Humans are teaching AI how to do their jobs | 60 Minutes

This past week in Washington, America's This past week in Washington, America's tech titans met with President Trump to tech titans met with President Trump to tech titans met with President Trump to talk about, well, the future of talk about, well, the future of talk about, well, the future of humanity. Specifically, will AI, humanity. Specifically, will AI, humanity. Specifically, will AI, artificial intelligence, mark the end of artificial intelligence, mark the end of artificial intelligence, mark the end of civilization as we know it. Only civilization as we know it. Only civilization as we know it. Only slightly less grave and only slightly slightly less grave and only slightly slightly less grave and only slightly less depressing, there's a related, more less depressing, there's a related, more less depressing, there's a related, more immediate question. Will AI take our immediate question. Will AI take our immediate question. Will AI take our jobs? jobs? jobs? That right there, not me. That was AI. That right there, not me. That was AI. That right there, not me. That was AI. So it is, we don't exempt ourselves in So it is, we don't exempt ourselves in So it is, we don't exempt ourselves in wondering, is any line of work safe? So wondering, is any line of work safe? So wondering, is any line of work safe? So far this year, US companies have cited far this year, US companies have cited far this year, US companies have cited AI as the number one reason for layoffs. AI as the number one reason for layoffs. AI as the number one reason for layoffs. AI, after all, doesn't sleep or take AI, after all, doesn't sleep or take AI, after all, doesn't sleep or take sick days. Is this technology simply sick days. Is this technology simply sick days. Is this technology simply going to transform how and where we going to transform how and where we going to transform how and where we work, much the same way other workplace work, much the same way other workplace work, much the same way other workplace revolutions did? Or is this one revolutions did? Or is this one revolutions did? Or is this one different? Is the great job apocalypse different? Is the great job apocalypse different? Is the great job apocalypse upon us? upon us? upon us? Here in this nondescript office in Here in this nondescript office in Here in this nondescript office in downtown San Francisco, downtown San Francisco, downtown San Francisco, [laughter] these 20somes are designing [laughter] these 20somes are designing [laughter] these 20somes are designing the future of your workplace. You may the future of your workplace. You may the future of your workplace. You may not have heard of Merkore, but it's not have heard of Merkore, but it's not have heard of Merkore, but it's quickly become a leader in a booming new quickly become a leader in a booming new quickly become a leader in a booming new industry built around supercharging the industry built around supercharging the industry built around supercharging the already supercharged rise of artificial already supercharged rise of artificial already supercharged rise of artificial intelligence.

intelligence. intelligence. >> We were in January last year about 20 >> We were in January last year about 20 >> We were in January last year about 20 people. people. people. >> How many now? >> How many now? >> How many now? >> And now it's 400 people in San >> And now it's 400 people in San >> And now it's 400 people in San Francisco. Yeah. Francisco. Yeah. Francisco. Yeah. Brendan Foody is Merkor's CEO. It's now Brendan Foody is Merkor's CEO. It's now Brendan Foody is Merkor's CEO. It's now a multi-billion dollar company and he's a multi-billion dollar company and he's a multi-billion dollar company and he's now a 23-year-old billionaire. now a 23-year-old billionaire. now a 23-year-old billionaire. >> Backtory. Four years ago, Chat GPT came >> Backtory. Four years ago, Chat GPT came >> Backtory. Four years ago, Chat GPT came out and Foody and his two co-founders, out and Foody and his two co-founders, out and Foody and his two co-founders, high school buddies, saw where the high school buddies, saw where the high school buddies, saw where the technology was heading. To get better, technology was heading. To get better, technology was heading. To get better, AI needed more information than what was AI needed more information than what was AI needed more information than what was widely available on the internet. AI widely available on the internet. AI widely available on the internet. AI went from this high-powered search went from this high-powered search went from this high-powered search engine to all of a sudden we're in engine to all of a sudden we're in engine to all of a sudden we're in astrophysics. We've gone from cutesy to astrophysics. We've gone from cutesy to astrophysics. We've gone from cutesy to holy moly in a very short amount of holy moly in a very short amount of holy moly in a very short amount of time. time. time. >> I think that's spot on. And the core >> I think that's spot on. And the core >> I think that's spot on. And the core thing powering that huge transformation thing powering that huge transformation thing powering that huge transformation in the capabilities is human in the capabilities is human in the capabilities is human intelligence. intelligence. intelligence. >> It seems like overarching goal. Anything >> It seems like overarching goal. Anything >> It seems like overarching goal. Anything we humans can do, we want AI to be able we humans can do, we want AI to be able we humans can do, we want AI to be able to do. to do. to do. >> I think a significant portion of things, >> I think a significant portion of things, >> I think a significant portion of things, everything that humans want AI to be everything that humans want AI to be everything that humans want AI to be able to do, uh, we want to teach it how able to do, uh, we want to teach it how able to do, uh, we want to teach it how to do that.

to do that. to do that. So what does Merore do? Well, when the So what does Merore do? Well, when the So what does Merore do? Well, when the big AI companies want, say, Chat, JPT or big AI companies want, say, Chat, JPT or big AI companies want, say, Chat, JPT or Claude to improve in a particular field, Claude to improve in a particular field, Claude to improve in a particular field, they hire Meror to make their models they hire Meror to make their models they hire Meror to make their models smarter. Pick a subject, any subject, smarter. Pick a subject, any subject, smarter. Pick a subject, any subject, finance, architecture, poetry. Meror has finance, architecture, poetry. Meror has finance, architecture, poetry. Meror has assembled an army of more than a 100,000 assembled an army of more than a 100,000 assembled an army of more than a 100,000 freelancers, humans, ready to use their freelancers, humans, ready to use their freelancers, humans, ready to use their hard-earned expertise to train the AI. hard-earned expertise to train the AI. hard-earned expertise to train the AI. >> I work late in the evening when >> I work late in the evening when >> I work late in the evening when >> we met three such experts. Shauna >> we met three such experts. Shauna >> we met three such experts. Shauna Miller, a wine maker. Robbie Heiser, a Miller, a wine maker. Robbie Heiser, a Miller, a wine maker. Robbie Heiser, a music producer, and Melania Punacha, a music producer, and Melania Punacha, a music producer, and Melania Punacha, a physician. physician. physician. >> When you're assigned a task, what are >> When you're assigned a task, what are >> When you're assigned a task, what are you actually doing? How are you training you actually doing? How are you training you actually doing? How are you training AI? AI? AI? >> On one project, we were training the AI >> On one project, we were training the AI >> On one project, we were training the AI to be able to accurately interpret to be able to accurately interpret to be able to accurately interpret laboratory results. laboratory results. laboratory results. >> For a songwriting project, you might get >> For a songwriting project, you might get >> For a songwriting project, you might get two different versions of the same two different versions of the same two different versions of the same lyric, and then you go through and give lyric, and then you go through and give lyric, and then you go through and give feedback on it. And feedback on it. And feedback on it. And >> all three have full-time jobs. AI >> all three have full-time jobs. AI >> all three have full-time jobs. AI training is just a side gig. Long-term, training is just a side gig. Long-term, training is just a side gig. Long-term, by spending hours teaching a computer by spending hours teaching a computer by spending hours teaching a computer the tricks of their trade, are they not the tricks of their trade, are they not the tricks of their trade, are they not training themselves out of a career? No, training themselves out of a career? No, training themselves out of a career? No, they insist. Heiser believes that great they insist. Heiser believes that great they insist. Heiser believes that great songwriting, for instance, will always songwriting, for instance, will always songwriting, for instance, will always require the human touch.

require the human touch. require the human touch. >> AI doesn't have any life experience to >> AI doesn't have any life experience to >> AI doesn't have any life experience to pull from. You know, the an AI never had pull from. You know, the an AI never had pull from. You know, the an AI never had a girlfriend break up with it. a girlfriend break up with it. a girlfriend break up with it. >> Real life inputs that impact songwriting >> Real life inputs that impact songwriting >> Real life inputs that impact songwriting in a way that in a way that in a way that >> absolutely >> absolutely >> absolutely >> robots. Yeah. There's no way to write >> robots. Yeah. There's no way to write >> robots. Yeah. There's no way to write that in. that in. that in. >> I don't think so. >> I don't think so. >> I don't think so. >> Ultimately, Brendan Foody foresees a >> Ultimately, Brendan Foody foresees a >> Ultimately, Brendan Foody foresees a utopia. Advanced AI helping us cure utopia. Advanced AI helping us cure utopia. Advanced AI helping us cure cancer and tackle climate change and the cancer and tackle climate change and the cancer and tackle climate change and the untold millions of workers liberated untold millions of workers liberated untold millions of workers liberated from the dullst parts of their jobs. from the dullst parts of their jobs. from the dullst parts of their jobs. They'll be more productive than ever. They'll be more productive than ever. They'll be more productive than ever. >> People still have this fundamental >> People still have this fundamental >> People still have this fundamental question, is my job safe from AI? How do question, is my job safe from AI? How do question, is my job safe from AI? How do you answer that? I think the key thing you answer that? I think the key thing you answer that? I think the key thing to look at is if you become more to look at is if you become more to look at is if you become more productive, is there more demand for productive, is there more demand for productive, is there more demand for your expertise in the economy? your expertise in the economy? your expertise in the economy? >> If you're training AI to do what people >> If you're training AI to do what people >> If you're training AI to do what people have spent years and years perfecting in have spent years and years perfecting in have spent years and years perfecting in their careers, aren't aren't you their careers, aren't aren't you their careers, aren't aren't you necessarily endangering human work? necessarily endangering human work? necessarily endangering human work? >> Well, I think that you're changing human >> Well, I think that you're changing human >> Well, I think that you're changing human work. It might not necessarily be that work. It might not necessarily be that work. It might not necessarily be that repetitive task that people have done in repetitive task that people have done in repetitive task that people have done in the past, but there's still so many the past, but there's still so many the past, but there's still so many other things that people could be able other things that people could be able other things that people could be able to do. And so I think that evolution is to do. And so I think that evolution is to do. And so I think that evolution is natural. It's something natural. It's something natural. It's something >> whether workers asked for it or not, >> whether workers asked for it or not, >> whether workers asked for it or not, that evolution is already happening and that evolution is already happening and that evolution is already happening and not just in the tech hotbands in places not just in the tech hotbands in places not just in the tech hotbands in places like Columbus, Ohio where the law firm like Columbus, Ohio where the law firm like Columbus, Ohio where the law firm Vory Seder Seymour and Peas has been Vory Seder Seymour and Peas has been Vory Seder Seymour and Peas has been serving clients needs since 1909.

serving clients needs since 1909. serving clients needs since 1909. Kim Hurley, a trial lawyer, is a partner Kim Hurley, a trial lawyer, is a partner Kim Hurley, a trial lawyer, is a partner at the firm. at the firm. at the firm. >> You're going into courtrooms and facing >> You're going into courtrooms and facing >> You're going into courtrooms and facing a judge and jury. How is AI going to a judge and jury. How is AI going to a judge and jury. How is AI going to help with that? help with that? help with that? >> AI is never going to walk into the >> AI is never going to walk into the >> AI is never going to walk into the courtroom and give an opening statement courtroom and give an opening statement courtroom and give an opening statement to the jury, but it helps us have to the jury, but it helps us have to the jury, but it helps us have additional tools to use as we prepare additional tools to use as we prepare additional tools to use as we prepare that opening statement. What about this? that opening statement. What about this? that opening statement. What about this? >> A year ago, Vores worked with Stanford >> A year ago, Vores worked with Stanford >> A year ago, Vores worked with Stanford University to build an internal tool for University to build an internal tool for University to build an internal tool for the firm. individual AI personas trained the firm. individual AI personas trained the firm. individual AI personas trained on its senior lawyers. How do they on its senior lawyers. How do they on its senior lawyers. How do they think? What kind of advice do they give think? What kind of advice do they give think? What kind of advice do they give presto an AI version of Avor's partner? presto an AI version of Avor's partner? presto an AI version of Avor's partner? Hurley has her own which she consulted Hurley has her own which she consulted Hurley has her own which she consulted for us. for us. for us. >> So what you have on your screen here is >> So what you have on your screen here is >> So what you have on your screen here is a draft opening statement. a draft opening statement. a draft opening statement. >> This is uh ladies and gentlemen of the >> This is uh ladies and gentlemen of the >> This is uh ladies and gentlemen of the jury. jury. jury. >> Now Hurley asks her AI double to give >> Now Hurley asks her AI double to give >> Now Hurley asks her AI double to give notes. You can see it's an AI comment notes. You can see it's an AI comment notes. You can see it's an AI comment from my persona is saying the legal from my persona is saying the legal from my persona is saying the legal phrasing is too stiff for an opening phrasing is too stiff for an opening phrasing is too stiff for an opening statement. statement. statement. >> I'm just struck that people who aren't >> I'm just struck that people who aren't >> I'm just struck that people who aren't familiar with AI, they might think, you familiar with AI, they might think, you familiar with AI, they might think, you know, it's robots and avatars. It's just know, it's robots and avatars. It's just know, it's robots and avatars. It's just a word doc.

a word doc. a word doc. >> Yeah, it is. You're not seeing a picture >> Yeah, it is. You're not seeing a picture >> Yeah, it is. You're not seeing a picture of me. I'm not talking out loud. of me. I'm not talking out loud. of me. I'm not talking out loud. >> Not yet, anyway. Still, we wondered, is >> Not yet, anyway. Still, we wondered, is >> Not yet, anyway. Still, we wondered, is today's worker optimizer not tomorrow's today's worker optimizer not tomorrow's today's worker optimizer not tomorrow's worker replacement? So, we've built this worker replacement? So, we've built this worker replacement? So, we've built this model with partner Kim Hurley's model with partner Kim Hurley's model with partner Kim Hurley's expertise baked into it. It's not hard expertise baked into it. It's not hard expertise baked into it. It's not hard to see a future in which the client just to see a future in which the client just to see a future in which the client just goes right to the model, is it? goes right to the model, is it? goes right to the model, is it? >> That's hard for me to see. AI cannot >> That's hard for me to see. AI cannot >> That's hard for me to see. AI cannot take the place of what's a fundamentally take the place of what's a fundamentally take the place of what's a fundamentally human business. You call your lawyer human business. You call your lawyer human business. You call your lawyer because you want to look in their eye because you want to look in their eye because you want to look in their eye and say, "What should I do about this and say, "What should I do about this and say, "What should I do about this issue?" issue?" issue?" >> This sunny picture, it's at odds with >> This sunny picture, it's at odds with >> This sunny picture, it's at odds with the bleak labor predictions many AI the bleak labor predictions many AI the bleak labor predictions many AI executives have been issuing. But we may executives have been issuing. But we may executives have been issuing. But we may indeed have a have a serious employment indeed have a have a serious employment indeed have a have a serious employment crisis on our hands. crisis on our hands. crisis on our hands. >> It's early and overall unemployment >> It's early and overall unemployment >> It's early and overall unemployment remains generally steady. But mounting remains generally steady. But mounting remains generally steady. But mounting research shows that for the most AI research shows that for the most AI research shows that for the most AI exposed jobs, take software developers, exposed jobs, take software developers, exposed jobs, take software developers, hiring has slowed and wages have hiring has slowed and wages have hiring has slowed and wages have declined. The impact focused on one declined. The impact focused on one declined. The impact focused on one group in particular, 20somes.

group in particular, 20somes. group in particular, 20somes. Traditionally, the tasks that you might Traditionally, the tasks that you might Traditionally, the tasks that you might assign to a young person, maybe doing assign to a young person, maybe doing assign to a young person, maybe doing some market research or creating the some market research or creating the some market research or creating the first draft of a memo, AI is just really first draft of a memo, AI is just really first draft of a memo, AI is just really good at doing those now. good at doing those now. good at doing those now. >> Until January, Clara Shai was overseeing >> Until January, Clara Shai was overseeing >> Until January, Clara Shai was overseeing major AI divisions at Salesforce and major AI divisions at Salesforce and major AI divisions at Salesforce and then Meta. then Meta. then Meta. >> And you've seen how powerful this can >> And you've seen how powerful this can >> And you've seen how powerful this can be. be. be. >> Oh, yeah. I've I've seen us go from >> Oh, yeah. I've I've seen us go from >> Oh, yeah. I've I've seen us go from previously requiring dozens of people to previously requiring dozens of people to previously requiring dozens of people to conceive of a product, prototype it, conceive of a product, prototype it, conceive of a product, prototype it, build it, to now being able to do that build it, to now being able to do that build it, to now being able to do that with with one or two or three people with with one or two or three people with with one or two or three people using AI agents. using AI agents. using AI agents. >> Shai was so alarmed by what this meant >> Shai was so alarmed by what this meant >> Shai was so alarmed by what this meant for the workforce, she quit her plum for the workforce, she quit her plum for the workforce, she quit her plum tech job and founded a nonprofit helping tech job and founded a nonprofit helping tech job and founded a nonprofit helping young people navigate this new economy. young people navigate this new economy. young people navigate this new economy. And she has emerged as an AI Cassandra. And she has emerged as an AI Cassandra. And she has emerged as an AI Cassandra. I think AI is going to have a profound I think AI is going to have a profound I think AI is going to have a profound impact on on every profession. There are impact on on every profession. There are impact on on every profession. There are a lot of people whose jobs it is today a lot of people whose jobs it is today a lot of people whose jobs it is today within companies to prepare information, within companies to prepare information, within companies to prepare information, research, analyze data for other research, analyze data for other research, analyze data for other individuals in that company. And individuals in that company. And individuals in that company. And increasingly, although it's starting increasingly, although it's starting increasingly, although it's starting with the entry level, it could result in with the entry level, it could result in with the entry level, it could result in a lot of people losing their their jobs.

a lot of people losing their their jobs. a lot of people losing their their jobs. >> And job loss means what? As you see it, >> And job loss means what? As you see it, >> And job loss means what? As you see it, >> it's never just about the jobs. It's >> it's never just about the jobs. It's >> it's never just about the jobs. It's people's sense of of self-worth. It's people's sense of of self-worth. It's people's sense of of self-worth. It's the fracturing of communities. It's the fracturing of communities. It's the fracturing of communities. It's >> Shai knows this cycle firsthand. Her >> Shai knows this cycle firsthand. Her >> Shai knows this cycle firsthand. Her family came to the US from Hong Kong in family came to the US from Hong Kong in family came to the US from Hong Kong in the 1980s and landed in Ohio, where the 1980s and landed in Ohio, where the 1980s and landed in Ohio, where globalization was hollowing out globalization was hollowing out globalization was hollowing out factories, then neighborhoods. She sees factories, then neighborhoods. She sees factories, then neighborhoods. She sees clear parallels. clear parallels. clear parallels. >> I think what we can learn is that first >> I think what we can learn is that first >> I think what we can learn is that first we have to be honest with people about we have to be honest with people about we have to be honest with people about what the risks are. I think, you know, what the risks are. I think, you know, what the risks are. I think, you know, sugar coating that this this AI utopia, sugar coating that this this AI utopia, sugar coating that this this AI utopia, maybe we'll get there, but there's a lot maybe we'll get there, but there's a lot maybe we'll get there, but there's a lot of hurt that could happen between now of hurt that could happen between now of hurt that could happen between now and there. And that's and there. And that's and there. And that's >> the public is beginning to revolt. >> the public is beginning to revolt. >> the public is beginning to revolt. Nearly three4s of Americans now fear AI Nearly three4s of Americans now fear AI Nearly three4s of Americans now fear AI is coming for our jobs. And amid this is coming for our jobs. And amid this is coming for our jobs. And amid this growing backlash, the big tech firms growing backlash, the big tech firms growing backlash, the big tech firms have been massaging their message. have been massaging their message. have been massaging their message. Here's OpenAI's Sam Alman in June. But I Here's OpenAI's Sam Alman in June. But I Here's OpenAI's Sam Alman in June. But I think our industry underestimated how think our industry underestimated how think our industry underestimated how much much much we're going to be able to keep people at we're going to be able to keep people at we're going to be able to keep people at the center of everything in an economy the center of everything in an economy the center of everything in an economy that is in a world that is based on that is in a world that is based on that is in a world that is based on people.

people. people. >> For a time, the AI companies were >> For a time, the AI companies were >> For a time, the AI companies were trumpeting that this product is going to trumpeting that this product is going to trumpeting that this product is going to make work obsolete and now there seems make work obsolete and now there seems make work obsolete and now there seems to be a pivot and a change of tune. What to be a pivot and a change of tune. What to be a pivot and a change of tune. What do you make of this shift? do you make of this shift? do you make of this shift? >> I think that they have the AI labs have >> I think that they have the AI labs have >> I think that they have the AI labs have every incentive to to sell what they're every incentive to to sell what they're every incentive to to sell what they're doing to the public now. And I don't doing to the public now. And I don't doing to the public now. And I don't think that they they actually believe think that they they actually believe think that they they actually believe that AI won't won't hurt jobs. that AI won't won't hurt jobs. that AI won't won't hurt jobs. >> Back at Meror, typical trainers can be >> Back at Meror, typical trainers can be >> Back at Meror, typical trainers can be paid anywhere from $ 20 to $200 an hour. paid anywhere from $ 20 to $200 an hour. paid anywhere from $ 20 to $200 an hour. Not bad. Not bad. Not bad. >> We spoke with more than a dozen Merur >> We spoke with more than a dozen Merur >> We spoke with more than a dozen Merur trainers, past and current. Some were trainers, past and current. Some were trainers, past and current. Some were happy. Many more said that the gig work happy. Many more said that the gig work happy. Many more said that the gig work comes unpredictably or not at all. No comes unpredictably or not at all. No comes unpredictably or not at all. No substitute for a full-time job with substitute for a full-time job with substitute for a full-time job with benefits. I mean, sometimes you have benefits. I mean, sometimes you have benefits. I mean, sometimes you have experts that are twice and three times experts that are twice and three times experts that are twice and three times their age and they've spent a lot of their age and they've spent a lot of their age and they've spent a lot of time in their field and one thing time in their field and one thing time in their field and one thing they've gotten is a level of they've gotten is a level of they've gotten is a level of predictability and stability in their predictability and stability in their predictability and stability in their job and then it seems like the the hours job and then it seems like the the hours job and then it seems like the the hours are much more erratic here. are much more erratic here. are much more erratic here. >> Yeah, the hours are more erratic, but >> Yeah, the hours are more erratic, but >> Yeah, the hours are more erratic, but it's also something that we're very it's also something that we're very it's also something that we're very transparent with them about. transparent with them about. transparent with them about. >> I mean, it does not sound like stable >> I mean, it does not sound like stable >> I mean, it does not sound like stable work work work >> right now. It generally is more >> right now. It generally is more >> right now. It generally is more part-time work is what experts sign up part-time work is what experts sign up part-time work is what experts sign up for. But for the high performing for. But for the high performing for. But for the high performing experts, we always make sure that they experts, we always make sure that they experts, we always make sure that they have work available.

have work available. have work available. >> Today, AI training is America's fourth >> Today, AI training is America's fourth >> Today, AI training is America's fourth fastest growing job category on fastest growing job category on fastest growing job category on LinkedIn. And just as machinists once LinkedIn. And just as machinists once LinkedIn. And just as machinists once replaced artisans, Brendan Foody insists replaced artisans, Brendan Foody insists replaced artisans, Brendan Foody insists he's creating a career of the future. he's creating a career of the future. he's creating a career of the future. Out of work, fear not. Come train AI. Out of work, fear not. Come train AI. Out of work, fear not. Come train AI. Literally all of the top 20 economists Literally all of the top 20 economists Literally all of the top 20 economists in America, they would say the exact in America, they would say the exact in America, they would say the exact same thing, which is that there's going same thing, which is that there's going same thing, which is that there's going to be more jobs in 10 years than there to be more jobs in 10 years than there to be more jobs in 10 years than there are today. are today. are today. >> You're a top economist in America. What >> You're a top economist in America. What >> You're a top economist in America. What say you? say you? say you? >> No. >> No. >> No. >> No, not on our current trajectory. I >> No, not on our current trajectory. I >> No, not on our current trajectory. I don't saw how that could happen. What we don't saw how that could happen. What we don't saw how that could happen. What we are living through with AI is are living through with AI is are living through with AI is unprecedented. The first phase of the unprecedented. The first phase of the unprecedented. The first phase of the industrial revolution lasted for 80 industrial revolution lasted for 80 industrial revolution lasted for 80 years. Today it's taking place in one or years. Today it's taking place in one or years. Today it's taking place in one or two years and it's taking place across two years and it's taking place across two years and it's taking place across many sectors at the same time. many sectors at the same time. many sectors at the same time. >> Duramoglu is a Nobel Prize winning >> Duramoglu is a Nobel Prize winning >> Duramoglu is a Nobel Prize winning professor at MIT who studies professor at MIT who studies professor at MIT who studies technologies impact on labor. technologies impact on labor. technologies impact on labor. >> We were told by a lawyer and also a >> We were told by a lawyer and also a >> We were told by a lawyer and also a music producer. There are some things music producer. There are some things music producer. There are some things that humans are so fundamental. Humans that humans are so fundamental. Humans that humans are so fundamental. Humans do them, robots can't. Do you buy that?

do them, robots can't. Do you buy that? do them, robots can't. Do you buy that? >> Today absolutely 100%. >> Today absolutely 100%. >> Today absolutely 100%. >> You said today. today in 15 years time >> You said today. today in 15 years time >> You said today. today in 15 years time what it's going to be capable of doing I what it's going to be capable of doing I what it's going to be capable of doing I don't know don't know don't know >> but there's going to be this huge sector >> but there's going to be this huge sector >> but there's going to be this huge sector of work training these AI models so if of work training these AI models so if of work training these AI models so if you're a law student you have a hard you're a law student you have a hard you're a law student you have a hard time finding a job you can still use time finding a job you can still use time finding a job you can still use your expertise your expertise your expertise >> here is one thing I'm not uncertain >> here is one thing I'm not uncertain >> here is one thing I'm not uncertain about what you just described as BS about what you just described as BS about what you just described as BS [laughter] [laughter] [laughter] >> why do you say that >> why do you say that >> why do you say that >> because the number of people they're >> because the number of people they're >> because the number of people they're employing employing employing in these positions is small relative to in these positions is small relative to in these positions is small relative to the number of people who will be the number of people who will be the number of people who will be replaced placed. I mean, that's the replaced placed. I mean, that's the replaced placed. I mean, that's the whole point of automation. whole point of automation. whole point of automation. >> Asamoglu says we could see unemployment >> Asamoglu says we could see unemployment >> Asamoglu says we could see unemployment triple in the next decade if we do triple in the next decade if we do triple in the next decade if we do nothing and continue on our current nothing and continue on our current nothing and continue on our current course. course. course. >> I am very very very cautious in saying >> I am very very very cautious in saying >> I am very very very cautious in saying we should say no to technology. we should say no to technology. we should say no to technology. Absolutely not. But in every Absolutely not. But in every Absolutely not. But in every technological revolution there is push technological revolution there is push technological revolution there is push back and that push back takes many back and that push back takes many back and that push back takes many different forms. He comes with different forms. He comes with different forms. He comes with suggestions. Designing AI that makes suggestions. Designing AI that makes suggestions. Designing AI that makes humans better, not expendable. A tax humans better, not expendable. A tax humans better, not expendable. A tax code that incentivizes hiring real code that incentivizes hiring real code that incentivizes hiring real people. But the window is closing. And people. But the window is closing. And people. But the window is closing. And Aimoglu fears for the stability of Aimoglu fears for the stability of Aimoglu fears for the stability of society itself.

society itself. society itself. >> That shouldn't scare the hell out of us. >> That shouldn't scare the hell out of us. >> That shouldn't scare the hell out of us. It should. And it should move us into It should. And it should move us into It should. And it should move us into thinking about what we can do because thinking about what we can do because thinking about what we can do because there is a lot we can do because the there is a lot we can do because the there is a lot we can do because the future is so uncertain. Because the future is so uncertain. Because the future is so uncertain. Because the future is so much subject to our choice future is so much subject to our choice future is so much subject to our choice and agency, it is all the more important and agency, it is all the more important and agency, it is all the more important that we have this discussion.