies that get you there? What are
Speaker 2: the things we need to do or avoid doing to
Speaker 2: make sure we're as competitive as possible.
Speaker 1: I think we're doing a pretty good job on that.
Speaker 1: I mean, there's you would push the edge on light regulation,
Speaker 1: make it easy to build data centers. You know, I
Speaker 1: think the government's done open field running, so I can't
Speaker 1: think I don't I don't think we need like a
Speaker 1: government investment program or something like that. So there's a
Speaker 1: lot of progress, and we are ahead of our competitors
Speaker 1: as far as we can tell. And again, we don't
Speaker 1: want to make it zero some because you'd like, just
Speaker 1: like we did in globalization, we would like to bring
Speaker 1: the rest of the world along with us so that
Speaker 1: we've got a stable we have less likely chance of war.
Speaker 1: So I mean, but that's happening.
Speaker 3: Okay, So let's talk about what you really love.
Speaker 2: This has been very entertaining snow powder and mountain resorts.
Speaker 3: This is what you really love, you know.
Speaker 1: I have a slight addiction to skiing, and then retiring
Speaker 1: from Netflix, rather than do a sailboat or something like that,
Speaker 1: I decided to take over a ski resort and try
Speaker 1: to make another Yellowstone Club, but one that was sort
Speaker 1: of more artists, Dick, and I'm a visitor else don
Speaker 1: not a member. But it's a great place. But to
Speaker 1: do something like that, yeah, So I've been learning the
Speaker 1: real estate business. It's a real turnaround. It's a very
Speaker 1: different thing for me. But when you've got overwhelming capital
Speaker 1: relative to our project, things are pretty easy. So I
Speaker 1: can't say it's it's it's gonna work out great for customers.
Speaker 1: I'm not sure it'll be the best investment I ever made,
Speaker 1: but I do love it. But you get to snowboard
Speaker 1: a lot, but I get to snowboard all winter like
Speaker 1: Powder Mountain. Utah's fantastic place.
Speaker 3: Check it out. Thank you, thank you so much.
Speaker 1: Really what an honor. Thank you all, thank you all.