Speaker 1: Sleepwalkers is a production of I Heart Radio and unusual productions.
Speaker 1: AI will make phenomenal companies and tycoons faster, and it
Speaker 1: will also displace jobs faster than computers and the Internet.
Speaker 1: It's already happening. That's Kai Fu Lee speaking, the former
Speaker 1: head of Google China and the so called oracle of AI.
Speaker 1: I think there are at least two issues involved. One
Speaker 1: is how to do income redistribution, and that is a
Speaker 1: very complex issue. I'm not an expert, but one way
Speaker 1: or another, the ultra rich who did extremely well based
Speaker 1: on AI or other reasons, I think somehow need to
Speaker 1: help the people who are under privileged or even victimized
Speaker 1: by technology. The exact mechanism I don't know, but if
Speaker 1: we don't do it, redistribution is going to be a
Speaker 1: serious matter for our social stability. It's not actually a
Speaker 1: underprivileged minority, it will become an underprivileged majority. The benefits
Speaker 1: of the AI revolution will not be evenly distributed, and
Speaker 1: according to Kaifu, automation will replace fort of jobs worldwide
Speaker 1: in the next fifteen years. The second part is how
Speaker 1: do we help people whose jobs have been displaced find
Speaker 1: the new beginning? We ask the question what can AI
Speaker 1: and automation not do? That is the central question this episode,
Speaker 1: as AI and Automation displays more and more jobs, What
Speaker 1: will be left for us to do and who will
Speaker 1: be qualified to do it? Today will explore the automated
Speaker 1: economy and the changes it will bring. Im as Velashen
Speaker 1: Welcome to Sleepwalkers. So, Carol, when I hear Kaifou talking
Speaker 1: about jobs being lost to AI, my mind goes immediately
Speaker 1: to driverless cars and self driving cars replacing taxis, um,
Speaker 1: long distance trucking, that kind of thing. Yeah, but there's
Speaker 1: also you know, agriculture, like combine harvests, like robots who
Speaker 1: are picking fruit. Um. Washington State actually announced that next
Speaker 1: season they're going to be rolling out these vacuum harvesters
Speaker 1: that use AI to identify and pick only ripe apples. Wow,
Speaker 1: so not only picking the fruit, but also being smart
Speaker 1: about which fruit it picks. That's right, the ripe stuff,
Speaker 1: the stuff. And there's actually this raspberry picking robot in
Speaker 1: the UK that was funded by some British supermarkets and
Speaker 1: those robots can pick twenty five thousand berries a day
Speaker 1: versus a humans fifteen thousand in an eight hour day,
Speaker 1: and also remember this, eight hour days for human being
Speaker 1: is a long day for a robot. A robot doesn't
Speaker 1: know what a long day is, nor does it know
Speaker 1: what a short day is. And it can work into
Speaker 1: the night right and when we force ourselves into comparison
Speaker 1: with these robots, that kind of creates very realistic expectations
Speaker 1: for workers can do. Interesting is not just jobs that
Speaker 1: require mechanical skills that Kaifu thinks will be lost to automation.
Speaker 1: And AI actually doesn't distinguish between white collar and blue
Speaker 1: collar jobs. So any job that has a routine element,
Speaker 1: whether it's underwriting loans or telemarketing or researching, you know,
Speaker 1: this is a lot of work. The first AI podcast
Speaker 1: may not be too far off. Um. It actually reminds
Speaker 1: me the episode we did about AI and creativity that
Speaker 1: algorithms that can write poetry and music and screenplays are
Speaker 1: already here. This is not some robot apocalypse in the
Speaker 1: distant future. Job displacement is with us. Julian, You've got
Speaker 1: in touch with somebody who's seeing this play out in
Speaker 1: real time. Yeah, it did. His name's Wild Kankowski and
Speaker 1: he lives in Florida, all around the city whatever direction
Speaker 1: we're gonna go. We know where every every McDonald's pretty
Speaker 1: much is on the did a job well. A lot
Speaker 1: of the people know us because we go in there
Speaker 1: all the time. A lot of them know me because
Speaker 1: not too many people get a medium coffee with twelve creams. Yeah,
Speaker 1: as what is taking a huge number of creams and
Speaker 1: his coffee? What? He owns the pool screens and repair
Speaker 1: business in Orlando, Florida. His job takes him all around town,
Speaker 1: but every morning starts the same way Adam McDonald's and
Speaker 1: recently what he has seen a change. They just started
Speaker 1: to show up, probably about a year or so ago.
Speaker 1: That way, when we go to a counter, people are
Speaker 1: getting mad because they want you to go to use
Speaker 1: the key off and I'm walking up to the counter
Speaker 1: wanting to get my coffee and get on on our day.
Speaker 1: They're like, oh, you got to use the kios so
Speaker 1: and then they want me to hit the screen. The
Speaker 1: screen says, go to this thing, go to beverage. Okay,
Speaker 1: what kind of beverage? Well, okay, go the coffee, but
Speaker 1: what do you want? Ice coffee? This? That? And then
Speaker 1: instead of me saying twelve cream and she hears me.
Speaker 1: Now I get to hit the machine like twelve times
Speaker 1: that that that that that that that that that that
Speaker 1: twelve times to get it, because that's how many times
Speaker 1: I get to hit it to get to twelve. The
Speaker 1: thing is knocking someone out of a job. We've all
Speaker 1: been wally stuck at a self checkout or yelling at
Speaker 1: an automated phone menu that refuses to understand what we're saying.
Speaker 1: But those interactions are not just frustrating for us. They're
Speaker 1: real world examples of jobs being displaced by technology, and
Speaker 1: they don't only affect the people whose jobs are threatened.
Speaker 1: We're in a lot of different McDonald's and I probably
Speaker 1: recognize every single person in there. Some people I've known
Speaker 1: probably ten fifteen years, and they know who I am.
Speaker 1: You know, they're friendly enough to make you feel a
Speaker 1: little special there. That way, I guess we might be
Speaker 1: walking through a store and then I'll see those people
Speaker 1: and I'll go over and them say, yeah, you're for
Speaker 1: McDonald's or that, and then they'll be like, yeah, I
Speaker 1: know who you are. Then you actually get them meet
Speaker 1: and greet someone and make a conversation for a minute
Speaker 1: or two. That way, why would human contact when you
Speaker 1: talking to a person for a second and getting my
Speaker 1: food and paying them in another two seconds. There shouldn't
Speaker 1: have been nothing wrong with that process. So, Julie, how
Speaker 1: did this come about? What made you want to include
Speaker 1: Wally story in the podcast? Well, for one thing, I
Speaker 1: love Wally, but these are also familiar stories, right, I mean,
Speaker 1: and while he's been able to see this one play
Speaker 1: out over time, where you can see how just changing
Speaker 1: one part of one task the way he orders a
Speaker 1: coffee has actually had this ripple effect that also follows
Speaker 1: him around as he goes about his day. Yeah. I
Speaker 1: was especially struck by Wally story because it's easy to
Speaker 1: talk about automation and job displacement as these big abstract ideas,
Speaker 1: but here's somebody who's actually felt it. Even though it's
Speaker 1: not his job that's been lost. Is something that affects
Speaker 1: the whole community. You know, I don't mean to be
Speaker 1: super nestar algic, but a lot of great movies and
Speaker 1: great young adult novels have you know, the teenage girl
Speaker 1: who's angsty and you know works at the Friar and
Speaker 1: you know, now it's just like you're gonna have like
Speaker 1: an angsty data scientist, you know, mulling over the express
Speaker 1: checkout crouched over the screen. Well, those those golden arches,
Speaker 1: they are very enduring symbol for America UM And earlier
Speaker 1: this year, McDonald's acquired an AI company for three hundred
Speaker 1: million dollars. It was their biggest acquisition for twenty years.
Speaker 1: And it's all about predicting what people might order before
Speaker 1: they even arrive at the store. So even the days
Speaker 1: of Kiosks maybe numbered, maybe we'll be nostalgic about them
Speaker 1: in twenty years, but nonetheless, this AI acquisition could ultimately
Speaker 1: lead to a better customer experience. And it's important to
Speaker 1: remember that the AI revolution doesn't need to be just
Speaker 1: about displacing jobs. It can also be about augmenting us
Speaker 1: and our experience. One person working on human machine partnership
Speaker 1: is Gil Pratt see EEO of the Toyota Research Institute.
Speaker 1: Many of our colleagues at other companies are really focused
Speaker 1: on building only the self driving car, where you replace
Speaker 1: the driver with an AI system. But we also have
Speaker 1: this other track of building something that we call the Guardian,
Speaker 1: which is meant to safeguard a human being when they drive,
Speaker 1: to avoid accidents and to avoid crashes. I think the
Speaker 1: Guardian approach has been at odds because of money. The
Speaker 1: economic desire to replace the driver in a taxi is
Speaker 1: very large, and a lot of companies are sort of
Speaker 1: going after this attractive idea of automating out the human
Speaker 1: being from driving taxis. But you know, Toyota is first
Speaker 1: and foremost a car company, which means that we have
Speaker 1: this business of making cars. We also want to make
Speaker 1: cars a lot more safe, and we also want to
Speaker 1: make them a lot more fun. Gil makes an important
Speaker 1: point today, our innovation is driven by the market. Companies
Speaker 1: like Uber in tested to keep their valuations high by
Speaker 1: promising their investors that they will be able to do
Speaker 1: better business in future by replacing human drivers. Toyota is
Speaker 1: actually an investor in Uber, but it's primary business is
Speaker 1: car manufacturing, so there that is on enhancing the abilities
Speaker 1: of human drivers rather than replacing them, making driving more
Speaker 1: fun and Gil's humanistic approach to technology is also being
Speaker 1: applied to other problems at the Toyota Research Institute. We
Speaker 1: want to allow people to age in place with dignity,
Speaker 1: and in particular, we want to help them by amplifying
Speaker 1: their abilities to make up for what was lost, rather
Speaker 1: than replacing their abilities. And make them feel as if
Speaker 1: they're elderly. It's a subtle difference, and it's very easy
Speaker 1: to get it wrong. It's very easy to build a
Speaker 1: technology that is ostensibly going to help some someone, but
Speaker 1: it's what it's really doing is offloading work from them
Speaker 1: and making them feel they can't do it and therefore
Speaker 1: they're old and they should just sit in a chair.
Speaker 1: It's much harder to figure out a way, particularly in
Speaker 1: the robotics field, to continue to engage the person so
Speaker 1: that they feel like they can do it themselves. And
Speaker 1: that's a little bit of a difference in how we
Speaker 1: try to do things. There's one that we've recently started
Speaker 1: to show, which is a machine called the Buddy, and
Speaker 1: this idea is one where older people have a lot
Speaker 1: of difficulty reaching down low to pick up things from
Speaker 1: the ground and difficulty moving heavy things, and so we're
Speaker 1: working on a machine that still has the human in
Speaker 1: the loop, but makes it much easier for them to
Speaker 1: do that task. But it understands that no matter how
Speaker 1: much robotics may be able to help solve the practical
Speaker 1: challenges of life as an older person, it can never
Speaker 1: replace a human cab provider. Just to be very very clear,
Speaker 1: we don't want to replace people as companions. We think
Speaker 1: it what human beings want most of all in a
Speaker 1: companion is another human being, so companion. This brings us
Speaker 1: back to what Kaifu was saying right at the top
Speaker 1: of the episode, what can AI and automation not do?
Speaker 1: So Yeah, Gil acknowledges that no matter how much progress
Speaker 1: is made in the field of robotics to help elderly people,
Speaker 1: nothing's going to make up for human contact. I actually
Speaker 1: was able to talk to Sherry Turkle, who's a professor
Speaker 1: at m i T who talks a lot about human
Speaker 1: beings and their relationship with technology, and she talks about
Speaker 1: this fluffy seal robot called Pero, which is used in
Speaker 1: nursing homes to soothe Alzheimer's patients. And it can simulate
Speaker 1: this like affectionate little animal, and it can be really
Speaker 1: effective at drawing people out of their shells when they're
Speaker 1: otherwise hard to reach or feeling disoriented. On the other hand,
Speaker 1: and this is Sherry's argument, it becomes really easy for
Speaker 1: family members to be like, well, you know, my grandpa
Speaker 1: has this, you know, seal at home. I don't need
Speaker 1: to go visit him all the time. And I know
Speaker 1: that sounds extreme, but it's more of the idea of
Speaker 1: the fact that we're using these robots to make us
Speaker 1: feel better about calming people who we could otherwise have
Speaker 1: strong relationships with. Yeah, and I think it also normalizes
Speaker 1: the idea of interacting with robots or technology instead of
Speaker 1: real people. And that's painful. That's what wal he was
Speaker 1: really talking about. Yes, it's frustrating to have to use
Speaker 1: the Kiosk when you want twelve creems with your coffee.
Speaker 1: But more important, Leader Rhodes Community bonds. It's no wonder
Speaker 1: that a company like McDonald's is spending a ton of
Speaker 1: money on this. It makes them more efficient and profitable
Speaker 1: if they don't have to pay people. Yeah, and it's
Speaker 1: hard to turn back the clocks. You know. Donald Trump
Speaker 1: talks about bringing back the cold jobs, but jobs that
Speaker 1: have been lost are very hard to recreate. It doesn't
Speaker 1: make me think about Kaifu's comment at the top of
Speaker 1: the episode about the underprivileged majority. Uvell know Harari, who's
Speaker 1: coming to join us later in the series, talks about
Speaker 1: a useless class. When we come back, we look at
Speaker 1: what this means for the people at the sharp end
Speaker 1: the people losing their jobs to automation, and at some
Speaker 1: of the proposed solutions. According to an OXFAM International report
Speaker 1: published earlier this year, the twenty six richest billionaires in
Speaker 1: the world have as much wealth as the poorest three
Speaker 1: point eight billion people, and many of those billionaires made
Speaker 1: their fortunes from technology. Jeff Bezos is the world's richest
Speaker 1: person thanks to Amazon. Meanwhile, Amazon is investing hundreds of
Speaker 1: millions of dollars in automating their supply chain, in other words,
Speaker 1: attempting to cut out the labor force who made the
Speaker 1: business possible. It's a bit like Uber's investment in self
Speaker 1: driving technology. So what jobs might be safe from the
Speaker 1: relentless march towards automation, I asked Kai Fu Lee. My
Speaker 1: general feeling is that these will be the human interaction jobs,
Speaker 1: the compassion and empathetic jobs, the jobs that we expect
Speaker 1: a human and refused to work with a robot. That
Speaker 1: would doubly ensure these jobs are safe as one AI
Speaker 1: can't do them now, and too, even if AI got better,
Speaker 1: customers don't accept it, then those jobs will become the
Speaker 1: right areas to retrain people to move into so jobs
Speaker 1: like nurses, Nanni's elderly care, high end jobs like psychiatrists
Speaker 1: and doctors, because the future it will be different. AI
Speaker 1: can do the analytical part, but the doctor will still
Speaker 1: need to provide the warmth and the human contact that
Speaker 1: the patient expects during the worst period of vulnerability. What
Speaker 1: we may move more towards ordering from kiosks and help menus,
Speaker 1: or not even needing to order at all. Kaifu agrees
Speaker 1: with Gil, will still need to human touch in a
Speaker 1: range of industries, many of them senters around care and
Speaker 1: human services, and it's striking to hear these two pioneers
Speaker 1: of new technology. Kaifu and AI and Gil in robotics agree,
Speaker 1: both arguing that automation might increase the value of what
Speaker 1: is uniquely human. Guilt terms the history. To back up
Speaker 1: his argument, he looks at how our understanding of our
Speaker 1: own value as humans shifted during the Industrial Revolution away
Speaker 1: from the ability of our bodies towards the ability of
Speaker 1: our minds. You know, if you go back in history
Speaker 1: and you say, how did people earn a living back
Speaker 1: in the days of mechanical work, There wasn't you know,
Speaker 1: steam engines, no use of gasoline or oil or anything
Speaker 1: like that. And the answer was that the economic capital
Speaker 1: that a human being would have just by being born
Speaker 1: was primarily mechanical. So our muscles made us worthwhile at
Speaker 1: a minimum level, and machines effectively took over most of
Speaker 1: the mechanical work that we do, and so we now
Speaker 1: are valued mostly what we can do with our minds,
Speaker 1: assuming that this next stage of AI occurs where most
Speaker 1: of the mental labor that is done is displaced. What
Speaker 1: I think we need to think about now is what
Speaker 1: will we do then? And we need to think about
Speaker 1: it even if this next stage of A doesn't come
Speaker 1: for a while, because we went from mechanical to mental.
Speaker 1: Is there something next? Is there something next? That is
Speaker 1: the trillion dollar question? According to Guilty, industrial revolution led
Speaker 1: us to place more value on the mind than the muscle.
Speaker 1: Now that a I can increasingly perform mental labor, but
Speaker 1: we find a new source of value. And could it
Speaker 1: be like CAIFU hinted at as well, some emotional connection.
Speaker 1: When I read a story to my son, it matters
Speaker 1: a whole lot to him. When I read a story
Speaker 1: to my mother, it's very much the same thing. So
Speaker 1: could we actually decide to increase the value that we
Speaker 1: pay for social work. There's many, many different jobs that
Speaker 1: really should be paid much much higher than they are now,
Speaker 1: jobs of teaching and helping so forth. And so I'm
Speaker 1: an optimist that we can find an answer, but I
Speaker 1: think we need to realize the difficulty in order to
Speaker 1: move towards that answer. The difficulty is huge because as
Speaker 1: of now, excepting the luxury, the market does not reward
Speaker 1: the kind of human contact that Kaifu and Gil allude to.
Speaker 1: And while we, like Wally may wish for our food
Speaker 1: orders not to be automated, how much more would we
Speaker 1: pay for human contact? How much more could we afford
Speaker 1: to pay. Part of the problem is that automation is
Speaker 1: exacerbating the gap between rich and poor. Technology companies can
Speaker 1: increasingly create wealth without needing to pay the wages of
Speaker 1: additional employees. That's the secret behind that word you hear
Speaker 1: so often scale, which is why Kai Fu Lee proposes
Speaker 1: a radical solution. If we start to redistribute the income
Speaker 1: that is taking away the power of the ultra ridge,
Speaker 1: If we start to give the people who are stripped
Speaker 1: of their current jobs a new job that has not
Speaker 1: only income but also meaning, I think um people would
Speaker 1: be more fulfilled, their children at least would have a
Speaker 1: chance just to pause. Kai Foo Lee is a hugely
Speaker 1: successful international investor arguing that we need to overturn and
Speaker 1: one of the most fundamental assumptions of American society that
Speaker 1: the market should be allowed to set the price. And
Speaker 1: Kaifu is not alone. Others in Silicon Valley are calling
Speaker 1: for a so called universal basic income as SI pen
Speaker 1: pay to all citizens to acknowledge an increasingly broken relationship
Speaker 1: between labor and value. Today, we're nowhere close on either
Speaker 1: of those ideas, but a growing course of inside voices
Speaker 1: is acknowledging that automation will bring further disruption to society,
Speaker 1: and others have even greater fears. You may remember Ian
Speaker 1: Bremer from our episode on China and Surveillance. He's a
Speaker 1: political scientist and the author of Us Versus Them, The
Speaker 1: Failure of Globalism. I am less worried about just jobs
Speaker 1: going away, then I am about technology facilitating the creation
Speaker 1: of completely different types of human beings. What happens when
Speaker 1: you have the ability to actually provide comp copletely different
Speaker 1: sets of cognitive skills to human beings that have access
Speaker 1: to certain types of new technology ian sphere is that
Speaker 1: as technology improves, the rituals simply reproduced their privilege through
Speaker 1: elite universities and professional networks, they may start to upgrade
Speaker 1: their very hardware, making social mobility even harder for those
Speaker 1: who can't afford the same modifications. Better memory retention, better
Speaker 1: pattern recognition, more ability to link to real time information,
Speaker 1: and the global net I mean, ability not to sleep
Speaker 1: for longer periods of time, all of this sort of thing. Right,
Speaker 1: The danger is that I don't care how much money,
Speaker 1: how much wealth in society, and when you start creating
Speaker 1: that kind of differentiation, everything we know about human history
Speaker 1: is that that doesn't end well. Those other people that
Speaker 1: aren't as capable get treated like animals or worse. And
Speaker 1: I am very deeply worried that the speed of technol
Speaker 1: logical transformation, coupled with the speed of this new industrial revolution,
Speaker 1: makes it much more likely that large numbers of people
Speaker 1: in our own societies, not in other countries, but like
Speaker 1: right here, are suddenly not going to have that capacity,
Speaker 1: and we're going to treat them as different types of humans,
Speaker 1: maybe not even as humans at all. This is the
Speaker 1: truly dystopient future that we will fear carat this concept
Speaker 1: of a two track humanity facilitated by technology, where some
Speaker 1: people have value and others don't. Yeah, you know, this
Speaker 1: is the dark version of trans humanism, which we're going
Speaker 1: to talk about later in the series. But you know
Speaker 1: it's not some sci fi fantasy. Our favorite pre super
Speaker 1: villain Elon Musk, founded Neuralink, which aims to create brain
Speaker 1: computer interfaces. Like why do we need that? Well, I
Speaker 1: guess because in today's economy, being smart is seen as
Speaker 1: the most important differentiating factor. But we're not talking about
Speaker 1: being an intellectual, like, we're talking about being cognitively enhanced
Speaker 1: by a computer or by technology. And Elon Musk isn't
Speaker 1: the only person who's noticed how important it is to
Speaker 1: be cognitively enhanced, shall we say? Last year, the World
Speaker 1: Bank announced the program called the Famine Action Mechanism to
Speaker 1: get relief to famine hit areas faster, and they explicitly
Speaker 1: said one of the reasons they're doing this is that
Speaker 1: because people who are malnourished in the womb may have
Speaker 1: cognitive issues later in life and thus be unable to
Speaker 1: compete in the new economy. You know, I found it
Speaker 1: really interesting that this program is actually powered by AI.
Speaker 1: It draws on data like social media, food prices, rainfall,
Speaker 1: and then automatically assigns funds so that money gets where
Speaker 1: it's needed before it's too late. It's a textbook case
Speaker 1: of what AI can do and we can't, which is
Speaker 1: to notice these patterns and correlations between different types of
Speaker 1: data sets which are so big as to be impossible
Speaker 1: for us to compute, and as so often in Sleepwalkers,
Speaker 1: and it's an example of technology being a double edged short.
Speaker 1: On the one hand, it may be widening the gap
Speaker 1: between rich and poor, but on the other hand, it
Speaker 1: can potentially feed the world. When we come back, we
Speaker 1: explore other ways AI and robotics can revolutionize food production.
Speaker 1: We've looked at how AI and robotics could exacerbate the
Speaker 1: gulf between rich and poor, and how this new industrial
Speaker 1: revolution could put a new value on human connection. But
Speaker 1: could we use automation to actually decrease global inequality? One
Speaker 1: key factor is access to quality nutrition and roboticist George
Speaker 1: Kantor gave a talk last year at south By Southwest
Speaker 1: called AI will help feed a growing planet. I wanted
Speaker 1: to learn more, so I called him for a conversation
Speaker 1: from his office at the Robotics Institute of Carnegie Mellon.
Speaker 1: A lot of people when they think about robots and
Speaker 1: technology being used to assist agriculture, think about robots driving
Speaker 1: around and picking grapes or plowing fields and things like that.
Speaker 1: But despite being a robotics expert, George is currently focusing
Speaker 1: on crop genetics. The way plant breeding works, you have
Speaker 1: a bunch of parents. Uh plant breeder very carefully uses
Speaker 1: all his or her experience to figure out which parents
Speaker 1: will make the best potential children. They make those crosses.
Speaker 1: They then do these field trials where they grow the
Speaker 1: child varieties and they measure them and see how they do,
Speaker 1: and then the winners go back in the pool and
Speaker 1: the losers they weed out. One of the crops we
Speaker 1: work with is sorghum. It's grown all over the world.
Speaker 1: They're like forty different varieties of it. In particular, the
Speaker 1: grain sorghum variety is a staple crop in places like
Speaker 1: Sub Saharan Africa and India, parts of the world where
Speaker 1: population is growing more rapidly than the rest of the
Speaker 1: planet's populations, and the predictions for the impact of global
Speaker 1: warming are are pretty high. Jewles uses technology to make
Speaker 1: the work if human plant breed is dramatically more efficient.
Speaker 1: But this work is completely invisible to consumers. So we
Speaker 1: have built a robot that goes out to a breeding
Speaker 1: experiment where a breeder has grown a thousand different varieties
Speaker 1: of sorghum are robot goes through and takes all these
Speaker 1: detailed measurements about how the plants are growing throughout the year,
Speaker 1: and then the breeder can use those measurements to make
Speaker 1: better decisions. The end user of this process I'm describing
Speaker 1: won't see any technology at all. They will get a
Speaker 1: seed that looks just like the seed they get now,
Speaker 1: except it will be a little bit better because the
Speaker 1: breeder improved it using our robots. These invisible changes to
Speaker 1: the food production system can have huge consequences. Better seeds
Speaker 1: mean better yields and could ultimately lead to a better
Speaker 1: nourish world. But George isn't only thinking about how to
Speaker 1: make heartier, better plants. He's also thinking about another problem,
Speaker 1: how will we efficiently feeded global population who increasingly live
Speaker 1: in cities and not on the farm. Imagine every building
Speaker 1: in a city had a little greenhouse hanging off the
Speaker 1: side of it, or a little growing room in the basement,
Speaker 1: and now you've got these indoor growing systems that tend
Speaker 1: to like generate more heat than they need, so one
Speaker 1: of their big problems is venting off the heat. Well,
Speaker 1: buildings have to pay a lot of money to heat
Speaker 1: the buildings. So if you had this sort of sim
Speaker 1: the artic relationship between the people in the building and
Speaker 1: the plants in the building, they can exchange heat, and
Speaker 1: they can exchange atmosphere and all kinds of things. If
Speaker 1: you take that idea and you scale it up to
Speaker 1: like a city scale, where now you have dozens or
Speaker 1: hundreds of buildings that all have these different energy needs
Speaker 1: and different agricultural needs, and they're all sort of sharing.
Speaker 1: You have some sort of overarching AI that controls what
Speaker 1: energy gets moved where. Um, you can imagine that there
Speaker 1: are big efficiencies that can be gained. George's outlining a
Speaker 1: vision where robotics and AI help us tackle one of
Speaker 1: the world's most enduring sources of inequality food access, and
Speaker 1: doing so could also make agriculture more energy efficient and
Speaker 1: thus begin to address another huge problem that will disproportionately
Speaker 1: affect the world's poorest people, climate change. So yes, automation
Speaker 1: will take jobs away, but it can also potentially raise
Speaker 1: quality of life and the quality of the global environment.
Speaker 1: And as far as George is concerned, the type of
Speaker 1: labor being replaced is not exact the work that maximizes
Speaker 1: human potential. We call them dull, dirty, dangerous, so jobs
Speaker 1: that people don't want or are dangerous to do, or
Speaker 1: people are getting injured in. When I go visit the
Speaker 1: Great industry in California and I see the laborers, they're
Speaker 1: out there, they're stooped over under trees, They're doing this
Speaker 1: extremely backbreaking labor. There are high incidences of repetitive stress injuries,
Speaker 1: and so it's just not a very pleasant environment to
Speaker 1: be working in. When automation comes into an industry, it
Speaker 1: takes away some jobs that were there, but it creates
Speaker 1: other opportunities. So for example, most orchards, you know, they'll
Speaker 1: have sort of a year round staff of maybe a
Speaker 1: dozen people, and then at certain busy times of the
Speaker 1: year they'll bring in maybe a hundred laborers to come
Speaker 1: in and help with the harvest. I think everybody would
Speaker 1: be better off if that orchard had a year round
Speaker 1: staff of twenty people that were productive all year long.
Speaker 1: And we're able to use technology to even out these
Speaker 1: bumps in the labor demand. And so those people, those
Speaker 1: twenty people are going to need to be higher skilled,
Speaker 1: but they're also going to get paid more, and they're
Speaker 1: also going to have more comfortable jobs, and overall they
Speaker 1: will produce more per person than they would in the
Speaker 1: other system. Of course, the lingering question is what happens
Speaker 1: to the eight people who no longer have a job,
Speaker 1: and who gets to enjoy the fruits of this more
Speaker 1: efficient system. Technology has improved lives all around the world
Speaker 1: and lifted millions out of poverty, but it is also
Speaker 1: dramatically enriched an extremely small number of people. We mentioned
Speaker 1: Elon Musk's neural link earlier, and he's not alone in
Speaker 1: the Silicon Valley elite investing in transhumanist technologies. That should
Speaker 1: give us pause, remembering what Ian Bremer said about cognitive differentiation.
Speaker 1: So there's much to fear, and there are no obvious
Speaker 1: solutions in sight, and yet people like Kai Fu Lee
Speaker 1: and Gil Pratt, people who are leading the field, remain optimistic.
Speaker 1: I wanted to know why there is a strong belief
Speaker 1: that thought leaders should do the best they can do
Speaker 1: to project a possible future and strive towards it and
Speaker 1: encourage other people to help make that a reality. Because
Speaker 1: whether we point at the future that is an utopia
Speaker 1: or dystopia, if everybody believes in it, then it becomes
Speaker 1: a self fulfilling prophecy. So I'd like to be part
Speaker 1: of that force which points towards more of utopian direction.
Speaker 1: Even though I fully understand and recognize the possibility and
Speaker 1: risks of the negative ending, we will want to believe
Speaker 1: in that utopian direction, honesting automation to help feed the
Speaker 1: world without stripping ourselves of community interaction, because man cannot
Speaker 1: live on bread alone, and we need to make sure
Speaker 1: to balance gains inefficiency with preserving the fabric of our society.
Speaker 1: In the next episode, we travel from the farm yard
Speaker 1: to the battlefield. We meet some of the people pioneering
Speaker 1: the use of AI and robotics to wage different kinds
Speaker 1: of wars, and we speak with Arti Pravaca, the former
Speaker 1: head of Darper, the agency that created the Internet, about
Speaker 1: how technology is revolutionizing the military. I'm oz veloshin see
Speaker 1: you next time. Sleepwalkers is a production of I Heart
Speaker 1: Radio and Unusual Productions for the latest AI news live
Speaker 1: interviews and behind the scenes footage. Find us on Instagram,
Speaker 1: at Sleepwalkers podcast or at Sleepwalker's podcast dot com. Sleepwalkers
Speaker 1: is hosted by me Oz Veloshin and co hosted by
Speaker 1: me Kara Price. We're produced by Julian Weller with help
Speaker 1: from Jacopo Penzo and Taylor Chikoin. Mixing by Tristan McNeil
Speaker 1: and Julian Weller. Our story editor is Matthew Riddle. Recording
Speaker 1: assistance this episode from Walter Kowski. Sleep Workers is executive
Speaker 1: produced by me Ozvaloshen and mangesh had Tigella. For more
Speaker 1: podcasts from my Heart Radio, visit the i heart Radio app,
Speaker 1: Apple Podcasts, or wherever you listen to your favorite shows.