« The Jordan Harbinger Show

567: Kai-Fu Lee | Ten Visions for Our Future with AI

2021-09-30 | 🔗

Kai-Fu Lee (@kaifulee) is an AI expert, CEO of Sinovation Ventures, former President of Google China, and co-author (with Chen Qiufan) of AI 2041: Ten Visions for Our Future.

What We Discuss with Kai-Fu Lee:
  • How AI will magnify the effects of the energy revolution, materials revolution, and life science revolution currently under way.
  • How can we keep the data that trains AI to operate free from human and cultural biases and other inaccuracies?
  • The four waves of AI and where we are on the path to truly autonomous AI that frees humans to do more worthwhile work.
  • How human beings can avoid displacement when all the repetitive, soul-crushing tasks are being done by robots, and what society must do to keep this from widening the gap in economic inequality.
  • How AI might be used to optimize the educational experience and make it engaging for every child by tailoring it to their individual interests.
  • And much more...

Full show notes and resources can be found here: jordanharbinger.com/567

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This is an unofficial transcript meant for reference. Accuracy is not guaranteed.
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the battery level have anything to do with the credit. Does the person's address haven't you know where the credit turns out. Most of them are actually relevant when you think about it. Welcome to the show, I'm Jordan Harbinger on the Jordan Harbinger show we decode the stories, secrets and skills of the world's most fascinating people. We have in depth conversations with people at the top of their game, astronauts and entrepreneurs, spies and psychologists, even the occasional national security Adviser WAR, correspondent or underworld figure. Each episode turns our guests wisdom into practical advice that you can use to build a deeper understanding of how the world works and become a better critical thinking if your new to the show or you're looking for a handy way to tell your friends about if we now have episode starter packs, these are collections of your favorite episodes organised by popular topics. It'll help new listeners get a taste of everything that we do here on the shelf. His visit, George
harbinger, dotcom, Slash, starts to get started or tell somebody else. Get started, crochet always appreciate it. When you do that today on the shell there's a lot of talk about a I art official intelligence, these days from whether it'll take all of our jobs and leave us alone imploid or whether it old birder all of us in some particularly brutal fashion, while watching experts in science fiction authors debate this endlessly online. I came across this plot. Viking filled the former president of Google China, discussing the rise of HIV in China in the United States, the future of a life, what it means for I in the rest of the world will learn how close or how far we are from the different types of artificial intelligence. How I will
to change the world and our position, and it will also discover why I is as important as the industrial revolution or as electricity itself and yet will happen a lot faster and what this means for us as mere humans. This is sort of enough to die for his previous appearance here on the show relate to them, show notes as well and if you're wondering how I managed to both of these great authors, thinkers and creators every single week, it's because of my network and on teaching you how to build your network for free over at Jordan Harbinger of outcome, slash course peddling most the guests on the show they subscribe to the course and contribute to the course come join you'll, be in smart company where you belong Here's Kai fully! previously on the show. I had Kevin Kelly. That's episode, five thirty seven and he had said something along the lines of the a revolution will be on the scale of the industrial revolution, but it'll be larger, It'll happen faster. It's basically the best thing since electricity, but even more impact full on our society
you agree with then? Yes, I would that, coincidentally, were seeing actually multiple revolutions where scene? the revolution. What's the matter else revolution wasting life science revolution. So when you follow, together. This will actually be all the more magnify when you say that we're gonna and we'll get into this later in the show, but when you say we're seeing things like life sciences, revolutions, I assume what you mean is a I stacked on top of each of these industries. he's going to game changer, for example, with life sciences. I can't come open, the human genome and a textbook and go aha theirs. Thing that I can use. But a I can look at that genome and say you know four people that have this this drug might cure this thing that these people are always dealing with, and that might not happen century of human experimentation, exactly watching attic. Sequencing is almost one gigabytes of data researchers, don't know how to read most of it and thought
certainly don't know how to read it. It's really up to ai to figure out. How do we create precision medicine based on each person's individual characteristics in the genetic sequencing may be? A different kind of treatment is needed. So just like a I can show you a different Facebook newsfeed and it shows me a I can give you a different treatment and it gives me and those being much more effective. So it's a perfect combination that everything's going digital in a lot of these industries are for bill researchers, putting things in a pile on saying, hey? I can't deal what this right now I'll handle it later. Their lot of professionals, kind of saying, like this problem too big for me to tackle, but maybe in the future, will have the computing technology or is it simply going to be almost like invisible layer on top of everything that we do now and I'll take care of sequencing, for example, you're saying there's no way. I can read the GB of data for every human breast, so we're just going to figure out what the one percent that we can read the other ninety nine percent. I will. Maybe it contains
information, but maybe it doesn't so. Yes, I, like you said, they are deferring is, and I think now we figure out how to get permission by people to collect this data, because genetic sequencing is extremely sensitive, personal information and you can anonymize it so wise. We figure out how to get some people to donate their information than I can really partly on that. What do you mean it? You can anonymize it because it's a genome and it's very unique to you- there's no way to make it so that I can't figure out in your area that makes sense you like, with a hospital record. You can remove your name, written move, your zip code, remove your phone number address more or less people can't figure out and reverse engineer issue, but with genetic secrecy by definition, it is just you so that there's a privacy concern there, because at some point the cats gonna be out of whether I guess
this information through some channel that we really dont want Daban or, for example, if there's just a company or an insurance company, that decides to be a little bit less than ethical. With it or a nation state that says our citizens don't get privacy, we don't allow that we could. up with a bunch of Eric Data. That is obviously super traceable. It's like a fingerprint, except you can never get rid of the finger right. Is you forever your Georgina yeah, there could be less say, important political figure. Sat genetic secrecy got known, then that person's mutation and England sure to get in the Alzheimer's or whatever disease, and that get spread is terrible for the person and the country. So as forest Lucian, I think there are many solutions for managing the heck sequencing proverbs right in terms of protecting
our cake and either to that's the goal that we protect. Our privacy and personal information, still the eyes able to train for most kinds of data. There's ideas like privacy, computing, federated learning, good work. There is anonymisation that good work, but on the genetic sequencing I think we have to be extremely careful. I think possibly privacy computing could still work the idea of February. The learning is a technology that keeps your data only in computers that you and trust and never beyond. So let's say you do your genes equalising indeed Mass General Hospital, you obviously entrust mass general. So now, if we want the train- and I thus precision medicine for particular illness- and your data could be included in it by doing the training and mass general. And all the other hospitals. And then I would aggravate the models from the hospitals, but never your personal data, so that kind of a privacy computing together.
What could potentially one they allow us to have a cake and eat it. The while Just for me, as somebody who looks at things that adverse was to be secure and be like. No, that's really scary, because at the idea of a hospital that's operating on whatever budget and has like two, I t security guys or will or zero, and there, like. Don't worry, we're gonna, keep tens of thousands slash. Hundreds of thousands of people genomes totally secure from bad actors, because we put like a password on the five inches like there are so many things that can go wrong with that. But I realized that's what happens Ray technology right online banking. Now I get hackers, steel and money. It's kind of just the way it is it's just a little we'll scarier, when it here's the exact thing that can kill these species. People are here. Is that but you're allergic to, or here's the disease that this person is going to get yeah. That's that become so much more personal literally in every way. Now we need to boost security everywhere. I mean people might think Hale if I'd
stored my genetic sequencing on my phone, then I feel safe, but actually that's the easiest thing hack into sure right even worse, that hospital Yeah I mean I don't. I would definitely not trust my phone with anything that that important you don't even my credit card numbers where I have to put them liable for, like fifty bucks worth of fraud or zero dollars worth of fraud. Even then, I'm like I don't know if I want that on my phone banking, that is one percent is scary- is having my genome online. With a we talk before about the key bottleneck in developing a. I is the amount of data right in China. The United States penny your superpower has a huge amount of data coming in and in the air I twenty forty one. You mentioned that
Some of the ai, the new stuff is programmed by M paraphrasing here ingesting five hundred million pages of information, and things like that is that just like the whole internet where's that information from what is that is Google books yeah for most applications. You actually want data that is closed. Loop irrelevant to your business, ok so Facebook data would be no good to a hospital and vice versa. So by a large you wanted, find what have you been. Iran collected data relevant to that and you can collect the data and use the optimum isometric symmetric, faster, normal application. Now there a new technology that is coming out, some color foundation model, others call it a pre training. Generic pre training, followed by fine to me and what that means is suppose we don't have any relevant date our very little relevant data. Can we take the whole day
from the whole world and train a general model that consumes and injustice. Everything, and then, when you have a particular domain, then that can be fine tuned for the domain. So many of your audience may have read about gpt. Three some of the new Google lambda and birds and transformer those are in that class, and it's pretty amazing that a gigantic now were trained. I everything in the world and to ask your question: yes, it is every text we can find anywhere it can. Basically has seen everything. Then, when you ask it to do something like a right,
Limerick, about Islam, ask any doctors do style. It can do that because it actually has a little concept: grouping of doktor zoos and Limerick and Yellow Mosque, so that ability is something that five years ago I did not think would work as well as it does in fact has no human programmed concept of what you alarmist, or limerick or doktor shoes, and it's totally self organizing with no supervision. And then we have that data when you want to fine tune it to do something specifically, whether it's too in a right palms or generate music, for answer, questions about technology or pretend you're talking like Albert Einstein, it can do that with mistakes, but I think the level of fidelity and qualities amazing that having the mistakes will be reduced overtime, and this can be too many new
the commission's. So if we have in by the way for people who don't know Jpg three transformer some of these things, these are what would we even call them there? I dare not botz. That's too simple. What are we call them? What are we call these systems sounds to generic to me, it's like this is the entity. This is the robot red is a large dinner. Merrick model trained on everything known to mankind, so it's kind of like, When we were very young, just learning cost. the language you know, maybe before on elementary school now we re that watch tv and listen to people and our brains form a certain connections, neuron firing that allow, us to gain a general understanding of language, then, based on that knowledge, when you take a class in arithmetic or chemistry or United States hit,
you, can draw upon your general knowledge and then learn something new, so that is very much akin to this foundation model, which is one name to college, which includes a generic. Retraining. That's like learning everything about the language and a fine tuning, that's like I'm, making it work for specific Donny and this is different than what we have today. Typically in our computer right, which is like a rules based system in an early I, which has an expert system, this neural network, it's not when there's input, you gotta, do this and then there's that output. This is a neural network that has a different approach to problem solving right, so the less human interference with what the eyes doing the better. The outcome verses, a computer, like mine, that I'm using now we're somebody had to tell it pretty much exactly what to do with everything. I'm putting in right now, exactly is very counter enjoyed if people would think that way?
Everything that we humans. Now we should programme every detail right. It turns out that are, for our rules are very simple, very brutal. The rules whereby we make decisions are very brutal. The reason I can beat us in so many tasks from game playing to reading radiology, to diagnosing sickness and is because a eyes able to consume so much data from so many permutations and draw its own mathematical conclusion. So when a makes a decision or makes a prediction. It is doing so on a thousand dimensional space and finding a particular way to divide up the yes and knows that humans can never do that and can never comprehend that now humans still have to do a little bit of programming. One is tell the network what the goal is right rooms or Facebook with towel then that new network get people to click more people to read more at Amazon, with click show them good products that their likely
by Jan maximize my revenue, so each company could programme the eye in that sense that an objective function is a goal that we want to accomplish and often have. I learned to optimize and, of course the human has to create the architecture of the network, how large it is, how it's connected, what sequencing where the train them with the law of a lack of black magic yeah. It's not programming in the rule says but other human man is still now nine zero, but it's not as substantial. I certainly not as detail oriented as people's our intuitions might be. I think anybody who has gone on Youtube to watch one thing and then has like shook themselves off three hours later and realize they ve done they were the video unlike world war to another, watching something different
full, let's leave it there like they invest negatively, know what a I ask you. Why did I watch five additional or twenty five additional videos? It's because the ay I was like this guy likes these kinds of things. Let's do that, but one end to the left and then they just keep doing Ba. I just keep doing that until I wake up and I realize I haven't, eaten or showered and might my days ruin with a sigh won't, I'm also be programmed with bias and, alas, of common sense if we're training it on bulk information from a wide sweep of society. That lets say represents the population at large right we were ingesting twitter or ingesting Facebook. Weren't, thing all the blogs of the world. Do we maybe you want to feed the eye everything cause, there's some ridiculously dumb bad thinking on ethical stuff in horrific things that we see on social media, let alone everywhere else. Do we want That away from me I or is it our way for us to say hey by the way this is low. Quality information is a double edged. Sword,
had we definitely want to filter out some things due to quality due to Miss fits and also due to misrepresentation. If you feed it content all from men, then they were completely miss the women angle right because the whole mission, or because of a racial, so I think balance is important. Quality quality is somewhat important because, when humans tried to play God with a is, are you shouldn't miss that this information should be given then you're removing data and less data makes less powerful a system. So generally want to balance the need to who are we know, is bad with the desire to have more data, so that has meant a train out. So you want to give a the ability to make us on this. as an example. So let's say we want to train a system that determines, if someone has good credit or not
suppose hypothetically we have everything other far less it. We have likeness to the ability to feed that in you would think alike, things are irrelevant. Does what actually use haven't you do their credit does battery level. Have anything to do with the credit. Does the person's address have anything to do with a credit? turns out. Most of them are actually relevant when you think about these battery level. A real example, because my theory would be that people whose battery levels critically law the time or does it irresponsible and have grabbed credit, is our correlation. There is a correlation, but not the way you stay there, there's probably a fifty one percent correlation. So it's slightly better than useless and you could use it and I would be smart now. Ok, battery level has a tiny bit of correlation, saw, consider with everything else being equal. So actually you can throw more garbage added it we'll figure out. What's irrelevant. highly relevant and rank them. Wait them accordingly. So I wouldn't throughout all the data just because I humanly
It is not useful right, but you might want to drought day that that you think he's really contain Anything is really negative sentiment, This is interesting, as is kind of like raising a teenager right, so you're like ok. I know I have to tell you about people that think that other races, our bad, that the Holocaust didn't happen, but those people are eighty. It you're going to see a lot of it, but I want you to just let it wash over you and forget it immediately. Dont forget it forget it, but don't pay any attention to it. Any more than you need do, because it's a bunch of crap right, like we're gonna, have to show a I that so it's kind of like grazing kid network You want some supervision that not too much right but also like we always have to teach a I some sort of common to say common sense, requisite doesn't really fit, but we have to teach it almost almost ethics, but also how the way things, like maybe posts on social media that are spelled horribly, that are by people who, post hateful staff are just wade near nothing. That seems like a very tricky.
two programme. Do we let the a decide what has weighed or do we program that in at least or we programme the outcome right so in a way oh, that beginner, that companies, their alchemists, make more money, get ribaldry out and that's what's causing the problem. So in the book at twenty forty one talk about scenarios where companies have aligned interests with a user imagined. There were, and I ask that would make you more knowledgeable or make you happier or make you wealthier, whatever good measured, you think there, there might be an let's say we train than I am a lot of people to continue to expose you to content that would actually make you knowledgeable then that I would actually figure out not to show you fake news because bacon it doesn't make us more knowledgeable or give a lot of violent content is enticing for you to watch if it makes you very angry and not happy today, I do tat tat. It can choose not to show you those
I was content, so I think, knowing how to measure things that are long term, definitely good for us and then building apps on those long term positive things, that's probably the ultimate way out of the current situation, as described by the documentary social goals. that kind of thing is we don't want to make that worse than it already is right. If we have the sort of I don't know, rudimentary, but more or less early stage a I and it's already doing what lets a facebook is able to do to us as humans. It as a country or, as is a global society. Do we exacerbate that times, a hundred times, a thousand or ten thousand, which is kind of the direction where I is headed. Of course right. We don't want to be defenceless against that kind of thing, any more than we already are right, which brings up the idea in the book in one year earlier writings, you had four waves of ay, I M paraphrasing here, but like there's internet ay, I write Amazon knows what you want. Netflix tells me what I should watch next and is almost always wrong, although I still
maybe watch some of those things like our algorithms right, crummy articles about sports that you can tell a written by about there's business, a eyes, so business analytics and deep learning and supply chain, and fraud, detection and stuff like that, and then actually I, which is computers, looking at photos or listening to audio and labeling it in categorizing things like that, where are we now? What autonomous ay. I words like machines that shape the world around us as opposed to merely understanding its self driving cars, drone swarms that paint houses or install windows on skyscrapers. Where kind of in this? Is it Extremism timeline. Where are we with? These were actually made in tremendous progress and the law that progress is coming from China, because China is the bacteria world and China has a strong incentive to automate the factories, because the blue collar workers in China making twice as much money as those in Vietnam and other lower wealth countries.
So as a result, the only way China can continue to produce goods for the world is to automate. So there's a strong push to automate and starting at the factory is the right place. Because that's where you can afford to pay a million dollar for any equipment that can automatically do something that may be hundreds of people do today and once it's perfect for for the manufacturing environment, it can move into commercial, so robots before shopping malls and restaurants, and once that work can move to our home and robust can do our dishes, including our homes in and cook, for us, so that is the progression from starting from and within and within manufacturing weaken breakdown, various tasks that we might want robust do, starting from visually inspection using computer vision.
that's, arguably third way but still important process in the factories and then moving to moving moving things around turns out to be a lot easier with in the factory or warehouse. As people know, Amazon bought a company called Kiba that when you buy something when you buy a bunch of things and there's a box, that's coming to your home, the Amazon, Kiva Robot will move to show to a person for a pic, and I then put it into the box and other shelf to the person. Take the item that the current work slow so moving. The shelves is the relatively easier thing, so anything having to do with Sportflex are people walking around pushing things that would be wiped out and gone and done with robotic then, after that to picking increasingly picking has been improving and picking is simpler or more difficult, depending on what industry, or in example, if you're always taking the same thing like in the laboratory environment,
ignition or doing a covert test- that's very easy, because you can just customized for that. Picking any arbitrary thing can be difficult. Riders an egg will break right, so that requires a lot more work There is the hand I coordination. Things are required dexterity and with a very fine you now putting a screw in place, etc. That longer term so in the factory were seeing right now going from easy, too hard increasing number of farm, repetitive, routine work being done by robots. So that's a lot of progress being done and some of that technology is now making its way into now, manufacturing environments. So, for example, many chinese restaurants today have waiter they're, not human rights. They are boss. You go to a restaurant. So when I go to some of the restaurants I go in, I place an order on my phone and then a tray walks up to me not a humanoid robots are the trade rules
after me with the dishes that water take it off, and then it says that I took it off. I finish eating and then I put to pay no human contact in the entire process. So that's already functioning in a number of restaurants in China and also in consumer. In my up. nice when I buy something on the chinese Amazon Equivalent or the chinese delivery equivalent for fast food, a robot actually brings it from the reception up to my group, so that was originally put in place to minimize and spreading of covert right now, it's standard is so convenient because I can just go. when the door mat pajamas. I will have to worry about being embarrassed because it's just a robot that sees me not a human so that
Nation is going rather quickly and, of course, our time as vehicles with have some ups and downs, but I think we're. My belief is that you want to launch in relatively simpler environments like forklifts, followed by airport luggage, transportation, followed by trucks, followed buses with fixed rouse, followed by rebel taxis and that's kind of the roll out. We see in China today the simpler scenario, have been now we're going to tougher scenarios thinking to you ass in a way moment has le tend to go directly to the tough problems. Two different ways to solve the problem both valid, and I think you know we're going to see a relatively autonomous vehicles on the streets of our. U S answer
and other countries in the next five years. We will see a lot of the enemy we see. I'm already in Silicon Valley is that there's somebody behind the wheel, texting and pretending to drive so that they don't run anybody over right, but you can't get in one and he can't call it on your phone. It's just being tested, yeah Your listening to the Jordan Harbinger show with our guest Kai foully, we'll be right back so much for listening to and supporting the show your support of our advertisers, housekeeper it's on around here frankly, so if you want those codes, those urls you dont have to write that stuff down. We put em all in one place for you, Jordan. Harbinger dot com, slash deals is where you can find it. Please do consider supporting those who support us and yet we have worksheets for many episodes. If you want some of the drills and exercises talked about during the show in one easy place there link is in the show notes at Jordan, harbinger dot com, slash podcast, now back to car foully
I mean: are you personally ready to get into a self driving car and just be like our right? It's gotta be very hard for those of us. They grew up driving, I think so. the technology is, I can recommend to your audience that it depends The environment and constraints you may or may not want to get into a fully autonomous vehicles as yet. So if they say you know a bus, shovelling people at airport, no problem very simple scenario: if it's in our tourist spot, probably no problem, if it's a truck only on the highway rashly cars in the highway, generally ok safer than people, if it's in a bus, robots with now humans. I would say it's ok, because it also is fixed rout, so it can get a lot of data on a small number of permutations, but it is really a car that teach you anyway. any time any weather and with no safety.
Driver in that car. I would say, that's quite challenging and unsafe, at least whether this year and maybe next year. I would wait and see the numbers of fatalities before I would completely like a driving too are autonomous vehicles is so it sounds like going from what you mentioned before, where there's going to be autonomous, ay I autumn jobs that hundreds of people used to do, especially in China work, which is the world's factory. It seems like the Nevertheless, the result of that is gonna be widespread unemployment and that the wealth gap of people who control a higher on the factory is going to be in those who used to work there. That wealth gap gonna, be enormous, especially in countries where there is a lot of and you factory or where there's a lot of mere hands on jobs that are now automated? I mean that,
it's going to be so many people, yes, but also why jobs are not at all immune to the shore. Of course, in the last two or three years, a technology caught RPF, robotic process. Automation has really taken off in a company called you. I pass and other companies have gone Publican them very well What they do is replaced white collar, routine work. These software robots sit on your computer watch everything you do and eventually one day tells your boss, hey, I can do seventy percent of the jobs and those parts of your time are rooted today? I lothar percent of the workforce remains to do more FIFA ones and then the day, will continue to improve and chip away at it. These are routine tasks like telemarketing customer service response, email address.
managing email, marketing campaigns, expense reports, hr processing and so on and so forth in the various admin area of work, so I think the a I replacement we'll be substantial in any rooting were white collar or blue color, so really all countries equally, the sharp ok. So do you think that countries are gonna have time to adapt to this because it seems like progress is going faster than anybody assume. So if we see widespread manufacturing job losses and say China, we see what spread white collar. Applause in the western economies were all kind of screwed great. If we're prepare it yes for their stars, silver lining here: ok, because I will do the work, so it will generate a lot of wealth for the economies. So the question is number one, do, we really should you that wealth, otherwise, the inequality increases the I make all the money- and while the jobs are gone the hour, so something like the universal basic income needs to be considered
that's not enough, because people need to be re skill, because people not only there. And on the job for the money, but for a self satisfaction, naturalisation contribute to the world, meaning of existence? Private yeah? So We need to be retrain and they can't just arbitrarily take a new job to be retained it because you could do what so my service job, that one's gone ragged be trained on graphic design that one's gone. You need help by people who know what jobs are likely to be two last longer, and then you need to get training and then the jobs. Last longer you'll have to train longer than you have to think hard, because any simple rooting minimal thinking job,
be taken over by ice or people who water pride in their work have two conscientiously get training and move into professions that are not so easy. Skilled jobs and some of them are require thinking some of em required in our thinking on your feet. Some require creativity, but also a big number, a large number of jobs in the service industry, jobs that require a high degree of human connection and trust and warm while those jobs may be somewhat routine. Those are hard for I to do because it doesn't
feeling it can only fake feeling and when it fix it, makes mistakes. People like that, and even if I did a reasonable job faking feeling and try to create connection people don't want to be connected to a robot beyond be connected to another person. So there will be job increases in service sector. So some kind of a coordinated plan by governments and companies and an awareness by the public is needed to do that, and that's why, in the book twenty forty one, I have several stories based on how the retraining could take place and how People can find a satisfaction in jobs that may look nothing like jobs. If today I know when we talked probably three are almost four years ago now you had said the third world. The developing world is going to be the hardest hit because cheap labour, cheap exports. You got all these laborers that are no longer needed. It could destabilize the whole country or the whole. Economy in those areas. Now you think you could,
stabilize everything everybody? Yes, I still think that inequality is a major issue because enough from a human race standpoint, when the top technologies and companies and countries can generate so much wealth can produce good at such a low cost. It would seem that we have a responsibility to human race to eradicate poverty, but at the same time feeling with the inequality that will be growing within the country and between countries. That problem isn't gonna go away, and I think I'm not sure what the global solution is, but I think we need to be aware of the problem and the weather was rely on some either some mechanism, or just the good will of the people cilantro to eat, to take care of that something needs to be done. Otherwise the inequality will cost more social tension and
these under even complex. It just seems like a I is almost it could become an inequality machine right where it really hit the poorest countries. The hardest is essential, creates pardon the phrasing here, but it essentially creates a useless class of people that can never generate enough economic value to support themselves, in addition to what you mentioned about having no purpose in doing a budget psychological damage. That way, like imagine, knowing that you are completely a drain on your society, you're never going to be able to pay for anything, because all you can do is skilled or semi skilled labour, which now a robot and in a can do to a thousand times better than you ever could and you're getting older right so like, robot can do something instantly that you ve spent your whole life. Mastering that's not good for you psychologically, it's not good for you. It's not good for the country to have that happen, and millions of people in a decade or a decade and a half, or even in two decades right, but we're moving so much faster than that. So you're right. It seems like this problem. It seems to me
This could creep up on us and we could wake up one day and be like. Oh, we didn't plan for this at all, so farther writing a book is so that people are aware of it and so that governments and companies can think about in start planning but also, I think, to your point about increasing number of people finding it increasingly difficult to make an economic value contribution I agree with that, but maybe we also need at the same time to shift the economic value social value, so someone who can no longer driver truck because Robert talks have taken over or someone who can not be as customer service rap because tat bats are taking over. Why can't day take on things that contribute to the society bit? Maybe not that much economically, but generates goodwill and warmth in connection? For example, elderly care, healthcare services, keeping the elderly and kids in a fast
her home company or for some people homes. Schooling for the kids right is home schooling, generating economic value- probably not much, but if apparent does a great job, can the child have ass, much happier and better future? Definitely so how can we as a society and courage? These kind That's new jobs that clearly add value, but not necessarily economic value. That might be the solution, because, if we just tried so hard to make every job at value while a is chipping away at the jobs that doesn't leads to a good outcome right. this is certainly a complex issue. That's gonna end up being politicized and probably botched which is kind of horrifying, but there's only so much. We can do right. We gotta make people aware of it and then hope it doesn't slap in the face going. To the idea of bias and biased mitigation right. It seems like the quality of data going in woody the quality of output coming out more or less that May or may not. True they I may be a ransom.
up nicely, but I guess where I'm going, This is let's say we train the data. We train the a on one point: four billion chinese people, because it's a chinese company that happens to be developing whatever. I that we're talking about right now. Could the data then come biased against. Let's say indian people right because chinese people don't like any of evil, is that where I'm going with us, I mean you ever conflict right now, but what I mean is its specialised for chinese province, Try, chinese culture, chinese ways of thought: is it possible? there's going to be like a cultural mismatch or they ingesting so much information that all of that stuff comes out in the wash so to speak. So a company say: chinese company wants to launch software globally and who, then the company must gather data globally from India, from U S and so on. Otherwise it
work are a good example is tiktok right. That is a problem that is global. Actually, their version for China is very different from the version. The? U S, not only is the training data different, but usage habits are different, so The companies that have global ambitions are we'll need to train on global data, similar situation is a large. U S, company trained a high technology to select people that they might want to interview because a trademark too many men, it became negative for women applicants. So it's not just the country racial basis, but rather there has to be good balance. among, if you want to provide spare ai, you need to make sure the data is the training day. That's balance, otherwise the bias will become in parent, so that I think, can be done
first by educating or the engineers that they have this responsibility, not just to make money not just get good results, but also provide something that is fair and their needs. be continued social media and other watchdog from this behavior. So the companies now that this kind of training is important. I also think there can be tools that can help Matically scan every time you do when they are training, and I love you- you have a data inadequacy problem a day that balance problem and suggest that you should fix it. Just like you know, compilers today, I report likely bugs and Prob, and warnings and leaks of memory. You can also alert potential buyers and fairness issues, so I think, with some effort put in education and training and tools, most other problem can go away, but- and I
Some will still remain. It just seems to me and look I'm a layman, obviously site or no squat about what I'm talking about when it comes to a lie, but it seems like the a process wont. Let me phrase, it is a question. Is the ay I process too complex to be made transparent, re local if someone's debugging code they go here is your problem. This is clear this needs to be rewritten awaited more flexible, but a it's not looking at a bunch of code. Here you ve got a neural network. You ve got deep learning going on right like this, not its. Let's somebody can this is your problem problem there. It's not a mechanical like that right to do you think the a process, is so complex that it's gotta be near. impossible to sort of diagnosed. These lay. It also seems like the more we regulate, something like this: the less efficient and useful it might become because we're essentially hamstringing it, and maybe that's a good thing in this case. The answer is yes, and no yes in the sense that, the reason I so good is because
decision and makes, is a mathematical equation involving thousands of variables, something we go. Miss cannot comprehend. If we could comprehend We would do it with only day. I did. I ask precisely because its accomplice too complex, to explain fully, however, because we are relatively simple minded being scale is tat. We can comprehend the fancy, mathematical, equations then I can basin. Come down the answer for us right. So let's say I went to a bank life long I got rejected. I say why, so the actual reason is a complex mathematical equation in charge your phone battery. That's why There is no reason why the air I can not analyse its decision and come up with the top five reasons and say it's because you didn't charge you have abandoned
seriously, you're incomes, not good enough. You haven't lived long enough in particular house, and your job is to know the job etc, because Ultimately, it makes this decisions for many. The same reasons that we humans make. So There's no reason I can't explain a good part of his actual decision making in a way that you may can understand. So I think that will be good enough and I think someone, we as humans give ourselves too much credit. Do we really think we know why we made? Every decision if you ask a driver, why did you make them over decision and ran into the house. They could give all kinds of reasons there is: may not even be true, they might want, may not want to admit they had wondering too many, so at least I will be honest as we programme and will attempt to explain it, and I think it will explain itself no, no worse than probably better than human explanations. I think this problem will be solved for Europe.
this is the Jordan. Harbinger fell with our guest Kai foully, we'll be right back for the rest of my conversation with Kai foully yeah. it's kind of like when you ask somebody why they bought something, was on sale. Well, that's not the reason you bought something like wave. You dig enough. You find out that they wanted it because they thought it would impress their neighbours and their feelings I care about. You know you just get. You can't really dig down that many layers, because people are really aware of them die out the a. I knows that it took the following: three hundred and fifty or three hundred and fifty I was in various into consideration in a might tell you the top ten of those variables that comprise eighty percent of the decision right. It can actually lay those out because it's part of the equation, whereas a human would never, even if your I can give you one or two good reasons why they ve done something and most of the time that's bs right. They don't know, we don't know exactly right. I do
that we won't be able to retrain workers fast enough to keep up with the development of a I write. It can even predict which workers are gonna, be obsolete and in a few years kinda, but maybe not really right training to take so long yeah. We can their predicts, maybe not exactly right but roughly, which ones will go first, For example, we can pretty accurately estimate that most are the more they prepare will need to be changed, because Cars, are changing not to say I, but electrical vehicles is a phone running honour, simpler mechanical parts and the job like plumber that's not going to be replaced by a anytime soon, because every building every house is different. A plumbers job is action. little bit like a detective right before you see the leak, would ya gotta find out which part of the wall to knock open? So we can make some predictions. So how would we do the training right? I think we can thus the basic thing is all the vocational schools really need to go through a revamped,
if you recall a dont train that many traditional, although mechanics, train, more plumbers and train more robot repair right in a similarly you, gotta medical school go into medical research, which I cannot do in humans. Creativity is needed, but maybe have fewer students seen radiology and pathology. These are that's where I will become increasingly good. So we can do a better map and can provide the training. There is still a very interesting additional issue, which is, I will take over the routine jobs. First, routine jobs tend to be entry level, jobs right, you do bookkeeping, become you You become a good content if your journalist, your first right about quarterly reports before you can be my columnist. But if a taking over all the routine jobs at every level. How does someone ever become a senior accountant or a famous lawyer or a great journalism columnists. So one of the stories in book? A twenty forty one is: maybe we need your help
made up jobs to give people the impression or pretext that they are working, but actually there game it's very like a pod cast park. Ass is not that easily taken over. No, no, it's just a made up job, though. Why is another major job? I mean x, Ray feel like I'm working, but really, let's be honest, tell hard, as I read books and I talked to smart people now made up job would when I say may that job I meant that you think you are doing something useful meaningful by this actually you're, not so some I think there are still thinking that I made a nailed it on this when you have a guy. Are so here's an example, a new person, we'll get hired by New York Times. Who is not bad experience yet needs Lhasa practice is right a bunch of quarterly reports, simple things, but those things never get public. I or maybe they get modified by I and then published or they get published, but I could have done the job, but by doing,
They quarterly reports. They get to now do annual reports that they get to do reports our industries they can get to become columnist. We may need to have these jobs that are really practitioner, jobs that the work you do is meaningless to the society, but is meaningful for your growth. So one of the stories in the book talks about new approach caught job reallocation. That is when a company lay off a bunch of people they get retrained and they get a sign to the domains they want to go into. Let's say they want to be a journalist, then they think they're working but firstly, there are the alpha that their work is not being used anywhere, but they are improving their skills until there at a point when they can take a more senior job. Yet this it's kind of freeing in a way right, because instead of keeping workers going- let's be honest, mindless crap for years because you need it to get done, you can ask
they just get them enough work that sort of on the low end of the totem pole enough to get trained to do something more interesting. So, instead of maybe having to pay your dues, so to speak at the newspaper for five years or more writing the police, blotter and writing about petty crimes and all this other stuff you do for a year until you can really throw something down. That's deserving of the paper itself that gets public right, so we might actually end up in more satisfying work earlier in time than we normally would. Yes, I think so, and ultimately I mean the process- will still be difficult and painful, but ultimately, let's say twenty or thirty years from now, when I all the routine jobs and we can be liberated from it. There were free to do that we love and things were passionate about things were good adds. That includes in spending time with family homes, cooling, our kids and the learning about poetry or sculpture, and I think our lives will be much more fulfilling an interesting if we could get up
the hump that is ahead of us look, there's a lot of exciting innovations and you write about many of them in the book, one of which was a I transforming education. Imagine a one on one custom teacher for literally every one in any subject that you want at any age and its basically free because of what's it going to cause for me to plug into Jpg twenty or whatever we have in a few years for to teach me a very specific but random skull that I want to learn, and it's just teaching me on my phone right. It doesn't need food, it doesn't need housing, its infinitely patient. With all my stupid questions and in dad jokes writing every single person on earth. Pretty much can have this in their native language at any time right right and for younger children. This could be entertaining Gatwick that loves basketball, it can make learning like you're playing basketball. If someone who likes a superhero that kid can become the superhero and try to fight villains ended in the process of doing so
Mass in the process and also earlier we talked about AI, introducing inequality, but probably in education and perhaps in health care. I can actually become equalising by providing a decent quality of service to anyone, whether their wealthier, not another use. That's really exciting, is drug discovery and re purpose sing, and I didn't really think about this, but it completely makes sense that were already using drugs that are quoting could save at sir doses or certain use cases for humans, but we don't necessarily know everything that that drug can treat, because nobody is thinking about every rare, random disease and every drug. That's ever been tested safely on human rights. So I so to figure that out addition to helping find but save actions for novel viruses like we're dealing with now. Absolutely today The big problems is that pharmaceuticals may spend two billion dollars to invent a new drug, so
They only go after a relatively common sicknesses, because a rarity, huge markets, huge market, If there is a disease, where only a hundred thousand people in the world have it, they can get their money back with that two billion dollar investment. If a I can analyze these pathogens and targets and I was asked more molecule or other solutions to work with the scientists. Together is a symbiotic process eyes, not replacing scientists, but in a way I can help the scientists in then ten times as many drugs. In a given period of time, because a rules out certain permutations due to its internal evaluation and prioritization? So that, ultimately fact is the cost of discovering a drug. may drop by ninety percent. Then many rare diseases will become treatable and am many common diseases may have multiple treatments in each design for a different type of people, pay someone
exposing or raising gender age or whatever gives the greatest efficacy. So I think we can definitely look forwards who are living longer and healthier, partly because of the new drug discovery, partly because of precision medicine, partly because we ve got the new genetic sequencing So you know we will probably live longer, maybe another. Forty years I can still come to your podcast they sure people will be sick of me long before then. Idea INA, give you mentioned equality before Come to me that a lot of drug companies can't afford to solve problems- or find cure diseases or treat diseases. That lets say only occurred in Sub Saharan Africa if it's an expensive cure, because the market, while its big, is extremely poor. But if we can have a I say, hey, you know what this is really easy cure for this Ebola or some other type of virus, that's even smaller and less scary. It can find it like that
and then it doesn't cost billions of dollars to discover and distribute it costs the marginal cost might even be negligible. It might even find a solution for this, while looking for something else- and we end up- able to treat hundreds of thousands or millions of people in very, very poor countries where normally a drug company would go we're not can invest in were never going to see a return now, like you mention with rare diseases, so there's a to be said for quality of life improvements when it to a high and drugs, and I didn't realize that finding a vaccine was almost like a very complex equation. You have to solve proteins. Some are you familiar with this process at all yeah? There are multiple process you have to go through. One is you can take the pathogen followed. The protein to figure out, where is the target target, is only like little pocket in which the treatment can go into, and then you can hypothesize how to fold the protein. Where are the target might be and what to put in it
would counteract the pathogen had treat the disease. So this is not all that are invented that way, but this is one possible path and in all drug discovery are looking at the infinite space, all the ways of treating all the problems, and I I can't help eliminate unlikely, pass and help select them prioritized more likely past, so that scientists have a much higher likely could there
process of conjecturing experimenting. There's the other side is once a drug is conjectured and the trial and Error Lee success. It needs to move into wedlock. It needs to move into the actual trial and that's a process where a I can help again by having these little Robo technician that can do at Thurmond twenty four by seven, with no errors and no risk for contamination that can further accelerate that part of the drug discovery. So I think the whole chain is something a I can fit in very nicely and we're going to see many public companies that will become listed does ai drug discovery and shut off from assume the costs will be either given the run for money, or they will have to find a way to learn and embrace this new technology. You mentioned in the book and twenty forty one that we're going to see a lot of games and other applications. I mean, there's a lot of application, the bucket of really good book full of shit,
is in some of the stories resemble a black mirror. Episodes of you are familiar with that show that, and I'm wondering when we're talking about things like mixed reality, where we are looking at something, and we can maybe see the score over the game or different sorts of layers to what were actually interacting with real life. It almost sounds like and, alas, for you protection here. Are we going to see something like Google Glass again, where we have our goggles and we're looking around? We can see warning there's a car coming. Our here is a restaurant that has your favorite food in right now our store, that's having assail like? Are we going to maybe see that type of thing? Yet again, absolutely I think that Google Glass was just way before it
and also it was packaged poorly that people think as a privacy issue. So those issues would be resolved in parallel in order for such a pair of glasses to work right that you can see and guess super imposed content on it that could be fun or could be for training or could be in a visualize new spaces. It requires a couple of things one is it can't be too cumbersome. There can be a huge had said and we can be very heavy. It can't be tethered so that the set of problems, technical problems and need to be solved
Secondly, the quality infidelity has to be high. If it's going to put things in the world that I see right now, while the better have the right living and the right shadows and ass very hard to compute, so they're still technical problems there and others interface issue. So suppose I see something. Can I use my fingers, not love or not user. You know track passer anything but actually use my fingers to grasp that either to put it in whatever shopping basket. Something is the good interface. So all of these are technology problems and need to be overcome until a normal, looking and tethered glasses that can deliver lifelike. Did it experience and that's probably around five years away. So that's kind of one set of ways to do. Ornamented were mixed reality. The other direction and are we saw Mark Zuckerberg recently show having a conference with someone. Inanimated environment are that's more virtual reality. I think that is also going to develop towards
more realistic last heather more convenient and target at scenarios. I think all of this will probably first find routes in entertainment and games because ass the situation where we can let her imagination run wild where things have to be perfectly father, realistic the treaty as a lot of value, but we do have to still solve the problems of very simple device wearing and the very high quality rendering and display, and also we can't get dizzy right. The motion sickness thank yeah yeah, I mean this is almost like. I want safe. turning, because these are big problems, but our brow,
are very adaptable, and so the motion sickness thing may be kind of a problem that ends up now, starting to solve itself in concert with better optics and things like that. But yeah really does seem like we are moving so quick, so much faster in that direction than we predicted in. Wouldn't you and I talked three four years ago. What do you think we're moving faster than even you had originally predicted? Gives your timelines or pretty tight back then as well yeah. I think we may probably look more progress than I thought we would there's always you know you can predict the existing technologies on how they were extrapolating. Whom did you catch predict? New technologies right, so this new huge language model foundation model. Pre training was not something four years ago, but it has really taken off so and will continue to see breakthroughs like that. So I think in the book in twenty forty one, I feel comfortable with all of my predictions, but I'm sure I missed a couple of big ones, so the future might be more powerful and surprising. Then
what was portrayed in closing here, and I don't want to get to sort of cheesy philosophical, but I wanna go for it anyway. What have you learned about be human through studies of ay. I well I ll and that there are many things that I cannot do and made me those are the real essence of being human. I started going into I thinking that I would create a replica of me figure out how our brain works and that's the night Eve assumption of an engineering students forty years ago, in building I that has worked well, how many many tasks exceeding human performance and beating us. I realise that actually whatever I ends up not being able to do for the long term. That is the essence of our being human and those two things. If we kind of summarize it is really about our creativity and capacity to learn and our compassion,
and our ability to connect and love each other carefully. Thank you very much, always a fascinating conversation. I'm glad you're able to join us today from our Beijing actually sort of aspirin? The top of the shell yeah, I'm in Beijing yeah thanks for inviting me yeah, you got at any time and look we'll do it again for the next forty years? Oh, but I hope to talk again in a few years and see where these predictions of landed, because, like however, this stuff is moving so much faster than it sounded like from your earlier work. It's exciting and it's terrifying and the lesson here, kids is less lawyers more plumbers by somebody like that. Ok, very good! Thanks a lot Jordan yeah, I've got some thought this episode, but before I get into that, here's what you should, Next, on the Jordan Harbinger Shell routes, It made me aware of the power of the medium of television. There is miracle before routes in euros in America after it and they were the same country.
I'm wondering if the theme song was stuck in your head for the entire twenty one year running the show or if they had some brave still stuck in my home, the Silver reading rainbow, for example, every kid watch that, whether they like it or not just came on after cartoons. If memory serves our Solidarity Street or the they rolled in the av cart, you know on Fridays in Washington, School Amis. That's true, I think we did watch it in school with the honor of like a real to real projector If you want a veal expert old, I was a kid watching you we were watching real the real, but you were on the real problems, close the windows are treating Rambo teacher has a hang over, which is a hundred percent. What that was twenty twenty hides the back to words. Why didn't you implode? You are nineteen, I mean how can we not see and headlines like Laval,
Burton Pleads, not guilty says we have to take his word for it, and then we don't see. How long did you work on roads came to me in the shower? There's anymore, I'm just a storyteller. That's what I've discovered about myself, I'm a storyteller! I was born to storyteller. Can I'm going to do it in many ways, is again acting writing producing directing casting fulfilling my purpose. I genuinely believe that you can leave it that we are therefore, reason I believe that its important for us to covering discern what that reason is right, and then pursue it with everything we ve got. For me, with the legendary love. Our burden of reading Rainbow and STAR Trek same check out episode to thirteen of the Jordan Harbinger show interesting to talk about a I, especially with somebody who is as much an expert on this as Kivu. Lee now we tend to over
estimate technology in the short term and underestimate knowledge in the long term aim is no exception to this. The book, a twenty forty one is interesting because it's written as aid is a series of explanations of ay. I and stories that illustrate the possibilities of the technology. So it's kind of, like black mirror episode if you ve seen that only a little more hopeful and less dark if you're any like me, you have all these sort of kindergarten questions about a I as well. Will they replace us? What will we do? Well, my computer be bossing me around my phone already. Does HIV he has developed in the past five years. Beating humans and cancer diagnosis, legal and seeing games of all sorts from data to to go and, computer vision is now better than human vision in identifying objects and people. So these sort of kindergarten questions that I hope this up clear. Some of it up, but also I'm torrent. Is this
even more terrifying than it was before, and is this what's going to make? All of us feel all right with the natives, who grew up with a sigh are the ones adapting. This is possibly the technology. That's gonna make everyone. My age just feel like we don't get it and I'm I'm totally ready for this, or at least I'm totally ready to feel like that. I'm not necessarily ready for the technology data and roger thousands of times cheaper than before food service, cooking and deliveries- all gonna be automated. A lot of stuff already is, but imagine the cooking yeah nope bull from ingredients your belly other than you shoveling it in your mouth right. All automated having Kelly, who was on the show episode five, thirty seven. He said that a I was as important and as much of a game changer as the invention and discovery of atrocity now think about that for a second this is going to revolutionize everything, we're still away is away from all this. Of course, robotics isn't advancing as much as a. I wish this kind of weird think about areas great at thinking,
not necessarily great, at moving around and fine motor tasks. We, download an algorithm anywhere robots, to be manufactured, shipped and maintained on site. So I will make workers more productive, but necessarily obsolete right away, candlelight tractor worked farmhands farm hands people working on farms. In fact, we probably for the foreseeable future as well to pick strawberries in various. It's just really really hard to make a robot. They can do that as well as the on four. Finally, when it comes to replacing jobs, poorest countries. Be hit the hardest ay. I it's an inequality, machine it. May I Philly, create overtime, a useless class, of people- and I put that in airports, because it's a little cruel, but it's kind of true these are people. Can never general enough economic value to support themselves, imagined psychological and societal damage that comes
that robots can do things instantly that humans have spent our whole lives mastering. That is not going to be good for society at large and we need to start thinking about what we do now. Yes, we can retrain people, but some people are going to be able to be retrained in time? you're going to be obsolete before they can even be retrain and that's, provided they have the raw material on the intellect to be able to be retained in the first place. So that's a real argument for universal basic income or well some sort of solution needs to happen. People general aside from Elon Musk things that we are still really far from robot overlords or even generalised ally, but man for was China Sputnik moment when it came to a high at this, is very different, then how deep blue IBM deep Blue beat Gary Kasparov, also against on the show in chess in the nineties to be able to beat someone at go is right. They really a feat
China is investing massively in artificial intelligence. That was the topic of my earlier interview with carefully it's so little scary. That should light a fire under our butts here in the western world for sure in a we get preoccupied whether I will even happen and what will happen to our job. when it does, but we are really thinking about China or other superpowers racing to get there before us, which is really the issue that we should be taking note of here. China is set take the lion's share of new value. Added to the GDP by I seven trillion dollars, or something like that. So we really need to focus on this. There needs to be political will. We need to get Smartest people in on this and work- and on this I know we already are, but we really need to triple down on this a sap. If we are to be competitive in the coming decades. Big thing it carefully. The book title is a twenty forty one links to all of his stuff, as usual, will be in the website in the show notes at Jordan, harbinger dot com. Please use
Website links. If you buy the books from our guests, it always help support the shell worksheets for the episodes are in the show, notes, transcripts and shone out. There's a video Of this interview, given up on our Youtube Channel at Jordan, Harbinger Dotcom, Slash Youtube, we ve also got her, channel with cuts that don't make it to the show or highlights from the interviews that you can't see anywhere else. Those are a Jew harbinger dot com, slash clips, I'm at Joe, harbinger on both Twitter and Instagram, or you can hit me on Linkedin can you how to connect with great people and manage relationships using systems and software and tiny habits over it? six minute networking course that courses free Jordan harbinger dot. Com, slash course, is where you ll find. It dig that well before you get thirsty and remember most of the guests you here on the show they subscribe to the car, contribute to the course so come join us you'll, be in smart company. This show created in association with POD, one by team is Jen Harbinger, Jason Sanderson, Robert Frogeity million Campo Ian bared, Josh Ballard, Gabriel, Ms Raw. He remember we re
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Transcript generated on 2022-03-03.