Speaker 1: Bloomberg Audio Studios, podcasts, radio news Now.
Speaker 2: Earlier this month, an AI model called Manus went viral
Speaker 2: for its apparent ability to act more independently than AI chatbox.
Speaker 1: Now.
Speaker 2: The development of the so called artificial intelligence agents have
Speaker 2: raised concerns that they will erode human ability to think.
Speaker 2: But Read Hoffman, the Lincoln co founder, Microsoft board member
Speaker 2: and Greylock partner, thinks the opposite. Now He's just published
Speaker 2: a book in which he basically argues that aisystems gain
Speaker 2: greater abilities, they will enhance human agency, hence the book's
Speaker 2: title Souperagency? What could possibly go.
Speaker 1: Right with our AI?
Speaker 2: Feature? And read is here with me? Thank you so much,
Speaker 2: Read Hoffen for joining us. I mean, this is the
Speaker 2: fresh of breath air because there is a lot of
Speaker 2: concern and a lot of worry that AI takes over
Speaker 2: the computers will be in charge and will basically stop
Speaker 2: using our critical thinking.
Speaker 1: Yes, but actually, in fact, if anyone plays with AI today,
Speaker 1: it is the most amazing education technology.
Speaker 3: We have created in human history.
Speaker 1: If you want to learn anything, I use it to
Speaker 1: learn everything from quantum mechanics to like, huh, I wonder
Speaker 1: what cooking souved in this way looks like it's everything.
Speaker 2: But I guess the concern is that, you know, especially
Speaker 2: people that go into a first time job, or students
Speaker 2: or like you know, college kids don't use their critical
Speaker 2: thinking anymore. Because if you just go into chat box
Speaker 2: and say write me a song, it with this, this,
Speaker 2: and this, it does it for you.
Speaker 1: Well, it definitely can do a bunch of things for you,
Speaker 1: but that can help you elevate your game.
Speaker 3: Right.
Speaker 1: So it's a little bit like if you were just
Speaker 1: copying Wikipedia as handing in your essay, sure you could
Speaker 1: do that, but actually, in fact you should use it
Speaker 1: to inspire you to make you think better, to say, hey,
Speaker 1: like for example, when I was writing Superagency, I would
Speaker 1: put in sections and say, how at a history of
Speaker 1: technology specialists critique what I've said, and then I understand
Speaker 1: it and I can decide whether or not I change
Speaker 1: your editings or and therefore the book gets better.
Speaker 2: So I read and reduce cognitive capabilities. Right, this is
Speaker 2: a big concern that we stop thinking, that we think less,
Speaker 2: that we think differently.
Speaker 1: Well, I think it makes it just like all technology,
Speaker 1: you can approach it being lazy, and so if you
Speaker 1: just say, okay, I'm going to outsource it, just like
Speaker 1: for example, I'm going to say, whatever the first search
Speaker 1: result on Google is, that's the answer. And if you
Speaker 1: do it that way, then of course that doesn't help
Speaker 1: you extend. But if you do anything in terms of
Speaker 1: having it be a dialogue with you, having it extend
Speaker 1: your capabilities asking a question, getting an answer, asking another question,
Speaker 1: then it it greatly amplifies your capabilities.
Speaker 2: How do you get rid of the biases, because if
Speaker 2: you have too many biases then it excus of course democracy.
Speaker 1: Well, so all of the major AI labs are trying
Speaker 1: to get it as kind of call it unbiased as possible. Now,
Speaker 1: within human perspective and human knowledge, there's always some things
Speaker 1: a bias.
Speaker 3: We're always learning.
Speaker 1: Like if we kind of look at human beings fifty
Speaker 1: years ago and we are fifty years past and we
Speaker 1: look at them and say, oh, they were biased about this,
Speaker 1: I'm certain humans fifty years from now will be looking
Speaker 1: at us the same way. So it's an ongoing process
Speaker 1: with us as well as the technology.
Speaker 2: Is there anything that worries you about AI?
Speaker 1: The primary thing that worries me is I call AI
Speaker 1: the cognitive industrial Revolution. It's both for the upside, which
Speaker 1: is this whole society we live in, middle class education,
Speaker 1: medicine all comes from the Industrial Revolution. That same amplification
Speaker 1: is coming, but the transitions are difficult. So the thing
Speaker 1: that primarily worries me is to say, look, we're going
Speaker 1: to have to navigate this challenging transition, just like the
Speaker 1: Industrial Revolution was a challenging transition.
Speaker 3: But that's how we have.
Speaker 1: Our children on our future generations be prosperous and have
Speaker 1: amazing societies.
Speaker 3: And so that's the challenge we need to rise to.
Speaker 2: So what's the right way of either designing AI or
Speaker 2: designing safeguards for AI?
Speaker 1: Yeah, well, part of it, there's kind of a two
Speaker 1: part audience for super agency. One is the people who
Speaker 1: are AI fearful or concerned to help them become AI curious.
Speaker 1: But it's also for technologists, which is design for human agency,
Speaker 1: designed for increasing human agency.
Speaker 3: That should be your.
Speaker 1: Design principle and fundamental And the book is also I
Speaker 1: hope helpful for them.
Speaker 2: So read this is basically putting the human you know,
Speaker 2: at the center still of everything. So how they fit
Speaker 2: into the next decade?
Speaker 1: Yeah, well, AI, I think can be amplification intelligence, not
Speaker 1: just artificial intelligence and that amplification the superpowers that we get,
Speaker 1: and it's not just part of super agency. Is if
Speaker 1: you hit a superpower, that helps me too. That's how
Speaker 1: we have superagency together, as long as.
Speaker 2: It's democratic and everybody has it or is that a
Speaker 2: question for in a second phase?
Speaker 1: Well, I think one of the good things about it,
Speaker 1: And that's part of the reason why the first chapter
Speaker 1: is about humanity enters.
Speaker 3: The chat at chat GBT.
Speaker 1: When we build technologies for hundreds of millions and billions
Speaker 1: of people, that's that's broadly inclusive. So that your uber
Speaker 1: driver has the same iPhone that Tim Cook has. That's
Speaker 1: the kind of inclusion that we're targeting.
Speaker 2: Read I mean, I guess evolution is not necessarily progress
Speaker 2: full stop. So how do you make sure that this
Speaker 2: means progress for the majority of humans?
Speaker 3: Well, so I think.
Speaker 1: Look, I think as we iterate and we participate, we
Speaker 1: make progress. And for example, even though you say, well,
Speaker 1: we have a whole bunch of cars and that creates
Speaker 1: climate change, the cars also create our industrial society. And
Speaker 1: by the way, the way that we tackle climate change
Speaker 1: is we add carburetor emissions and we add you know,
Speaker 1: we new kinds of clean energy and we do evs
Speaker 1: and so you know, I tend to be very you know,
Speaker 1: as we do iterative deployment and as we bring humanity
Speaker 1: into the loop, I tend to think we do make progress.
Speaker 1: Now I think again, you make better progress by having
Speaker 1: the right kind of design principles, by accepting criticism.
Speaker 3: By talking about it.
Speaker 1: So, you know, I describe myself as a bloomer, which
Speaker 1: is not that technology is just great. It's technology engaging
Speaker 1: with people as great.
Speaker 2: But it also depends on the people in charge. What
Speaker 2: do you think of Sam Altman's performance so far in
Speaker 2: leading open AI?
Speaker 1: Well, so I think, Look, I think Sam's great contribution
Speaker 1: to humanity will be open AI. And that's what having
Speaker 1: done a number of amazing things before and done amazing
Speaker 1: investments like Confusion and all the rest. And I think
Speaker 1: that his ability to think very big and to have
Speaker 1: bet very hard on this, you know a little bit
Speaker 1: of technological thesis of scale compute and scale learning systems
Speaker 1: is what matters. And that's why open ai has brought
Speaker 1: this current revolution to us. And it's these machines learn
Speaker 1: and they learn things that we help them learn and
Speaker 1: help teach them.
Speaker 2: Is there someone I know You've also had your differences
Speaker 2: with Elon Musk. Who's the person in the space that you,
Speaker 2: if not admire or listen to the most well.
Speaker 1: Sam Altman is definitely one of them. Kevin Scott at
Speaker 1: Microsoft is another, Dario Ahmadi ananthropic as another, James Miyika
Speaker 1: at Google as another. I mean, I think part of
Speaker 1: the thing that's very important about making AI for humanity
Speaker 1: is people who listen to others and talk to others
Speaker 1: and accept criticism. And I think that's one of the
Speaker 1: things that all of these people are very good at.
Speaker 2: Do you need to regulate it or is it something
Speaker 2: that you need to see how it runs and then
Speaker 2: think about regulating afterwards.
Speaker 1: So I think what you do is you start with
Speaker 1: the absolute minimum regulation you could do for the things
Speaker 1: that could be really bad, not for oh, look it
Speaker 1: might have a biased picture or might have a bias statement,
Speaker 1: like we can iterate, we can fix those as we're going.
Speaker 2: Really bad is what people taking over planes to crash,
Speaker 2: the things.
Speaker 1: Like that, you know, cybercrime, et cetera. Regulate for that
Speaker 1: right and then do iterative deployment. And by the way,
Speaker 1: even though they deployment, you eventually get to fear the regulations. So,
Speaker 1: for example, if you try to make everything perfect with
Speaker 1: cars before you put them on the road, we'd never
Speaker 1: have cars. So you put them on the road and
Speaker 1: you go, oh, this for bumpers, this window wipers, this
Speaker 1: for and occasionally, like the market doesn't want seat belts,
Speaker 1: the car manufacturers all want seat belts, and then of
Speaker 1: course the regulators going to say, oh no, no seat
Speaker 1: belts is good, We're going to add those.
Speaker 2: I mean, if you regulate for things, I mean terrorism
Speaker 2: is bad actors, bad state actors, or so it's I mean,
Speaker 2: how do you regulate it unless you have to protect yourself.
Speaker 2: So it's basically finding the technology.
Speaker 1: That blocks them. Well, I think it's the regulation is
Speaker 1: if you're releasing the technology to the general public, which
Speaker 1: could be to the bad actors as well, you're doing
Speaker 1: red teaming and safety, you're putting the right security measures
Speaker 1: to make sure that you're not bleeding the technology to
Speaker 1: rogue states, terrorists, et cetera, that you have a safety
Speaker 1: plan that if you go, Okay, why is the technology
Speaker 1: I'm building if it does leak or anything else, why
Speaker 1: will it.
Speaker 3: Still be safe?
Speaker 1: And how do we continue to have the technology that
Speaker 1: makes anything that's in the wild as safe as possible.
Speaker 2: On Nilon must Do you think he has too much
Speaker 2: power being so close to the president.
Speaker 1: Well, so, look, I think he's a celebrated entrepreneur.
Speaker 3: But I think that.
Speaker 1: Governments are not companies, like, for example, risking a company
Speaker 1: like for example, to say, oh, our ten rockets blow up,
Speaker 1: who cares, it doesn't matter the financial system of a
Speaker 1: country blows up. That's the cultural revolution that's terrible. So
Speaker 1: you actually have to say we take less risk here,
Speaker 1: even at the price of some inefficiency, because it's more
Speaker 1: important for us to not have things blow up.
Speaker 2: Do you worry that things are going too quickly with
Speaker 2: the Trump administration, Well, I.
Speaker 1: Worry that very bad risks are being taken at speed.
Speaker 3: Is not a problem. Risks are a problem.
Speaker 1: And you know, for example, it's like, well, we're just
Speaker 1: going to fire a whole bunch of people. Oh oops,
Speaker 1: we fired a whole bunch of nuclear safety inspectors. Like
Speaker 1: that's the kind of thing that's taking risks that is unwarranted.
Speaker 3: Read.
Speaker 2: I also want to talk to you about China because
Speaker 2: Deep Sea kind of got everyone at the edge of
Speaker 2: their seat. But where do you have a good understanding
Speaker 2: about where China is on AI.
Speaker 3: I have a reasonable understanding.
Speaker 1: I do a fair amount of talking to various people
Speaker 1: in China in order to make sure. Part of the
Speaker 1: thing that when last year I was going around saying
Speaker 1: there was actually an economic race with AI between the
Speaker 1: West and China, people are like, oh, no, you're overblowing
Speaker 1: that because you just simply don't want.
Speaker 3: To be regulated.
Speaker 1: And I think with deep Seak and everything else, we
Speaker 1: see that that race is there, and the Chinese government
Speaker 1: has said that they want to be you know, AI leaders,
Speaker 1: like leading the world.
Speaker 3: By twenty thirty. I think the race is on.
Speaker 1: I think it's very important for US and our industries
Speaker 1: to actually in fact be winning.
Speaker 2: Is this an r Is this the new arms race?
Speaker 1: Well, I don't call it an arms race because it's
Speaker 1: primarily an economic race. There is arm stuff components with it,
Speaker 1: but yes, it is the economic race.
Speaker 2: Read thank you so much for joining us. That was
Speaker 2: Reid Hoffman LinkedIn co founder Gray Luck, partner and of
Speaker 2: course author of Super Agency. It's a good book. It's
Speaker 2: well written, and it's to the point