back to indexErik Brynjolfsson: Economics of AI, Social Networks, and Technology | Lex Fridman Podcast #141
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The following is a conversation with Eric Brinjalson.
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He's an economics professor at Stanford
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and the director of Stanford's Digital Economy Lab.
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Previously, he was a long, long time professor at MIT
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where he did groundbreaking work
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on the economics of information.
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He's the author of many books,
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including The Second Machine Age
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and Machine Platform Crowd, coauthored with Andrew McAfee.
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Quick mention of each sponsor,
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followed by some thoughts related to the episode.
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Ventura Watches, the maker of classy,
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well performing watches.
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FourSigmatic, the maker of delicious mushroom coffee.
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ExpressVPN, the VPN I've used for many years
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to protect my privacy on the internet.
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And Cash App, the app I use to send money to friends.
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Please check out these sponsors in the description
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to get a discount and to support this podcast.
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As a side note, let me say that the impact
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of artificial intelligence and automation
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on our economy and our world
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is something worth thinking deeply about.
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Like with many topics that are linked
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to predicting the future evolution of technology,
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it is often too easy to fall into one of two camps,
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the fear of mongering camp
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or the technologically utopianism camp.
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As always, the future will land us the where in between.
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I prefer to wear two hats in these discussions
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and alternate between them often.
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The hat of a pragmatic engineer
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and the hat of a futurist.
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This is probably a good time to mention Andrew Yang,
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the presidential candidate who has been
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one of the high profile thinkers on this topic.
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And I'm sure I will speak with him
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on this podcast eventually.
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A conversation with Andrew has been on the table many times.
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Our schedule is just having aligned,
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especially because I have a strongly held to preference
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for long form, two, three, four hours or more, and in person.
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I work hard to not compromise on this.
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Trust me, it's not easy.
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Even more so in the times of COVID,
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which requires getting tested nonstop,
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staying isolated and doing a lot of costly
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and uncomfortable things that minimize risk for the guests.
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The reason I do this is because to me,
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something is lost in remote conversation.
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That's something that magic,
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I think is worth the effort,
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even if it ultimately leads to a failed conversation.
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This is how I approach life,
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treasuring the possibility of a rare moment of magic.
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I'm willing to go to the ends of the world
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for just such a moment.
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If you enjoy this thing, subscribe on YouTube,
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review it with fast stars on Apple Podcasts,
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follow on Spotify, support on Patreon,
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connect with me on Twitter at Lex Freedman.
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And now, here's my conversation with Eric Greenjawson.
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You posted a quote on Twitter by Albert Bartlett
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saying that the greatest shortcoming of the human race
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is our inability to understand the exponential function.
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Why would you say the exponential growth
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is important to understand?
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Yeah, that quote, I remember posting that.
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It's actually a reprise of something Andy McAfee
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and I said in the second machine age,
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but I posted it in early March
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when COVID was really just beginning to take off
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and I was really scared.
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There were actually only a couple dozen cases,
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maybe less at that time,
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but they were doubling every two or three days
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and I could see, oh my God, this is gonna be a catastrophe
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and it's gonna happen soon,
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but nobody was taking it very seriously
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or not a lot of people were taking it very seriously.
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In fact, I remember I did my last in person conference
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that week, I was flying back from Las Vegas
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and I was the only person on the plane wearing a mask
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and the flight attendant came over to me,
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she looked very concerned and she kind of put her hands
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on my shoulder, she was touching me all over,
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which I wasn't thrilled about
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and she goes, do you have some kind of anxiety disorder?
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And I was like, no, it's because of COVID.
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This is early March.
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Early March, but I was worried because I knew I could see,
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or I suspected, I guess,
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that that doubling would continue and it did
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and pretty soon we had thousands of times more cases.
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Most of the time when I use that quote, I try to,
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it's motivated by more optimistic things like Moore's law
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and the wonders of having more computer power,
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but in either case, it can be very counterintuitive.
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I mean, if you walk for 10 minutes,
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you get about 10 times as far away
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as if you walk for one minute.
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That's the way our physical world works.
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That's the way our brains are wired,
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but if something doubles for 10 times as long,
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you don't get 10 times as much,
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you get 1,000 times as much
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and after 20, it's a billion, after 30, it's a,
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no, sorry, after 20, it's a million, after 30, it's a billion.
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And pretty soon after that,
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it just gets to these numbers that you can barely grasp.
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Our world is becoming more and more exponential,
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mainly because of digital technologies.
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So more and more often our intuitions are out of whack
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and that can be good in the case of things creating wonders,
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but it can be dangerous in the case of viruses
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Do you think it generally applies?
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Like, is there spaces where it does apply
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and where it doesn't?
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How are we supposed to build an intuition
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about in which aspects of our society
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does exponential growth apply?
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Well, you can learn the math,
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but the truth is our brains,
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I think tend to be learned more from experiences.
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So we just start seeing it more and more often.
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So hanging around Silicon Valley,
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hanging around AI and computer researchers,
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I see this kind of exponential growth a lot more frequently.
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And I'm getting used to it, but I still make mistakes.
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I still underestimate some of the progress
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in just talking to someone about GPT3
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and how rapidly natural language has improved.
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But I think that as the world becomes more exponential,
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we'll all start experiencing it more frequently.
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The danger is that we may make some mistakes in the meantime
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using our old kind of caveman intuitions
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about how the world works.
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Well, the weird thing is it always kind of looks linear
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Like the, you know, it's hard to feel,
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it's hard to retrospect and really acknowledge
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how much has changed in just a couple of years
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or five years or 10 years with the internet.
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If we just look at investments of AI
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or even just social media,
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all the various technologies
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that go into the digital umbrella.
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It feels pretty calm and normal and gradual.
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Well, a lot of stuff, you know,
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I think there are parts of the world,
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most of the world is not exponential.
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You know, the way humans learn,
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the way organizations change,
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the way our whole institutions adapt and evolve,
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those don't improve at exponential paces.
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And that leads to a mismatch oftentimes
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between these exponentially improving technologies
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or let's say changing technologies
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because some of them are exponentially more dangerous
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and our intuitions and our human skills
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and our institutions that just don't change very fast at all.
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And that mismatch I think is at the root
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of a lot of the problems in our society,
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the growing inequality and other dysfunctions
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in our political and economic systems.
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So one guy that talks about exponential functions
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a lot is Elon Musk.
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He seems to internalize this kind of way
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of exponential thinking.
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He calls it first principles thinking,
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sort of the kind of going to the basics,
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asking the question like what were the assumptions
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of the past, how can we throw them out the window?
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How can we do this 10x much more efficiently
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and constantly practicing that process?
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And also using that kind of thinking to estimate sort of
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when create deadlines and estimate
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when you'll be able to deliver on some of these technologies.
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Now, it often gets him in trouble
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because he overestimates,
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like he doesn't meet the initial estimates of the deadlines
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but he seems to deliver late but deliver.
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And which is kind of an interesting,
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like what are your thoughts about this whole thing?
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I think we can all learn from Elon.
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I think going to first principles,
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I talked about two ways of getting more of a grip
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on the exponential function.
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And one of them just comes from first principles.
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If you understand the math of it,
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you can see what's going to happen.
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And even if it seems counterintuitive
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that a couple of dozen of COVID cases
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could become thousands or tens or hundreds
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of thousands of them in a month,
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it makes sense once you just do the math.
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And I think Elon tries to do that a lot.
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I think he also benefits from hanging out in Silicon Valley
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and he's experienced it in a lot of different applications.
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So, it's not as much of a shock to him anymore
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but that's something we can all learn from.
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In my own life, I remember one of my first experiences
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really seeing it was when I was a grad student
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and my advisor asked me to plot the growth of computer power
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in the US economy in different industries.
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And there are all these exponentially growing curves
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and I was like, holy shit, look at this.
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In each industry, it was just taking off.
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And you didn't have to be a rocket scientist
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to extend that and say, wow, this means that
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this was in the late 80s and early 90s
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that if it goes anything like that,
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we're gonna have orders of magnitude
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more computer power than we did at that time.
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And of course we do.
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So, when people look at Moore's law,
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they often talk about it as just,
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so the exponential function is actually a stack of S curves.
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So basically it's you milk or whatever,
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take the most advantage of a particular little revolution
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and then you search for another revolution.
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And it's basically revolutions stack on top of revolutions.
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Do you have any intuition about how the head humans
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keep finding ways to revolutionize things?
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Well, first let me just unpack that first point
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that I talked about exponential curves
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but no exponential curve continues forever.
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It's been said that if anything can't go on forever,
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eventually it will stop.
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That's very profound.
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It's very profound, but it seems that a lot of people
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don't appreciate that half of it as well either.
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And that's why all exponential functions
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eventually turn into some kind of S curve
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or stop in some other way, maybe catastrophically.
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And that's happened with COVID as well.
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I mean, it was, it went up and then it sort of,
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at some point it starts saturating the pool
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of people to be infected.
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There's a standard epidemiological model
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that's based on that.
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And it's beginning to happen with Moore's law
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or different generations of computer power.
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It happens with all exponential curves.
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The remarkable thing is you alluded,
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the second part of your question is that we've been able
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to come up with a new S curve on top of the previous one
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and do that generation after generation
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with new materials, new processes
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and just extend it further and further.
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I don't think anyone has a really good theory
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about why we've been so successful in doing that.
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It's great that we have been
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and I hope it continues for some time.
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But it's, you know, one beginning of a theory
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is that there's huge incentives when other parts
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of the system are going on that clock speed
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of doubling every two to three years.
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If there's one component of it that's not keeping up,
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then the economic incentives become really large
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to improve that one part.
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It becomes a bottleneck and anyone who can do
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improvements in that part can reap huge returns
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so that the resources automatically get focused
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on whatever part of the system is in keeping up.
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Do you think some version of the Moore's law will continue?
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Some version, yes, it is.
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I mean, one version that has become more important
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is something I call Kumi's law,
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which is named after John Kumi,
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which I should mention was also my college roommate,
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but he identified the fact that energy consumption
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has been declining by a factor of two.
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And for most of us, that's more important, you know,
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the new iPhones came out today as we're recording this.
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I'm not sure when you're gonna make it available.
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Very soon after this, yeah.
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And for most of us, you know, having the iPhone
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be twice as fast, you know, it's nice,
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but having it the battery life longer,
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that would be much more valuable.
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And the fact that a lot of the progress in chips now
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is reducing energy consumption is probably more important
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for many applications than just the raw speed.
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Other dimensions of Moore's law are in AI and machine learning.
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Those tend to be very parallelizable functions,
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especially deep neural nets.
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And so instead of having one chip,
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you can have multiple chips or you can have a GPU,
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a graphic processing unit that goes faster
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and now special chips designed for machine learning
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like tensor processing units.
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Each time you switch, there's another 10X
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or 100X improvement above and beyond Moore's law.
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So I think that the raw silicon
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isn't improving as much as it used to,
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but these other dimensions are becoming important,
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more important than we're seeing progress in them.
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I don't know if you've seen the work by OpenAI
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where they show the exponential improvement
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of the training of neural networks,
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just literally in the techniques used.
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So that's almost like the algorithm.
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It's fascinating to think like, can I actually continue?
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Us figuring out more and more tricks
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on how to train networks faster.
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Well, the progress has been staggering.
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If you look at image recognition, as you mentioned,
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I think it's a function of at least three things
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that are coming together.
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One, we just talked about faster chips,
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not just Moore's law, but GPUs, TPUs and other technologies.
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The second is just a lot more data.
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I mean, we are awash in digital data today
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in a way we weren't 20 years ago.
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Photography, I'm old enough to remember,
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used to be chemical and now everything is digital.
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I took probably 50 digital photos yesterday.
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I wouldn't have done that if it was chemical.
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And we have the internet of things
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and all sorts of other types of data.
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When we walk around with our phone,
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it's just broadcasting a huge amount of digital data
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that can be used as training sets.
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And then last but not least,
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as they mentioned at OpenAI,
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there have been significant improvements in the techniques.
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The core idea of deep neural nets
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has been around for a few decades,
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but the advances in making it work more efficiently
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have also improved a couple of orders of magnitude or more.
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So you multiply together 100 fold improvement
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in computer power, 100 fold or more improvement in data,
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100 fold improvement in techniques of software
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and algorithms, and soon you're getting
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into a million fold improvements.
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Somebody brought this idea with GPT3 that it's,
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so it's trained in a self supervised way
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on basically internet data.
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And that's one of the, I've seen arguments made
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and they seem to be pretty convincing
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that the bottleneck there is going to be
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how much data there is on the internet,
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which is a fascinating idea that it literally
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will just run out of human generated data to train on.
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I know we make it the point where it's consumed
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basically all of human knowledge
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or all digitized human knowledge, yeah.
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And that would be the bottleneck.
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But the interesting thing with bottlenecks
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is people often use bottlenecks as a way
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to argue against exponential growth.
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They say, well, there's no way you can
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overcome this bottleneck,
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but we seem to somehow keep coming up in new ways
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to overcome whatever bottlenecks the critics come up with.
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Which is fascinating.
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I don't know how you overcome the data bottleneck,
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but probably more efficient training algorithms.
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Yeah, well, you already mentioned that,
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that these training algorithms are getting much better
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at using smaller amounts of data.
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We also are just capturing a lot more data
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than we used to, especially in China,
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but all around us.
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So those are both important.
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In some applications, you can simulate the data,
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video games, some of the self driving car systems
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are, you know, simulating driving.
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And of course that has some risks and weaknesses,
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but you can also, and if you want to, you know,
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exhaust all the different ways you could beat a video game,
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you could just simulate all the options.
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Can we take a step in that direction of autonomous vehicles?
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Make sure you're talking to the CTO of Waymo tomorrow.
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And obviously, I'm talking to Elon again in a couple of weeks.
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What's your thoughts on autonomous vehicles?
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Like, where do we stand as a problem
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that has the potential of revolutionizing the world?
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Well, you know, I'm really excited about that,
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but it's become much clearer that the original way
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that I thought about it, and most people thought about it,
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like, you know, will we have a self driving car or not,
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is way too simple.
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The better way to think about it is that there's a whole
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continuum of how much driving and assisting
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I noticed that you're right next to your next door
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to Toyota Research Institute.
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That's a total accident.
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I love the TRI folks, but yeah.
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Have you talked to Gil Pratt?
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Yeah, we're going to, we're supposed to talk.
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It's kind of hilarious.
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So there's kind of the, I think it's a good counterpart
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to see what Elon is doing, and hopefully they can be frank
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in how they think about each other,
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because I've heard both of them talk about it.
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But they're much more, you know, this is an assistive,
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a guardian angel that watches over you,
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as opposed to try to do everything.
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I think there's some things like driving on a highway,
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you know, from LA to Phoenix,
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where it's mostly good weather, straight roads.
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That's close to a solved problem, let's face it.
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In other situations, you know, driving through the snow
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and in Boston, where the roads are kind of crazy.
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And most importantly, you have to make a lot of judgments
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about what the other driver's going to do
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at these intersections that aren't really right angles
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and aren't very well described.
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It's more like game theory.
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That's a much harder problem and requires understanding
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of human motivations, and so there's a continuum there
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of some places where the cars will work very well
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and others where it could probably take decades.
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What do you think about the Waymo?
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So as you mentioned, two companies
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that actually have cars on the road,
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there's the Waymo approach that it's more like,
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we're not going to release anything until it's perfect
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and we're going to be very strict about the streets
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that we travel on, but it'd be perfect.
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Well, I'm smart enough to be humble
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and not try to get between.
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I know there's very bright people on both sides
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of the argument, I've talked to them
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and they make convincing arguments to me
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about how careful they need to be
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and the social acceptance.
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Some people thought that when the first few people died
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from self driving cars, I would shut down the industry,
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but it was more of a blip actually.
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And you know, so that was interesting.
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Of course, there's still a concern
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that if there could be setbacks,
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if we do this wrong, you know,
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your listeners may be familiar
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with the different levels of self driving,
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you know, level one, two, three, four, five.
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I think Andrew Ang has convinced me
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that this idea of really focusing on level four,
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where you only go in areas that are well mapped,
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rather than just going out in the wild,
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is the way things are going to evolve.
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But you can just keep expanding those areas
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where you've mapped things really well,
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where you really understand them
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and eventually they all become kind of interconnected.
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And that could be a kind of another way of progressing
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to make it more feasible over time.
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I mean, that's kind of like the Waymo approach,
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which is they just now released,
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I think just like a day or two ago,
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anyone from the public in the Phoenix, Arizona,
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to, you know, you can get a ride in a Waymo car
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with no person, no driver.
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Oh, they've taken away the safety driver?
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Oh yeah, for a while now there's been no safety driver.
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Okay, because I mean, I've been following
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that one in particular, but I thought it was kind of funny
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about a year ago when they had the safety driver
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and then they added a second safety driver
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because the first safety driver would fall asleep.
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I'm not sure they're going in the right direction with that.
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No, they've Waymo in particular
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done a really good job with that.
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They actually have a very interesting infrastructure.
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Of remote like observation.
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So they're not controlling the vehicles remotely,
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but they're able to, it's like a customer service.
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They can anytime tune into the car.
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I bet they can probably remotely control it as well,
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but that's officially not the function that they.
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Yeah, I can see that being really,
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because I think the thing that's proven harder
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than maybe some of the early people expected was
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there's a long tail of weird exceptions.
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So you can deal with 90, 99, 99.99% of the cases,
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but then there's something that just never been seen
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before in the training data.
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And humans more or less can work around that,
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although let me be clear and note,
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there are about 30,000 human fatalities
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just in the United States and maybe a million worldwide.
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So they're far from perfect,
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but I think people have higher expectations of machines.
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They wouldn't tolerate that level of death
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and damage from a machine.
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And so we have to do a lot better
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at dealing with those edge cases.
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And also the tricky thing that,
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if I have a criticism for the Waymo folks,
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there's such a huge focus on safety,
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where people don't talk enough about creating products
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that customers love, that human beings love using.
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You know, it's very easy to create a thing that's safe
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at the extremes, but then nobody wants to get into it.
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Yeah, well, back to Elon.
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I think one of, part of his genius
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was with the electric cars, before he came along,
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electric cars were all kind of underpowered, really light,
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and there were sort of wimpy cars that weren't fun.
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And the first thing he did was,
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he made a roadster that went zero to 60 faster
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than just about any other car and went the other end.
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And I think that was a really wise marketing move
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as well as a wise technology move.
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Yeah, it's difficult to figure out
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what right marketing move is for AI systems.
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That's always been, I think it requires guts
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and risk taking, which is what Elon practices,
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I mean, to the chagrin of perhaps investors or whatever,
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but it also requires rethinking what you're doing.
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I think way too many people are unimaginative,
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intellectually lazy, and when they take AI,
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they basically say, what are we doing now?
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How can we make a machine do the same thing?
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Maybe we'll save some costs, we'll have less labor.
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And yeah, it's not necessarily the worst thing
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in the world to do, but it's really not leading
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to a quantum change in the way you do things.
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When Jeff Bezos said, hey, we're gonna use the internet
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to change how bookstores work, and we're gonna use technology,
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he didn't go and say, okay, let's put a robot cashier
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where the human cashier is and leave everything else alone.
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That would have been a very lame way
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to automate a bookstore.
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He went from soup to nut to say,
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let's just rethink it, we get rid of the physical bookstore,
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we have a warehouse, we have delivery,
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we have people order on a screen,
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and everything was reinvented.
link |
And that's been the story of these general purpose
link |
technologies all through history.
link |
In my books, I write about electricity
link |
and how for 30 years, there was almost no productivity gain
link |
from the electrification of factories a century ago.
link |
And that's not because electricity
link |
is a wimpy, useless technology,
link |
we all know how awesome electricity is.
link |
It's because at first, they really didn't rethink the factories.
link |
It was only after they reinvented them,
link |
and we describe how in the book,
link |
then you suddenly got a doubling
link |
and tripling of productivity growth.
link |
But it's the combination of the technology
link |
with the new business models, new business organization.
link |
That just takes a long time
link |
and it takes more creativity than most people have.
link |
Can you maybe linger on electricity?
link |
Because that's a fun one.
link |
Yeah, I'll tell you what happened.
link |
Before electricity, there were basically steam engines
link |
or sometimes water wheels.
link |
And to power the machinery,
link |
you had to have pulleys and crankshafts.
link |
And you really can't make them too long
link |
because they'll break the torsion.
link |
So all the equipment was kind of clustered around this,
link |
one giant steam engine.
link |
You can't make small steam engines either
link |
because of thermodynamics.
link |
So you have one giant steam engine,
link |
all the equipment clustered around it, multi story,
link |
they have it vertical to minimize the distance
link |
as well as horizontal.
link |
And then when they did electricity,
link |
they took out the steam engine,
link |
they got the biggest electric motor
link |
they could buy from General Electric
link |
or someone like that.
link |
And nothing much else changed.
link |
It took until a generation of managers retired or died
link |
30 years later that people started thinking,
link |
wait, we don't have to do it that way.
link |
You can make electric motors,
link |
big, small, medium.
link |
You can put one with each piece of equipment.
link |
There's this big debate,
link |
if you read the management literature
link |
between what they call group drive versus unit drive,
link |
where every machine would have its own motor.
link |
Well, once they did that,
link |
once they went to unit drive,
link |
those guys won the debate,
link |
then you started having a new kind of factory,
link |
which is sometimes spread out over acres,
link |
single story and each piece of equipment had its own motor.
link |
And most importantly,
link |
they weren't laid out based on who needed the most power.
link |
They were laid out based on
link |
what is the workflow of materials, assembly line.
link |
Let's have it go from this machine
link |
to that machine to that machine.
link |
Once they rethought the factory that way,
link |
huge increases in productivity was just staggering.
link |
People like Paul David have documented this
link |
in their research papers.
link |
And I think that there's a lesson you see over and over.
link |
It happened when the steam engine
link |
changed manual production.
link |
It's happened with the computerization.
link |
People like Michael Hammer said,
link |
don't automate, obliterate.
link |
the big gains only came once smart entrepreneurs
link |
and managers basically reinvented their industries.
link |
I mean, one other interesting point about all that
link |
is that during that reinvention period,
link |
you often actually,
link |
not only don't see productivity growth,
link |
you can actually see a slipping back,
link |
measured productivity actually falls.
link |
I just wrote a paper with Chad Severson and Daniel Rock
link |
called the Productivity J Curve,
link |
which basically shows that in a lot of these cases,
link |
you have a downward dip before it goes up.
link |
And that downward dip is when everyone's trying
link |
to reinvent things.
link |
And you could say that they're creating knowledge
link |
and intangible assets,
link |
but that doesn't show up on anyone's balance sheet.
link |
It doesn't show up in GDP.
link |
So it's as if they're doing nothing.
link |
Like take self driving cars, we're just talking about it.
link |
There have been hundreds of billions of dollars spent
link |
developing self driving cars.
link |
And basically no chauffeur has lost his job,
link |
I guess I gotta check on the one thing.
link |
It's a big J curve.
link |
Yeah, so there's a bunch of spending
link |
and no real consumer benefit.
link |
Now they're doing that in the belief,
link |
I think the justified belief
link |
that they will get the upward part of the J curve
link |
and they will be some big returns,
link |
but in the short run, you're not seeing it.
link |
That's happening with a lot of other AI technologies,
link |
just as it happened with earlier general purpose technologies.
link |
And it's one of the reasons we're having
link |
relatively low productivity growth lately.
link |
As an economist, one of the things that disappoints me
link |
is that as eye popping as these technologies are,
link |
you and I are both excited about some things they can do.
link |
The economic productivity statistics are kind of dismal.
link |
We actually believe it or not,
link |
have had lower productivity growth in the past,
link |
about 15 years than we did in the previous 15 years,
link |
in the 90s and early 2000s.
link |
And so that's not what you would have expected
link |
if these technologies were that much better.
link |
But I think we're in kind of a long J curve there.
link |
Personally, I'm optimistic.
link |
We'll start seeing the upward tick,
link |
maybe as soon as next year.
link |
But the past decade has been a bit disappointing
link |
if you thought there's a one to one relationship
link |
between cool technology and higher productivity.
link |
What would you place your biggest hope
link |
for productivity increases on?
link |
Like you kind of said at a high level AI,
link |
but if I were to think about
link |
what has been so revolutionary in the last 10 years,
link |
I would have 15 years and thinking about the internet,
link |
I would say things like,
link |
hope I'm not saying anything ridiculous,
link |
but everything from Wikipedia to Twitter.
link |
So like these kind of websites, not so much AI,
link |
but like I would expect to see some kind of big productivity
link |
increases from just the connectivity
link |
between people and the access to more information.
link |
Yeah, well, that's another area
link |
I've done quite a bit of research on actually
link |
is these free goods like Wikipedia, Facebook, Twitter,
link |
Zoom, we're actually doing this in person,
link |
but almost everything else I do these days is online.
link |
The interesting thing about all those is
link |
most of them have a price of zero.
link |
You know, what do you pay for Wikipedia?
link |
Maybe like a little bit for the electrons
link |
to come to your house.
link |
Basically zero, right?
link |
Take a small pause and say,
link |
I donate to Wikipedia often, you should too.
link |
It's good for you, yeah.
link |
So, but what does that do mean for GDP?
link |
GDP is based on the price and quantity
link |
of all the goods things bought and sold.
link |
If something has zero price,
link |
you know how much it contributes to GDP?
link |
To a first approximation, zero.
link |
So these digital goods that we're getting more and more
link |
of we're spending more and more hours a day
link |
consuming stuff off the screens, little screens,
link |
big screens, that doesn't get priced into GDP.
link |
It's like they don't exist.
link |
That doesn't mean they don't create value.
link |
I get a lot of value from watching cat videos
link |
and reading Wikipedia articles and listening to podcasts,
link |
even if I don't pay for them.
link |
So we've got a mismatch there.
link |
Now, in fairness, economists since Simon Kuznets
link |
invented GDP and productivity, all those statistics
link |
back in the 1930s, he recognized, he in fact said,
link |
this is not a measure of wellbeing.
link |
This is not a measure of welfare.
link |
It's a measure of production.
link |
But almost everybody has kind of forgotten
link |
that he said that and they just use it.
link |
It's like, how well off are we?
link |
What was GDP last year?
link |
It was 2.3% growth or whatever.
link |
That is how much physical production,
link |
but it's not the value we're getting.
link |
We need a new set of statistics.
link |
And I'm working with some colleagues,
link |
Avi Collis and others to develop something
link |
we call GDP dash B.
link |
GDP B measures the benefits you get, not the cost.
link |
If you get benefit from Zoom or Wikipedia or Facebook,
link |
then that gets counted in GDP B, even if you pay zero for it.
link |
So, you know, back to the original point,
link |
I think there is a lot of gain over the past decade
link |
in these digital goods that doesn't show up in GDP,
link |
doesn't show up in productivity.
link |
By the way, productivity is just defined as GDP
link |
divided by hours worked.
link |
So, if you mismeasure GDP, you mismeasure productivity
link |
by the exact same amount.
link |
That's something we need to fix.
link |
I'm working with the statistical agencies
link |
to come up with a new set of metrics.
link |
And over the coming years, I think we'll see,
link |
we're not going to do away with GDP.
link |
It's very useful, but we'll see a parallel set of accounts
link |
that measure the benefits.
link |
How difficult is it to get that B in the GDP B?
link |
I mean, one of the reasons it hasn't been done before
link |
is that, you know, you can measure it,
link |
the cash register, what people pay for stuff.
link |
But how do you measure what they would have paid?
link |
Like what the value is, that's a lot harder.
link |
You know, how much is Wikipedia worth to you?
link |
That's what we have to answer.
link |
And to do that, what we do is,
link |
we can use online experiments.
link |
We do massive online choice experiments.
link |
We ask hundreds of thousands, not millions of people,
link |
to do lots of sort of AB tests.
link |
How much would I have to pay you
link |
to give up Wikipedia for a month?
link |
How much would I have to pay you
link |
to stop using your phone?
link |
And in some cases, it's hypothetical.
link |
In other cases, we actually enforce it,
link |
which is kind of expensive.
link |
Like we pay somebody $30 to stop using Facebook
link |
and we see if they'll do it.
link |
And some people will give it up for $10.
link |
Some people won't give it up
link |
even if you give them $100.
link |
And then you get a whole demand curve.
link |
You get to see what all the different prices are
link |
and how much value different people get.
link |
And not surprisingly,
link |
different people have different values.
link |
We find that women tend to value Facebook more than men.
link |
Old people tend to value it a little bit more
link |
than young people, I was interesting.
link |
I think young people maybe know about other networks
link |
that I don't know the name of,
link |
that are better than Facebook.
link |
And so you get to see these patterns,
link |
but every person's individual.
link |
And then if you add up all those numbers,
link |
you start getting an estimate of the value.
link |
Okay, first of all, that's brilliant.
link |
Is this work that will soon eventually be published?
link |
Yeah, well, there's a version of it
link |
in the proceedings of the National Academy of Sciences
link |
about, I think we call it massive online choice experiments.
link |
I should remember the title, but it's on my website.
link |
So yeah, we have some more papers coming out on it,
link |
but the first one is already out.
link |
You know, it's kind of a fascinating mystery
link |
that Twitter, Facebook,
link |
like all these social networks are free.
link |
And it seems like almost none of them,
link |
except for YouTube,
link |
have experimented with removing ads for money.
link |
Can you like, do you understand that
link |
from both economics and the product perspective?
link |
Yeah, it's something that, so I teach a course
link |
on digital business models.
link |
So I used to at MIT at Stanford.
link |
I'm not quite sure.
link |
I'm not teaching until next spring.
link |
I'm still thinking what my course is gonna be.
link |
But there are a lot of different business models.
link |
And when you have something that's zero marginal cost,
link |
there's a lot of forces,
link |
especially if there's any kind of competition
link |
that push prices down to zero.
link |
But you can have ad supported systems.
link |
You can bundle things together.
link |
You can have volunteer, you mentioned Wikipedia.
link |
There's donations.
link |
And I think economists underestimate the power
link |
of volunteerism and donations.
link |
You know, national public radio.
link |
Actually, how do you, this podcast,
link |
how is this, what's the revenue model?
link |
There's sponsors at the beginning.
link |
And then, and people, the funny thing is,
link |
I tell people they can, it's very,
link |
I tell them the timestamp.
link |
So if you wanna skip the sponsors, you're free.
link |
But the, it's funny that a bunch of people,
link |
so I read the advertisement.
link |
And a bunch of people enjoy reading it.
link |
Well, they may learn something from it.
link |
And also, from the advertiser's perspective,
link |
those are people who are actually interested, you know?
link |
Like, I mean, the example I sometimes get is like,
link |
I bought a car recently.
link |
And all of a sudden, all the car ads were like,
link |
interesting to me.
link |
And then like, now that I have the car,
link |
like I sort of zone out on, okay, but that's fine.
link |
The car companies, they don't really wanna be advertising
link |
to me if I'm not gonna buy their product.
link |
So there are a lot of these different revenue models.
link |
And, you know, it's a little complicated,
link |
but the economic theory has to do with what the shape
link |
of the demand curve is,
link |
when it's better to monetize it with charging people
link |
versus when you're better off doing advertising.
link |
I mean, in short, when the demand curve
link |
is relatively flat and wide,
link |
like generic news and things like that,
link |
then you tend to do better with advertising.
link |
If it's a good that's only useful to a small number
link |
of people, but they're willing to pay a lot.
link |
They have a very high value for it.
link |
Then you, advertising isn't gonna work as well.
link |
You're better off charging for it.
link |
Both of them have some inefficiencies.
link |
And then when you get into targeting
link |
and you get into these other revenue models,
link |
it gets more complicated.
link |
But there's some economic theory on it.
link |
I also think, to be frank,
link |
there's just a lot of experimentation that's needed
link |
because sometimes things are a little counterintuitive,
link |
especially when you get into what are called
link |
two sided networks or platform effects,
link |
where you may grow the market on one side
link |
and harvest the revenue on the other side.
link |
You know, Facebook tries to get more and more users
link |
and then they harvest the revenue from advertising.
link |
So that's another way of kind of thinking about it.
link |
Is it strange to you that they haven't experimented?
link |
Well, they are experimenting.
link |
So, you know, they are doing some experiments
link |
about what the willingness is for people to pay.
link |
I think that when they do the math,
link |
it's gonna work out that they still are better off
link |
with an advertising driven model, but...
link |
Like this is what YouTube is, right?
link |
Yeah, you allow the person to decide,
link |
the customer to decide exactly which model they prefer.
link |
Yeah, no, that can work really well, you know.
link |
And newspapers, of course,
link |
I've known this for a long time,
link |
the Wall Street Journal, the New York Times,
link |
they had subscription revenue,
link |
they also have advertising revenue.
link |
And that can definitely work.
link |
The online is a lot easier to have a dial
link |
that's much more personalized
link |
and everybody can kind of roll their own mix.
link |
And I could imagine, you know,
link |
having a little slider about how much advertising
link |
you want or are willing to take.
link |
And if it's done right and it's incentive compatible,
link |
it could be a win win where both the content provider
link |
and the consumer are better off
link |
than they would have been before.
link |
Yeah, you know, the done right part is a really good point.
link |
Like with Jeff Bezos and the single click purchase
link |
on Amazon, the frictionless effort there,
link |
if I could just rant for a second
link |
about the Wall Street Journal,
link |
all the newspapers you mentioned
link |
is I have to click so many times to subscribe to them
link |
that I literally don't subscribe
link |
just because of the number of times I have to click.
link |
I'm totally with you.
link |
I don't understand why so many companies make it so hard.
link |
I mean, another example is when you buy a new iPhone
link |
or a new computer, whatever,
link |
I feel like, okay, I'm gonna like lose an afternoon,
link |
just like loading up and getting all my stuff back.
link |
And for a lot of us, that's more of a deterrent
link |
And if they could make it painless,
link |
we'd give them a lot more money.
link |
So I'm hoping somebody listening is working
link |
on making it more painless for us to buy your products.
link |
If we could just like linger a little bit
link |
on the social network thing,
link |
because there's this Netflix social dilemma.
link |
And Tristan Harris and company, yeah.
link |
And people's data, it's really sensitive
link |
and social networks are at the core,
link |
arguably of many of societal tension
link |
and some of the most important things happening in society.
link |
So it feels like it's important to get this right,
link |
both from a business model perspective
link |
and just like a trust perspective.
link |
I still gotta, I mean, it just still feels like,
link |
I know there's experimentation going on.
link |
It still feels like everyone is afraid
link |
to try different business models, like really try.
link |
Well, I'm worried that people are afraid
link |
to try different business models.
link |
I'm also worried that some of the business models
link |
may lead them to bad choices.
link |
And Danny Kahneman talks about system one
link |
and system two, sort of like our reptilian brain
link |
that reacts quickly to what we see,
link |
see something interesting, we click on it,
link |
we retweet it versus our system two,
link |
our frontal cortex that's supposed to be more careful
link |
and rational that really doesn't make as many decisions
link |
I think there's a tendency for a lot of these social networks
link |
to really exploit system one, our quick instant reaction,
link |
make it, so we just click on stuff and pass it on
link |
and not really think carefully about it.
link |
And in that system, it tends to be driven by sex, violence,
link |
disgust, anger, fear, these relatively primitive kinds
link |
of emotions, maybe they're important for a lot of purposes,
link |
but they're not a great way to organize a society.
link |
And most importantly, when you think about this huge,
link |
amazing information infrastructure we've had
link |
that's connected billions of brains across the globe,
link |
not just we can all access information,
link |
but we can all contribute to it and share it.
link |
Arguably the most important thing
link |
that that network should do is favor truth over falsehoods.
link |
And the way it's been designed,
link |
not necessarily intentionally, is exactly the opposite.
link |
My MIT colleagues, Aral and Deb Roy and others at MIT
link |
did a terrific paper in the cover of science
link |
and they document what we all feared,
link |
which is that lies spread faster than truth
link |
on social networks.
link |
They looked at a bunch of tweets and weed tweets
link |
and they found that false information was more likely
link |
to spread further, faster to more people.
link |
It's not because people like lies,
link |
it's because people like things that are shocking, amazing.
link |
Can you believe this?
link |
Something that is not mundane,
link |
not that it's something everybody else already knew.
link |
And what are the most unbelievable things?
link |
Well, lies, and so if you wanna find something unbelievable,
link |
it's a lot easier to do that
link |
if you're not constrained by the truth.
link |
So they found that the emotional valence
link |
of false information was just much higher,
link |
it was more likely to be shocking
link |
and therefore more likely to be spread.
link |
Another interesting thing was that
link |
that wasn't necessarily driven by the algorithms.
link |
I know that there is some evidence,
link |
Zennip Tafeki and others have pointed out in YouTube,
link |
some of the algorithms unintentionally were tuned
link |
to amplify more extremist content.
link |
But in the study of Twitter that Sinan and Deb and others did,
link |
they found that even if you took out all the bots
link |
and all the automated tweets,
link |
you still had lies spreading significantly faster.
link |
It's just the problems with ourselves
link |
that we just can't resist passing on the salacious content.
link |
But I also blame the platforms
link |
because there's different ways you can design a platform.
link |
You can design a platform in a way
link |
that makes it easy to spread lies
link |
and to retweet and spread things on.
link |
Or you can kind of put some friction on that
link |
and try to favor truth.
link |
I had dinner with Jimmy Wales once,
link |
the guy who helped found Wikipedia.
link |
And he convinced me that,
link |
look, you can make some design choices,
link |
whether it's at Facebook, at Twitter, at Wikipedia,
link |
or Reddit, whatever.
link |
And depending on how you make those choices,
link |
you're more likely or less likely to have false news.
link |
Create a little bit of friction, like you said.
link |
You know, that's the...
link |
It could be friction or it could be speeding the truth.
link |
You know, either way.
link |
But I don't totally understand...
link |
Speeding the truth, I love it.
link |
Amplifying it and giving it more credit.
link |
And you know, like in academia,
link |
which is far, far from perfect,
link |
but you know, when someone has important discovery,
link |
it tends to get more cited
link |
and people kind of look to it more
link |
and sort of it tends to get amplified a little bit.
link |
So you could try to do that too.
link |
I don't know what the silver bullet is,
link |
but the meta point is that if we spend time thinking about it,
link |
we can amplify truth over falsehoods.
link |
And I'm disappointed in the heads of these social networks
link |
that they haven't been as successful
link |
or maybe haven't tried as hard to amplify truth.
link |
And part of it, going back to what we said earlier,
link |
is you know, these revenue models
link |
may push them more towards growing fast,
link |
spreading information rapidly, getting lots of users,
link |
which isn't the same thing as finding truth.
link |
I mean, implicit in what you're saying now
link |
is a hopeful message that with platforms,
link |
we can take a step towards greater and greater popularity
link |
of truth, but the more cynical view
link |
is that what the last few years have revealed
link |
is that there's a lot of money to be made
link |
in dismantling even the idea of truth,
link |
that nothing is true.
link |
And as a thought experiment,
link |
I've been thinking about if it's possible
link |
that our future will have,
link |
like the idea of truth is something we won't even have.
link |
Do you think it's possible like in the future
link |
that everything is on the table in terms of truth
link |
and we're just swimming in this kind of digital economy
link |
where ideas are just little toys
link |
that are not at all connected to reality?
link |
Yeah, I think that's definitely possible.
link |
I'm not a technological determinist.
link |
So I don't think that's inevitable.
link |
I don't think it's inevitable that it doesn't happen.
link |
I mean, the thing that I've come away with
link |
every time I do these studies
link |
and I emphasize it in my books and elsewhere
link |
is that technology doesn't shape our destiny,
link |
we shape our destiny.
link |
So just by us having this conversation,
link |
I hope that your audience is gonna take it upon themselves
link |
as they design their products
link |
and they think about and they use products
link |
as they manage companies.
link |
How can they make conscious decisions
link |
to favor truth over false?
link |
So it's favor the better kinds of societies
link |
and not abdicate and say, well, we just build the tools.
link |
I think there was a saying that was it the German scientists
link |
when they were working on the missiles in late World War II.
link |
They said, well, our job is to make the missiles go up
link |
where they come down, that's someone else's department.
link |
And that's obviously not the,
link |
I think it's obvious that's not the right attitude
link |
that technologists should have,
link |
that engineers should have,
link |
they should be very conscious about
link |
what the implications are.
link |
And if we think carefully about it,
link |
we can avoid the kind of world that you just described
link |
where truth is all relative.
link |
There are going to be people who benefit from a world
link |
of where people don't check facts
link |
and where truth is relative and popularity
link |
or fame or money is orthogonal to truth.
link |
But one of the reasons I suspect
link |
that we've had so much progress over the past few hundred years
link |
is the invention of the scientific method,
link |
which is a really powerful tool or meta tool
link |
for finding truth and favoring things that are true
link |
versus things that are false.
link |
If they don't pass the scientific method,
link |
they're less likely to be true.
link |
And that has the societies and the people
link |
and the organizations that embrace that
link |
have done a lot better than the ones who haven't.
link |
And so I'm hoping that people keep that in mind
link |
and continue to try to embrace not just the truth,
link |
but methods that lead to the truth.
link |
So maybe on a more personal question,
link |
if one were to try to build a competitor to Twitter,
link |
what would you advise?
link |
Is there, I mean, the matter of question,
link |
is that the right way to improve systems?
link |
Yeah, no, I think that the underlying premise
link |
behind Twitter and all these networks is amazing
link |
that we can communicate with each other.
link |
And I use it a lot.
link |
There's a subpart of Twitter called econ Twitter,
link |
where we economists tweet to each other
link |
and talk about new papers.
link |
Something came out in the NBER,
link |
the National Bureau of Economic Research,
link |
and we share about it.
link |
People critique it.
link |
I think it's been a godsend
link |
because it's really sped up the scientific process,
link |
if you can call it economic scientific.
link |
Does it get divisive in that little?
link |
Sometimes, yeah, sure.
link |
Sometimes it does.
link |
It can also be done in nasty ways.
link |
And there's the bad parts.
link |
But the good parts are great
link |
because you just speed up that clock speed
link |
of learning about things.
link |
Instead of like in the old, old days,
link |
waiting to read it in a journal,
link |
or the not so old days when you'd see it posted
link |
on a website and you'd read it.
link |
Now on Twitter, people will distill it down
link |
and there's a real art to getting to the essence of things.
link |
So that's been great.
link |
But it certainly, we all know that Twitter
link |
can be a cesspool of misinformation.
link |
And like I just said, unfortunately misinformation
link |
tends to spread faster on Twitter than truth.
link |
And there are a lot of people who are very vulnerable to it.
link |
I'm sure I've been fooled at times.
link |
There are agents, whether from Russia
link |
or from political groups or others
link |
that explicitly create efforts at misinformation
link |
and efforts at getting people to hate each other.
link |
Or even more importantly, I've discovered, is nut picking.
link |
You know the idea of nut picking?
link |
Nut picking is when you find like an extreme nut case
link |
on the other side and then you amplify them
link |
and make it seem like that's typical of the other side.
link |
So you're not literally lying.
link |
You're taking some idiot, you know,
link |
ranting on the subway or just, you know,
link |
whether they're in the KKK or Antifa or whatever,
link |
they're just, and you normally,
link |
nobody would pay attention to this guy.
link |
Like 12 people would see him and it'd be the end.
link |
Instead, with video or whatever,
link |
you get tens of millions of people say it.
link |
And I've seen this, you know, I look at him, I get angry.
link |
I'm like, I can't believe that person did something so terrible.
link |
Let me tell all my friends about this terrible person.
link |
And it's a great way to generate division.
link |
I talked to a friend who studied
link |
Russian misinformation campaigns.
link |
And they're very clever about literally being
link |
on both sides of some of these debates.
link |
They would have some people pretend to be part of BLM,
link |
some people pretend to be white nationalists,
link |
and they would be throwing epithets at each other,
link |
saying crazy things at each other.
link |
And they're literally playing both sides of it,
link |
but their goal wasn't for one or the other to win.
link |
It was for everybody to get behating
link |
and distrusting everyone else.
link |
So these tools can definitely be used for that,
link |
and they are being used for that.
link |
It's been super destructive for our democracy
link |
And the people who run these platforms,
link |
I think have a social responsibility,
link |
a moral and ethical personal responsibility,
link |
to do a better job and to shut that stuff down.
link |
Well, I don't know if you can shut it down,
link |
but to design them in a way that, as I said earlier,
link |
favors truth over falsehoods and favors
link |
positive types of communication versus destructive ones.
link |
And just like you said, it's also on us.
link |
I try to be all about love and compassion and empathy
link |
I mean, one of the things,
link |
not picking is a fascinating term,
link |
one of the things that people do
link |
that's I think even more dangerous
link |
is not picking applied to individual statements
link |
So basically, worst case analysis in computer science
link |
is taking sometimes out of context,
link |
but sometimes in context,
link |
a statement, one statement by a person.
link |
because I've been reading The Rise and Fall of the Third Reich,
link |
I often talk about Hitler on this podcast with folks,
link |
and it is so easy.
link |
That's really dangerous.
link |
But I'm all leaning in.
link |
I'm 100% because, well, it's actually a safer place
link |
than people realize,
link |
because it's history and history in long form
link |
is actually very fascinating to think about.
link |
And it's, but I could see how that could be taken
link |
totally out of context and it's very worrying.
link |
I think about these digital infrastructures,
link |
not just they disseminate things,
link |
but they're sort of permanent.
link |
Anything you say at some point,
link |
someone can go back and find something you said three years ago,
link |
perhaps jokingly, perhaps not.
link |
Maybe you're just wrong and you made them,
link |
and like that becomes,
link |
they can use that to define you if they have an intent.
link |
And we all need to be a little more forgiving.
link |
I mean, somewhere in my 20s,
link |
I told myself, I was going through all my different friends
link |
and I was like, you know,
link |
every one of them has at least like one nutty opinion.
link |
And I was like, there's like nobody who's like completely,
link |
except me, of course,
link |
but I'm sure they thought that about me too.
link |
And so you just kind of like learned
link |
to be a little bit tolerant that like, okay, there's just,
link |
Yeah, I wonder who the responsibility lays on there.
link |
Like, I think ultimately it's about leadership,
link |
like the previous president, Barack Obama has been,
link |
I think quite eloquent at walking this very difficult line
link |
of talking about cancel culture,
link |
but it's a difficult, it takes skill.
link |
You say the wrong thing and you piss off a lot of people.
link |
And so you have to do it well,
link |
but then also the platform of the technology is
link |
create friction and spreading this kind of nut picking
link |
And your point that we have to like learn over time
link |
I mean, we can't put it all on the platform
link |
and say you guys design it.
link |
And cause if we're idiots about using it, you know,
link |
nobody can design a platform that withstands that.
link |
And every new technology people learn it's dangerous.
link |
You know, when someone invented fire,
link |
it's great cooking and everything,
link |
but then somebody burned himself.
link |
And then you had to like learn how to like avoid,
link |
maybe somebody invented a fire extinguisher later
link |
So you kind of like figure out ways
link |
of working around these technologies.
link |
Someone invented seat belts, et cetera.
link |
And that's certainly true
link |
with all the new digital technologies
link |
that we have to figure out,
link |
not just technologies that protect us,
link |
but ways of using them that emphasize
link |
that are more likely to be successful than dangerous.
link |
So you've written quite a bit about
link |
how artificial intelligence might change our world.
link |
How do you think, if we look forward again,
link |
it's impossible to predict the future.
link |
But if we look at trends from the past
link |
and we try to predict what's gonna happen
link |
in the rest of the 21st century,
link |
how do you think AI will change our world?
link |
That's a big question.
link |
You know, I'm mostly a techno optimist.
link |
I'm not at the extreme, you know,
link |
the singularity is near end of the spectrum.
link |
But I do think that we are likely in
link |
for some significantly improved living standards,
link |
some really important progress,
link |
even just the technologies that are already kind of like
link |
in the can that haven't diffused.
link |
You know, when I talked earlier about the J curve,
link |
it could take 10, 20, 30 years for an existing technology
link |
to have the kind of profound effects.
link |
And when I look at whether it's, you know,
link |
vision systems, voice recognition, problem solving systems,
link |
even if nothing new got invented,
link |
we would have a few decades of progress.
link |
So I'm excited about that.
link |
And I think that's gonna lead to us being wealthier,
link |
healthier, I mean, the healthcare is probably
link |
one of the applications I'm most excited about.
link |
So that's good news.
link |
I don't think we're gonna have the end of work anytime soon.
link |
There's just too many things that machines still can't do.
link |
When I look around the world
link |
and think of whether it's childcare or healthcare,
link |
clean the environment, interacting with people,
link |
scientific work, artistic creativity.
link |
These are things that for now,
link |
machines aren't able to do nearly as well as humans,
link |
even just something as mundane as, you know,
link |
folding laundry or whatever.
link |
And many of these, I think are gonna be years or decades
link |
before machines catch up.
link |
You know, I may be surprised on some of them,
link |
but overall, I think there's plenty of work for humans to do.
link |
There's plenty of problems in society
link |
that need the human touch.
link |
So we'll have to repurpose.
link |
We'll have to, as machines are able to do some tasks,
link |
people are gonna have to reskill and move into other areas.
link |
And that's probably what's gonna be going on
link |
for the next, you know, 10, 20, 30 years or more,
link |
kind of big restructuring of society.
link |
We'll get wealthier and people will have to do new skills.
link |
Now, if you turn the doubt further,
link |
I don't know, 50 or 100 years into the future,
link |
then, you know, maybe all bets are off.
link |
Then it's possible that machines
link |
will be able to do most of what people do.
link |
You know, say one or 200 years, I think it's even likely.
link |
And at that point,
link |
then we're more in the sort of abundance economy.
link |
Then we're in a world where there's really little
link |
for the humans can do economically better than machines
link |
other than be human.
link |
And, you know, that will take a transition as well,
link |
kind of more of a transition of how we get meaning in life
link |
and what our values are.
link |
But shame on us if we screw that up.
link |
I mean, that should be like great, great news.
link |
And it kind of saddens me
link |
that some people see that as like a big problem.
link |
You know, I think it should be wonderful
link |
if people have all the health and material things
link |
that they need and can focus on loving each other
link |
and discussing philosophy and playing
link |
and doing all the other things that don't require work.
link |
Do you think you'll be surprised to see what the 20,
link |
like if we were to travel in time,
link |
100 years into the future,
link |
do you think you'll be able to,
link |
like if I gave you a month to like talk to people,
link |
no, like let's say a week,
link |
would you be able to understand what the house going on?
link |
You mean if I was there for a week?
link |
Yeah, if you were there for a week.
link |
100 years in the future?
link |
So like, so I'll give you one thought experiment.
link |
It's like, isn't it possible
link |
that we're all living in virtual reality by then?
link |
No, I think that's very possible.
link |
You know, I've played around with some of those VR headsets
link |
and they're not great,
link |
but I mean, the average person spends
link |
many waking hours staring at screens right now.
link |
You know, they're kind of low res
link |
compared to what they could be in 30 or 50 years,
link |
but certainly games and why not any other interactions
link |
could be done with VR.
link |
And that would be a pretty different world
link |
that we'd all, you know, in some ways be as rich as we wanted.
link |
You know, we could have castles
link |
and it could be traveling anywhere we want.
link |
And it could obviously be multi sensory.
link |
So that would be possible.
link |
You know, of course, there's people, you know,
link |
you've had Elon Musk on and others, you know,
link |
there are people, Nick Bostrom, you know,
link |
makes the simulation argument that maybe we're already there.
link |
We're already there.
link |
So, but, but in general,
link |
or do you not even think about it in this kind of way?
link |
You're self critically thinking,
link |
how good are you as an economist
link |
at predicting what the future looks like?
link |
Well, it starts getting, I mean,
link |
I feel reasonably comfortable next, you know,
link |
five, 10, 20 years in terms of that path.
link |
When you start getting truly superhuman
link |
artificial intelligence, kind of by definition,
link |
be able to think of a lot of things
link |
that I couldn't have thought of
link |
and create a world that I couldn't even imagine.
link |
And so I'm not sure I can,
link |
I can predict what that world is going to be like.
link |
One thing that AI researchers,
link |
AI safety researchers worry about
link |
is what's called the alignment problem.
link |
When an AI is that powerful,
link |
then they can do all sorts of things.
link |
And you really hope that their values
link |
are aligned with our values.
link |
And it's even tricky defining what our values are.
link |
I mean, first off, we all have different values.
link |
And secondly, maybe if we were smarter,
link |
we would have better values.
link |
Like, you know, I like to think
link |
that we have better values than he did in 1860.
link |
And, or in, you know, the year 200 BC on a lot of dimensions,
link |
things that we consider barbaric today.
link |
And it may be that if I thought about it more deeply,
link |
I would also be morally evolved.
link |
Maybe I'd be a vegetarian or do other things
link |
that right now, whether my future self
link |
would consider kind of immoral.
link |
So that's a tricky problem,
link |
getting the AI to do what we want.
link |
Assuming it's even a friendly AI.
link |
I mean, I should probably mention,
link |
there's a non trivial other branch
link |
where we destroy ourselves, right?
link |
I mean, there's a lot of exponentially improving technologies
link |
that could be ferociously destructive,
link |
whether it's in nanotechnology or biotech
link |
and weaponized viruses, AI, and other things that...
link |
Nuclear weapons, of course.
link |
The old school technology.
link |
Yeah, good old nuclear weapons
link |
that could be devastating or even existential.
link |
And new things yet to be invented.
link |
So that's a branch that I think is pretty significant.
link |
And there are those who think that one of the reasons
link |
we haven't been contacted by other civilizations, right?
link |
Is that once you get to a certain level
link |
of complexity in technology,
link |
there's just too many ways to go wrong.
link |
There's a lot of ways to blow yourself up and people,
link |
or I should say species end up falling into
link |
one of those traps, the great filter.
link |
I mean, there's an optimistic view of that.
link |
If there is literally no intelligent life out there
link |
in the universe, or at least in our galaxy,
link |
that means that we've passed at least one of the great filters
link |
or some of the great filters that we survived.
link |
Yeah, no, I think, I think it's Robin Hansen
link |
has a good way of, maybe others,
link |
they have a good way of thinking about this,
link |
that if there are no other intelligence creatures out there
link |
and that we've been able to detect,
link |
one possibility is that there's a filter ahead of us.
link |
And when you get a little more advanced,
link |
maybe in a hundred or a thousand or 10,000 years,
link |
things just get destroyed for some reason.
link |
The other one is the great filters behind us.
link |
That'll be good is that most planets don't even evolve life
link |
or if they don't evolve life,
link |
they don't involve intelligent life.
link |
Maybe we've gotten past that.
link |
And so now maybe we're on the good side of the great filter.
link |
So if we sort of rewind back and look at the thing
link |
where we could say something a little bit more comfortably
link |
at five years and 10 years out,
link |
you've written about jobs
link |
and the impact on sort of our economy and the jobs
link |
in terms of artificial intelligence that it might have.
link |
It's a fascinating question of what kind of jobs are safe,
link |
what kind of jobs are not.
link |
He maybe speak to your intuition
link |
about how we should think about AI
link |
changing the landscape of work.
link |
Well, this is a really important question
link |
because I think we're very far
link |
from artificial general intelligence,
link |
which is AI that can just do the full breadth
link |
of what humans can do.
link |
But we do have human level or super human level,
link |
narrow intelligence, narrow artificial intelligence.
link |
And obviously my calculator can do math a lot better
link |
And there's a lot of other things
link |
that machines can do better than I can.
link |
So which is which?
link |
We actually set out to address that question.
link |
With Tom Mitchell, I wrote a paper called
link |
What Can Machine Learning Do That Was in Science?
link |
And we went and interviewed a whole bunch of AI experts
link |
and kind of synthesized what they thought
link |
machine learning was good at and wasn't good at.
link |
And we came up with what we called a rubric,
link |
basically a set of questions you can ask about any task
link |
that will tell you whether it's likely to score high or low
link |
on suitability for machine learning.
link |
And then we've applied that to a bunch of tasks
link |
In fact, there's a data set of all the tasks
link |
in the US economy, believe it or not.
link |
The US government put it together,
link |
part of Bureau of Labor Statistics.
link |
They divide the economy into about 970 occupations
link |
like bus driver, economist, primary school teacher,
link |
And then for each one of them,
link |
they describe which tasks need to be done.
link |
Like for radiologists, there are 27 distinct tasks.
link |
So we went through all those tasks
link |
to see whether or not a machine could do them.
link |
And what we found interestingly was
link |
Brilliant study weather.
link |
That's so awesome.
link |
So what we found was that there was no occupation
link |
in our data set where machine learning just ran the table
link |
and did everything.
link |
And there was almost no occupation where machine learning
link |
didn't have like a significant ability to do things.
link |
Like take radiology, a lot of people,
link |
I hear it saying, you know, it's the end of radiology.
link |
And one of the 27 tasks is read medical images.
link |
Really important one, like it's kind of a core job.
link |
And machines have basically gotten as good
link |
or better than radiologists.
link |
There was just an article in Nature last week,
link |
but you know, they've been publishing them
link |
for the past few years showing that machine learning
link |
can do as well as humans
link |
on many kinds of diagnostic imaging tasks.
link |
But other things radiologists do, you know,
link |
they sometimes administer conscious sedation.
link |
They sometimes do physical exams.
link |
They have to synthesize the results
link |
and explain to the other doctors or to the patients.
link |
In all those categories,
link |
machine learning isn't really up to snuff yet.
link |
So that job, we're gonna see a lot of restructuring.
link |
Parts of the job, they'll hand over to machines,
link |
others, humans will do more of.
link |
That's been more or less the pattern in all of them.
link |
So, you know, to oversimplify,
link |
but we see a lot of restructuring, reorganization of work.
link |
And it's real gonna be a great time.
link |
It is a great time for smart entrepreneurs and managers
link |
to do that reinvention of work.
link |
I'm not gonna see mass unemployment
link |
to get more specifically to your question.
link |
The kinds of tasks that machines tend to be good at
link |
are a lot of routine problem solving,
link |
mapping inputs X into outputs Y.
link |
If you have a lot of data on the X's and the Y's,
link |
the inputs and the outputs,
link |
you can do that kind of mapping
link |
and find the relationships.
link |
They tend to not be very good at,
link |
even now, fine motor control and dexterity,
link |
emotional intelligence and human interactions,
link |
and thinking outside the box, creative work.
link |
If you give it a well structured task,
link |
machines can be very good at it,
link |
but even asking the right questions, that's hard.
link |
There's a quote that Andrew McAfee and I use
link |
in our book, Second Machine Age.
link |
Apparently Pablo Picasso was shown an early computer
link |
and he came away kind of unimpressed.
link |
He goes, well, I don't see all the fusses.
link |
All that does is answer questions.
link |
And, you know, to him,
link |
the interesting thing was asking the questions.
link |
Try to replace me GPT three, I dare you.
link |
Although some people think I'm a robot.
link |
You have this cool plot that shows,
link |
I just remember where economists landed,
link |
where I think the X axis is the income.
link |
And then the Y axis, I guess, aggregating the information
link |
of how replaceable the job is,
link |
or I think there's an index.
link |
There's a suitability for machine learning index, exactly.
link |
So we have all 970 occupations on that chart.
link |
And there's gatters in all four corners
link |
have some occupations,
link |
but there is a definite pattern,
link |
which is the lower wage occupations tend to have more tasks
link |
that are suitable for machine learning, like cashiers.
link |
I mean, anyone who's gone to a supermarket or CVS knows
link |
that, you know, they not only read barcodes,
link |
but they can recognize, you know, an apple and an orange
link |
and a lot of things that cashiers,
link |
humans used to be needed for.
link |
At the other end of the spectrum,
link |
there are some jobs like airline pilot
link |
that are among the highest paid in our economy,
link |
but also a lot of them are suitable for machine learning.
link |
A lot of those tasks are.
link |
And then, yeah, you mentioned economists.
link |
I couldn't help peaking at those.
link |
And they're paid a fair amount,
link |
maybe not as much as some of us think they should be.
link |
But they have some tasks they're suitable for machine learning,
link |
but for now, at least,
link |
most of the tasks that economists do
link |
didn't end up being in that category.
link |
And I should say, I didn't like create that data.
link |
We just took the analysis and that's what came out of it.
link |
And over time, that scatter plot will be updated
link |
as the technology improves.
link |
But it was just interesting to see the pattern there.
link |
And it is a little troubling insofar
link |
as if you just take the technology as it is today,
link |
it's likely to worsen income inequality
link |
on a lot of dimensions.
link |
So on this topic of the effect of AI
link |
on our landscape of work,
link |
one of the people that have been speaking about it
link |
in the public domain, public discourse
link |
is the presidential candidate, Andrew Yang.
link |
What are your thoughts about Andrew?
link |
What are your thoughts about UBI,
link |
that Universal Basic Income,
link |
that he made one of the core idea.
link |
By the way, he has like hundreds of ideas
link |
about like everything, it's kind of interesting.
link |
But what are your thoughts about him
link |
and what are your thoughts about UBI?
link |
Let me answer the question about his broader approach first.
link |
I mean, I just love that.
link |
He's really thoughtful, analytical.
link |
I agree with his values.
link |
So that's awesome.
link |
And he read my book and mentions it sometimes,
link |
so it makes me even more exciting.
link |
And the thing that he really made
link |
the centerpiece of his campaign was UBI.
link |
And I was originally kind of a fan of it.
link |
And then as I studied it more, I became less of a fan,
link |
although I'm beginning to come back a little bit.
link |
So let me tell you a little bit of my evolution.
link |
You know, as an economist,
link |
we have, by looking at the problem
link |
of people not having enough income
link |
and the simplest thing is, well, why don't we write them
link |
a check, problem solved.
link |
But then I talked to my sociologist friends
link |
and they really convinced me that just writing a check
link |
doesn't really get at the core values.
link |
You know, Voltaire once said that
link |
work solves three great ills, boredom, vice and need.
link |
And you know, you can deal with the need thing
link |
by writing a check,
link |
but people need a sense of meaning,
link |
they need something to do.
link |
And when, you know, say steelworkers or coal miners
link |
lost their jobs and were just given checks,
link |
alcoholism, depression, divorce,
link |
all those social indicators, drug use all went way up.
link |
People just weren't happy just sitting around
link |
collecting a check.
link |
Maybe it's part of the way they were raised.
link |
Maybe it's something innate in people
link |
that they need to feel wanted and needed.
link |
So it's not as simple as just writing people a check.
link |
You need to also give them a way to have a sense of purpose.
link |
And that was important to me.
link |
And the second thing is that as I mentioned earlier,
link |
you know, we are far from the end of work.
link |
You know, I don't buy the idea
link |
that there's just like not enough work to be done.
link |
I see like our cities need to be cleaned up.
link |
And I mean, robots can't do most of that.
link |
You know, we need to have better childcare,
link |
we need better healthcare,
link |
we need to take care of people who are mentally ill
link |
or older, we need to repair our roads.
link |
There's so much work that require at least partly,
link |
maybe entirely a human component.
link |
So rather than like write all these people off,
link |
well, let's find a way to repurpose them
link |
and keep them engaged.
link |
Now that said, I would like to see more buying power
link |
from people who are sort of at the bottom end
link |
The economy has been designed and evolved in a way
link |
that's I think very unfair to a lot of hardworking people.
link |
I see super hardworking people
link |
who aren't really seeing their wages grow
link |
over the past 20, 30 years,
link |
while some other people who have been super smart
link |
and or super lucky have made billions
link |
or hundreds of billions.
link |
And I don't think they need those hundreds of billions
link |
to have the right incentives to invent things.
link |
I think if you talk to almost any of them, as I have,
link |
they don't think that they need an extra $10 billion
link |
to do what they're doing.
link |
Most of them probably would love to do it
link |
for only a billion or maybe for nothing.
link |
For nothing, many of them, yeah.
link |
I mean, you know, an interesting point to make
link |
is like, do we think that Bill Gates
link |
would have founded Microsoft if tax rates were 70%?
link |
Well, we know he would have
link |
because they were tax rates of 70% when he founded it.
link |
So I don't think that's as big a deterrent
link |
and we could provide more buying power to people.
link |
My own favorite tool is the earned income tax credit,
link |
which is basically a way of supplementing income
link |
of people who have jobs and giving employers
link |
an incentive to hire even more people.
link |
The minimum wage can discourage employment,
link |
but the earned income tax credit encourages employment
link |
by supplementing people's wages.
link |
You know, if the employer can only afford to pay him $10
link |
for a task, the rest of us kick in another $5 or $10
link |
and bring their wages up to 15 or 20 total.
link |
And then they have more buying power
link |
than entrepreneurs are thinking, how can we cater to them?
link |
How can we make products for them?
link |
And it becomes a self reinforcing system
link |
where people are better off.
link |
And I had a good discussion where he suggested
link |
instead of a universal basic income,
link |
he suggested or instead of an unconditional basic income,
link |
how about a conditional basic income
link |
where the condition is you learn some new skills,
link |
we need to reskill our workforce.
link |
So let's make it easier for people to find ways
link |
to get those skills and get rewarded for doing them.
link |
And that's kind of a neat idea as well.
link |
That's really interesting.
link |
So I mean, one of the questions,
link |
one of the dreams of UBI is that
link |
you provide some little safety net while you retrain
link |
while you're learning new skill.
link |
But I think, I guess you're speaking to the intuition
link |
that that doesn't always,
link |
like there needs to be some incentive to reskill,
link |
to train, to learn new things.
link |
I mean, there are lots of self motivated people,
link |
but they're also people that maybe need a little guidance
link |
or help and I think it's a really hard question
link |
for someone who is losing a job in one area
link |
to know what is the new area I should be learning skills in
link |
and we could provide a much better set of tools
link |
and platforms that mapped it.
link |
Okay, here's a set of skills you already have.
link |
Here's something that's in demand.
link |
Let's create a path for you to go from where you are
link |
to where you need to be.
link |
So I'm a total, how do I put it nicely about myself?
link |
I'm totally clueless about the economy.
link |
It's not totally true, but pretty good approximation.
link |
If you were to try to fix our tax system
link |
and or maybe from another side,
link |
if there's fundamental problems in taxation
link |
or some fundamental problems about our economy,
link |
what would you try to fix?
link |
What would you try to speak to?
link |
You know, I definitely think our whole tax system,
link |
our political and economic system has gotten
link |
more and more screwed up over the past 20, 30 years.
link |
I don't think it's that hard to make headway
link |
I don't think we need to totally reinvent stuff.
link |
A lot of it is what I've elsewhere with Andy
link |
and others called economics 101.
link |
You know, there's just some basic principles
link |
that have worked really well in the 20th century
link |
that we sort of forgot, you know,
link |
in terms of investing in education,
link |
investing in infrastructure, welcoming immigrants,
link |
having a tax system that was more progressive and fair.
link |
At one point, tax rates were on top incomes,
link |
were significantly higher and they've come down a lot
link |
to the point where in many cases,
link |
they're lower now than they are for poorer people.
link |
So, and we could do things like an earned income tax credit
link |
to get a little more wonky.
link |
I'd like to see more Pagoovian taxes.
link |
What that means is you tax things that are bad
link |
instead of things that are good.
link |
So right now we tax labor, we tax capital,
link |
and which is unfortunate because one of the basic principles
link |
of economics, if you tax something,
link |
you tend to get less of it.
link |
So, you know, right now there's still work to be done
link |
and still capital to be invested in,
link |
but instead we should be taxing things like pollution
link |
And if we did that, we would have less pollution.
link |
So a carbon tax is, you know, almost every economist
link |
would say it's a no brainer,
link |
whether they're Republican or Democrat.
link |
Greg Mankiw, who's head of George Bush's
link |
Council of Economic Advisors, or Dick Schmollensy,
link |
who is another Republican economist degree,
link |
and of course a lot of a Democratic economist degree
link |
as well, if we taxed carbon,
link |
we could raise hundreds of billions of dollars.
link |
We could take that money and redistribute it
link |
through an earned income tax credit or other things
link |
so that overall our tax system would become more progressive.
link |
We could tax congestion.
link |
One of the things that kills me as an economist
link |
is every time I sit in a traffic jam,
link |
I know that it's completely unnecessary.
link |
It's this is complete waste of time.
link |
You could just visualize the cost and productivity
link |
that this is creating.
link |
Exactly, because they are taking costs for me
link |
and all the people around me.
link |
And if they charged a congestion tax,
link |
they would take that same amount of money
link |
and people would, it would streamline the roads,
link |
like when you're in Singapore, the traffic just flows
link |
because they have a congestion tax.
link |
They listen to economists.
link |
They invite it be and others to go talk to them.
link |
And then I'd still be paying,
link |
I'd be paying a congestion tax instead of paying in my time,
link |
but that money would now be available for healthcare,
link |
be available for infrastructure,
link |
or be available just to give to people
link |
so they could buy food or whatever.
link |
So it saddens me when you sit in a traffic jam,
link |
it's like taxing me and then taking that money
link |
and dumping it in the ocean, just like destroying it.
link |
So there are a lot of things like that
link |
that economists, and I'm not,
link |
I'm not like doing anything radical here.
link |
Most good economists would,
link |
I probably agree with me point by point on these things.
link |
And we could do those things in our whole economy,
link |
become much more efficient,
link |
it become fair, invest in R&D and research,
link |
which is close to a free lunch is what we have.
link |
My erstwhile MIT colleague, Bob Solo,
link |
got the Nobel Prize, not yesterday, but 30 years ago,
link |
for describing that most improvements
link |
in living standards come from tech progress.
link |
And Paul Romer later got a Nobel Prize
link |
for noting that investments in R&D and human capital
link |
can speed the rate of tech progress.
link |
So if we do that, then we'll be healthier and wealthier.
link |
Yeah, from an economics perspective,
link |
I remember taking an undergrad econ,
link |
you mentioned econ 101,
link |
it seemed from all the plots I saw that R&Ds,
link |
that's close to free lunches as we have.
link |
It seemed like obvious that we should do more research.
link |
but we should do basic research.
link |
I mean, so, well, let me just be clear,
link |
it'd be great if everybody did more research.
link |
And I would make these things be to apply development
link |
versus basic research.
link |
So apply development, like,
link |
how do we get this self driving car feature
link |
to work better in the Tesla?
link |
That's great for private companies
link |
because they can capture the value from that.
link |
If they make a better self driving car system,
link |
they can sell cars that are more valuable
link |
and then make money.
link |
So there's an incentive,
link |
there's not a big problem there.
link |
And smart companies, Amazon, Tesla and others
link |
are investing in it.
link |
The problem is with basic research,
link |
like coming up with core basic ideas,
link |
whether it's in nuclear fusion
link |
or artificial intelligence or biotech,
link |
there, if someone invents something,
link |
it's very hard for them to capture the benefits from it.
link |
It's shared by everybody, which is great in a way,
link |
but it means that they're not gonna have the incentives
link |
to put as much effort into it.
link |
There you need, it's a classic public good,
link |
there you need the government to be involved in it.
link |
And the US government used to be investing much more in R&D,
link |
but we have slashed that part of the government
link |
really foolishly and we're all poorer,
link |
significantly poorer as a result.
link |
Growth rates are down,
link |
we're not having the kind of scientific progress
link |
It's been sort of a short term, eating the seed corn,
link |
whatever metaphor you wanna use,
link |
where people grab some money,
link |
put it in their pockets today,
link |
but five, 10, 20 years later,
link |
they're a lot poorer than they otherwise would have been.
link |
So we're living through a pandemic right now,
link |
globally in the United States.
link |
From an economics perspective,
link |
how do you think this pandemic will change the world?
link |
It's been remarkable.
link |
And it's horrible how many people have suffered,
link |
the amount of death, the economic destruction.
link |
It's also striking just the amount of change in work
link |
In the last 20 weeks,
link |
I've seen more change than there were in the previous 20 years.
link |
There's been nothing like it
link |
since probably the World War II mobilization
link |
in terms of reorganizing our economy.
link |
The most obvious one is the shift to remote work.
link |
And I and many other people stopped going into the office
link |
and teaching my students in person.
link |
I did a study on this with a bunch of colleagues
link |
at MIT and elsewhere.
link |
And what we found was that before the pandemic,
link |
in the beginning of 2020,
link |
about one in six, a little over 15% of Americans
link |
were working remotely.
link |
When the pandemic hit,
link |
that grew steadily and hit 50%,
link |
roughly half of Americans working at home.
link |
So a complete transformation.
link |
And of course, it wasn't even,
link |
it wasn't like everybody did it.
link |
If you're an information worker, professional,
link |
if you work mainly with data,
link |
then you're much more likely to work at home.
link |
If you're a manufacturing worker,
link |
working with other people or physical things,
link |
then it wasn't so easy to work at home.
link |
And instead, those people were much more likely
link |
to become laid off or unemployed.
link |
So it's been something that has had very disparate effects
link |
on different parts of the workforce.
link |
Do you think it's gonna be sticky
link |
in a sense that after vaccine comes out
link |
and the economy reopens,
link |
do you think remote work will continue?
link |
That's a great question.
link |
My hypothesis is yes, a lot of it will.
link |
Of course, some of it will go back,
link |
but a surprising amount of it will stay.
link |
I personally, for instance,
link |
I moved my seminars, my academic seminars to Zoom,
link |
and I was surprised how well it worked.
link |
Yeah, I mean, obviously,
link |
we were able to reach a much broader audience.
link |
So we have people tuning in from Europe
link |
and other countries,
link |
just all over the United States for that matter.
link |
I also actually found that it would,
link |
in many ways, is more egalitarian.
link |
We use the chat feature and other tools,
link |
and grad students and others
link |
who might've been a little shy about speaking up,
link |
we now kind of have more of ability for lots of voices,
link |
and they're answering each other's questions
link |
so you kind of get parallel.
link |
Like if someone had some question about some of the data
link |
or a reference or whatever,
link |
then someone else in the chat would answer it.
link |
And the whole thing just became
link |
like a higher bandwidth, higher quality thing.
link |
So I thought that was kind of interesting.
link |
I think a lot of people are discovering
link |
that these tools that, thanks to technologies
link |
have been developed over the past decade,
link |
they're a lot more powerful than we thought.
link |
I mean, all the terrible things we've seen with COVID
link |
and the real failure of many of our institutions
link |
that I thought would work better.
link |
One area that's been a bright spot is our technologies.
link |
Bandwidth has held up pretty well,
link |
and all of our email and other tools
link |
have just scaled up kind of gracefully.
link |
So that's been a plus.
link |
Economists call this question
link |
of whether it'll go back a hysteresis.
link |
The question is like when you boil an egg,
link |
after it gets cold again, it stays hard.
link |
And I think that we're gonna have a fair amount
link |
of hysteresis in the economy.
link |
We're gonna move to this new,
link |
we have moved to a new remote work system,
link |
and it's not gonna snap all the way back
link |
to where it was before.
link |
One of the things that worries me is that the people
link |
with lots of followers on Twitter and people with voices,
link |
people that can, voices that can be magnified by,
link |
you know, reporters and all that kind of stuff
link |
are the people that fall into this category
link |
that we were referring to just now
link |
where they can still function and be successful
link |
And then there is a kind of quiet suffering
link |
of what feels like millions of people
link |
whose jobs are disturbed profoundly by this pandemic,
link |
but they don't have many followers on Twitter.
link |
What do we, and again, I apologize,
link |
but I've been reading the rise and fall of the third Reich
link |
and there's a connection to the depression
link |
on the American side.
link |
There's a deep, complicated connection
link |
to how suffering can turn into forces
link |
that potentially change the world in destructive ways.
link |
So like it's something I worry about is like,
link |
what is this suffering going to materialize itself
link |
in five, 10 years?
link |
Is that something you worry about, think about?
link |
It's like the center of what I worry about.
link |
And let me break it down to two parts.
link |
There's a moral and ethical aspect to it.
link |
We need to relieve this suffering.
link |
I mean, I share the values of I think most Americans,
link |
we like to see shared prosperity
link |
or most people on the planet.
link |
And we would like to see people not falling behind
link |
and they have fallen behind, not just due to COVID,
link |
but in the previous couple of decades,
link |
median income has barely moved,
link |
depending on how you measure it.
link |
And the incomes of the top 1% have skyrocketed.
link |
And part of that is due to the ways technology has been used.
link |
Part of this has been due to, frankly,
link |
our political system has continually shifted more wealth
link |
into those people who have the powerful interest.
link |
So there's just, I think, a moral imperative
link |
to do a better job.
link |
And ultimately, we're all going to be wealthier
link |
if more people can contribute,
link |
more people have the wherewithal.
link |
But the second thing is that there's a real political risk.
link |
I'm not a political scientist,
link |
but you don't have to be one, I think, to see
link |
how a lot of people are really upset
link |
with their getting a raw deal.
link |
And they want to smash the system in different ways
link |
And now, I think there are a lot of people
link |
who are looking at the political system
link |
and they feel like it's not working for them
link |
and they just want to do something radical.
link |
Unfortunately, demagogues have harnessed that
link |
in a way that is pretty destructive to the country.
link |
And an analogy I see is what happened with trade.
link |
Almost every economist thinks that free trade
link |
is a good thing, that when two people voluntarily exchange
link |
almost by definition, they're both better off
link |
if it's voluntary.
link |
And so generally, trade is a good thing,
link |
but they also recognize that trade can lead
link |
to uneven effects, that there can be winners and losers
link |
in some of the people who didn't have the skills
link |
to compete with somebody else or didn't have other assets.
link |
And so trade can shift prices in ways
link |
that are averse to some people.
link |
So there's a formula that economists have,
link |
which is that you have free trade,
link |
but then you compensate the people who are hurt.
link |
And free trade makes the pie bigger.
link |
And since the pie is bigger, it's possible
link |
for everyone to be better off.
link |
You can make the winners better off,
link |
but you can also compensate those who don't win.
link |
And so they end up being better off as well.
link |
What happened was that we didn't fulfill that promise.
link |
We did have some more increased free trade
link |
in the 80s and 90s, but we didn't compensate
link |
the people who were hurt.
link |
And so they felt like the people in power
link |
were negged on the bargain, and I think they did.
link |
And so then there's a backlash against trade.
link |
And now both political parties,
link |
but especially Trump and company,
link |
have really pushed back against free trade.
link |
Ultimately, that's bad for the country.
link |
Ultimately, that's bad for living standards,
link |
but in a way I can understand
link |
that people felt they were betrayed.
link |
Technology has a lot of similar characteristics.
link |
Technology can make us all better off.
link |
It makes the pie bigger, it creates wealth and health,
link |
but it can also be uneven.
link |
Not everyone automatically benefits.
link |
It's possible for some people,
link |
even a majority of people to get left behind,
link |
while a small group benefits.
link |
What most economists would say,
link |
well, let's make the pie bigger,
link |
but let's make sure we adjust the system
link |
so we compensate the people who are hurt.
link |
And since the pie is bigger, we can make the rich richer,
link |
we can make the middle class richer,
link |
we can make the poor richer.
link |
Mathematically, everyone could be better off.
link |
But again, we're not doing that.
link |
And again, people are saying, this isn't working for us.
link |
And again, instead of fixing the distribution,
link |
a lot of people are beginning to say,
link |
hey, technology sucks, we've got to stop it.
link |
Let's throw rocks at the Google bus.
link |
And there were the Luddites almost exactly 200 years ago
link |
who smashed the looms and the spinning machines
link |
because they felt like those machines weren't helping them.
link |
We have a real imperative,
link |
not just to do the morally right thing,
link |
but to do the thing that is gonna save the country,
link |
which is make sure that we create,
link |
not just prosperity, but shared prosperity.
link |
So you've been at MIT for over 30 years, I think.
link |
Don't tell everyone how old I am.
link |
Yeah, no, that's true, that's true.
link |
And you're now moved to Stanford.
link |
I'm gonna try not to say anything
link |
about how great MIT is.
link |
What's that move been like?
link |
What, it's East Coast, the West Coast?
link |
Well, MIT is great.
link |
MIT has been very good to me.
link |
It continues to be very good to me.
link |
It's an amazing place.
link |
There's, I continue to have so many amazing friends
link |
and colleagues there.
link |
I'm very fortunate to have been able
link |
to spend a lot of time at MIT.
link |
Stanford's also amazing.
link |
And part of what attracted me out here
link |
was not just the weather, but also Silicon Valley,
link |
let's face it, is really more of the epicenter
link |
of the technological revolution.
link |
And I wanna be close to the people
link |
who are inventing AI and elsewhere.
link |
A lot of it is being invested at MIT, for that matter,
link |
in Europe and China and elsewhere in NIA.
link |
But being a little closer to some of the key technologists
link |
was something that was important to me.
link |
And it may be shallow, but I also do enjoy the good weather.
link |
And I felt a little ripped off
link |
when I came here a couple of months ago.
link |
And immediately there are the fires
link |
and my eyes were burning, the sky was orange,
link |
and there's the heat waves.
link |
And so it wasn't exactly what I'd been promised,
link |
but fingers crossed it'll get back to better.
link |
But maybe on a brief aside,
link |
there's been some criticism of academia
link |
and universities and different avenues.
link |
And I, as a person who's gotten to enjoy universities
link |
from the pure playground of ideas that it can be,
link |
always kind of try to find the words
link |
to tell people that these are magical places.
link |
Is there something that you can speak to
link |
that is beautiful or powerful about universities?
link |
I mean, first off, I mean,
link |
economists have this concept called revealed preference.
link |
You can ask people what they say,
link |
or you can watch what they do.
link |
And so obviously by reveal preferences,
link |
I love academia, I'm happy here.
link |
I could be doing lots of other things,
link |
but it's something I enjoy a lot.
link |
And I think the word magical is exactly right.
link |
At least it is for me.
link |
I do what I love, you know,
link |
hopefully my Dean won't be listening,
link |
but I would do this for free.
link |
You know, it's just what I like to do.
link |
I like to do research.
link |
I love to have conversations like this with you
link |
and with my students, with my fellow colleagues.
link |
I love being around the smartest people I can find
link |
and learning something from them
link |
and having them challenge me.
link |
And that just gives me joy.
link |
And every day I find something new and exciting to work on.
link |
And a university environment is really filled
link |
with other people who feel that way.
link |
And so I feel very fortunate to be part of it.
link |
And I'm lucky that I'm in a society
link |
where I can actually get paid for it
link |
and put food on the table
link |
while doing the stuff that I really love.
link |
And I hope someday everybody can have jobs
link |
that are like that.
link |
And I appreciate that it's not necessarily easy
link |
for everybody to have a job that they both love
link |
and also they get paid for.
link |
So there are things that don't go well in academia,
link |
but by and large, I think it's a kind of,
link |
you know, kinder, gentler version of a lot of the world.
link |
You know, we sort of cut each other a little slack
link |
on things like, you know, on just a lot of things.
link |
You know, of course there's harsh debates
link |
and discussions about things
link |
and some petty politics here and there.
link |
Personally, I try to stay away
link |
from most of that sort of politics.
link |
It's not my thing.
link |
And so it doesn't affect me most of the time,
link |
sometimes a little bit maybe.
link |
But, you know, being able to pull together
link |
something we have the digital economy lab,
link |
we get all these brilliant grad students
link |
and undergraduates and postdocs
link |
that are just doing stuff that I learn from.
link |
And every one of them has some aspect
link |
of what they're doing that's just,
link |
I couldn't even understand.
link |
It's like way, way more brilliant.
link |
And that's really, to me, actually, I really enjoy that.
link |
Being in a room with lots of other smart people.
link |
And Stanford has made it very easy to attract,
link |
you know, those people.
link |
I just, you know, say I'm gonna do a seminar or whatever
link |
and the people come, they come and wanna work with me.
link |
We get funding, we get data sets
link |
and it's come together real nicely.
link |
And the rest is just fun.
link |
And we feel like we're working on important problems,
link |
you know, and we're doing things that, you know,
link |
I think our first order in terms of
link |
what's important in the world
link |
and that's very satisfying to me.
link |
Maybe a bit of a fun question.
link |
What three books, technical, fiction, philosophical,
link |
you've enjoyed, had a big impact in your life?
link |
Well, I guess I go back to like my teen years
link |
and, you know, I read Sid Artha,
link |
which is a philosophical book
link |
and kind of helps keep me centered.
link |
Yeah, my Herman Hess, exactly.
link |
Don't get too wrapped up in material things
link |
or other things and just sort of, you know,
link |
try to find peace on things.
link |
A book that actually influenced me a lot
link |
in terms of my career was called
link |
The Worldly Philosophers by Robert Howe Brenner.
link |
It's actually about economists.
link |
It goes through a series of different companies,
link |
written in a very lively form.
link |
And it probably sounds boring,
link |
but it did describe whether it's Adam Smith,
link |
or Karl Marx, or John Maynard Keynes
link |
and each of them sort of what their key insights were,
link |
but also kind of their personalities.
link |
And I think that's one of the reasons
link |
I became an economist was just understanding
link |
how they grappled with the big questions of the world.
link |
So would you recommend it
link |
as a good whirlwind overview of the history of economics?
link |
Yeah, yeah, I think that's exactly right.
link |
It kind of takes you through the different things
link |
and, you know, so you can understand how they reach,
link |
thinking some of the strengths and weaknesses.
link |
I mean, probably there's a little out of date now.
link |
It needs to be updated a bit, but, you know,
link |
you could at least look through
link |
the first couple hundred years of economics,
link |
which is not a bad place to start.
link |
More recently, I mean, a book I really enjoyed
link |
is by my friend and colleague, Max Tagmark,
link |
You should have him on your podcast
link |
if you haven't already.
link |
He was episode number one.
link |
And he's back, he'll be back, he'll be back soon.
link |
Yeah, no, he's terrific.
link |
I love the way his brain works
link |
and he makes you think about profound things.
link |
He's got such a joyful approach to life.
link |
And so that's been a great book.
link |
And, you know, I learn a lot from it, I think everybody,
link |
but he explains it in a way,
link |
even though he's so brilliant,
link |
that, you know, everyone can understand,
link |
that I can understand.
link |
You know, that's three, but let me mention
link |
maybe one or two others.
link |
I mean, I recently read More From Less
link |
by my sometimes coauthor, Andrew McAfee.
link |
It made me optimistic about how we can continue
link |
to have rising living standards
link |
while living more lightly on the planet.
link |
In fact, because of higher living standards,
link |
because of technology,
link |
because of digitization that I mentioned,
link |
we don't have to have as big an impact on the planet.
link |
And that's a great story to tell
link |
and he documents it very carefully.
link |
You know, a personal kind of self help book
link |
that I found kind of useful, People is Atomic Habits.
link |
I think it's, what's his name?
link |
Yeah, James Clear.
link |
He's just, yeah, it's a good name
link |
because he writes very clearly.
link |
And, you know, most of the sentences I read in that book,
link |
I was like, yeah, I know that,
link |
but it just really helps to have somebody
link |
like remind you and tell you
link |
and kind of just reinforce it and...
link |
So build habits in your life
link |
that you hope to have a positive impact
link |
and don't have to make it big things.
link |
It could be just tiny little...
link |
Exactly, I mean, the word atomic,
link |
it's a little bit of a pun, I think he says.
link |
You know, atomic means a really small thing
link |
to take these little things,
link |
but also like atomic power,
link |
it can have like, you know, big impact.
link |
That's funny, yeah.
link |
The biggest ridiculous question,
link |
especially to ask an economist,
link |
but also a human being, what's the meaning of life?
link |
I hope you've gotten the answer to that from somebody else.
link |
I think we're all still working on that one,
link |
You know, I actually learned a lot from my son, Luke,
link |
and he's 19 now, but he's always loved philosophy
link |
and he reads way more sophisticated philosophy than I do.
link |
I once took him to Oxford
link |
and he spent the whole time like
link |
pulling all these obscure books down and reading them.
link |
And a couple of years ago, we had this argument
link |
and he was trying to convince me that hedonism
link |
was the ultimate, you know, meaning of life,
link |
just pleasure, yeah, seeking and...
link |
Well, how old was he at the time?
link |
But he made a really good like intellectual argument
link |
for it too, and you know...
link |
But it just didn't strike me as right.
link |
And I think that, you know,
link |
while I am kind of a utilitarian,
link |
like, you know, I do think we should do the grace,
link |
good for the grace number, that's just too shallow.
link |
And I think I've convinced myself
link |
that real happiness doesn't come from seeking pleasure.
link |
It's kind of a little, it's ironic.
link |
Like if you really focus on being happy,
link |
I think it doesn't work.
link |
You gotta like be doing something bigger.
link |
It's, I think the analogy I sometimes use is, you know,
link |
when you look at a dim star in the sky,
link |
if you look right at it, it kind of disappears,
link |
but you have to look a little to the side
link |
and then the parts of your retina
link |
that are better at absorbing light,
link |
you know, can pick it up better.
link |
It's the same thing with happiness.
link |
I think you need to sort of find something other goal,
link |
something, some meaning in life.
link |
And that ultimately makes you happier
link |
than if you go squarely at just pleasure.
link |
And so for me, you know, the kind of research I do
link |
that I think is trying to change the world,
link |
make the world a better place.
link |
And I'm not like an evolutionary psychologist,
link |
but my guess is that our brains are wired,
link |
not just for pleasure, but we're social animals
link |
and we're wired to like help others.
link |
And ultimately, you know, that's something
link |
that's really deeply rooted in our psyche.
link |
And if we do help others, if we do,
link |
or at least feel like we're helping others,
link |
you know, our reward systems kick in
link |
and we end up being more deeply satisfied
link |
than if we just do something selfish and shallow.
link |
Beautifully put, I don't think there's a better way
link |
You're one of the people when I first showed up at MIT
link |
that made me proud to be at MIT.
link |
So it's so sad that you're now at Stanford,
link |
but I'm sure you'll do wonderful things at Stanford as well.
link |
I can't wait till future books
link |
and people should definitely read the other books.
link |
Well, thank you so much.
link |
And I think we're all,
link |
we're all part of the invisible college as we call it.
link |
You know, we're all part of this intellectual
link |
and human community where we all can learn from each other.
link |
It doesn't really matter physically
link |
where we are so much anymore.
link |
Beautiful. Thanks for talking today.
link |
Thanks for listening to this conversation
link |
with Eric Brynjalsson and thank you to our sponsors.
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And now let me leave you with some words
link |
from Albert Einstein.
link |
It has become appallingly obvious
link |
that our technology has exceeded our humanity.
link |
Thank you for listening and hope to see you next time.