Also, that it will allow for the creation of completely new jobs and industries, just as in previous revolutions. Turny event, occupational is at an alltime low, so theres nothing to worry about. That is what this panel will talk about. Our automation and aia substitute or koppelman to human to humancomplement labor . First, we have diane bailey, associate professor at the school of information at ut austin. Her Current Research interests include remote occupational she conducts empirical studies, often involving multiple countries. James bessen is from the Boston University school of law. He is an economist. He does research on whether passion promotes innovation, how technology affects jobs, skills, and wages. His latest book is learning by doing. At kamar is a researcher microsoft research. She works in several subfields of ai. She particularly looks at the real word applications. Hal varian is chief economist at google. He has been involved in auction design, corporate strategy, public policy. Professor at uc berkeley and three departments. A good place to start this panel is to talk about what we actually mean by artificial intelligence. The preliminary discussions, ece brought this up. So i will ask you to lead us off and tell us where we are with a. I. Ece thanks. As a person studying ai and is not really involved in these policy discussions, it is a pleasure to be here and hear the discussion. A. I. , artificial intelligence, is around 70 years old. It started with alan turing, when he wrote his paper on machines. Then, he of the fathers of a. I. Came together and wrote a paper that said this is what is. To they had a meeting where they discussed all the different applications of a. I. That we think about today. The problem ended up being that it is more difficult than they ought it was going to be. Out to bes turned easier, some things turned out to be harder. We are going through these ups and downs and winters and summers, where he realized that we are getting kind of better at this oh, no, i think this is still kind of hard. So what is a. I. . There are multiple definitions of a. I. One definition i like very much is the activity of making machines and intelligent. What we mean by intelligence is, for whatever the machine is divine best designed for, we expect the machine to react appropriately iss and the environment and reacting on it. That is what we mean by intelligent machine. But intelligence is a term we think of humans for. Humans are intelligent. Other animals are not. A lot of abilities humans have we expect an a. I. System to have. So what is going on right now, why we think a. I. Is so much in the press. I was a graduate student 10 years ago the advice i was given was if you are in the job market, do not say you are doing a. I. Term that wasas a so kind of poisonous. People thought nothing ever comes out of a. I. Companyle is an a. I. From the birth. What is really going on is there fivewo sectors in the last to 10 years that came together to make some of the algorithms we are ready had in the field very successful. For some tasks that humans are good at, like perception. Data now coming from sensors, coming from crowdsourcing, coming from human activities. Conversation than ever before. That will increase as well. May things like deep numeral networks very successful. How to train existing algorithms. Through this, now we are seeing great advances in perception tasks, like image recognition. So then, we see these tasks that are very associated with humans, like perceiving the world and where objects are, i just machines are really getting intelligent this time. Scott before we go into the labor aspect of it, a. I. Has been around people have been working on a 70 years. It comes and goes in popularity. Is it the case that the last time it was popular, someone may have had a panel like this, where people were sitting, saying this is the time it is going to work . Or is is there really Something Different this time . Ece that is the question we are here for, to discuss. However, when you look around there are, already, a lot of applications of a. I. People use every day, like search engines. Was nott like a. I. There. Athink if a. I. Was good some tasks that others were not good at. Now, with new techniques, a. I. Is inching into tasks a. I. Was not good at by humans were good at. That is creating, first, a discussion about what other tasks to sheehan will be able to do now that we have these techniques. Second, what does this mean for the human job . That is something we need to see. However, there is another discussion, which is does this mean we are getting job loss because of intelligence . Meaning i will have a. I. Technique that will become so good that without much customization, i will be able to solve all a. I. Tasks . I do not think we are getting there. Scott jim, you have been writing about labor and a. I. Tell us your view. Are we going to be jobless . [laughter] and is that good or bad . [laughter] james not in the next 10 or 20 years. In the had a. I. Workplace and marketplace since 1987. Do. Systems were used to fraud section in credit card systems. But we had computer automation, some of which is not so we are seeing an acceleration in the scope of things that a. I. Can handle, and maybe in the case in which it is addressing. It is about automation and the impact of automation. Perennially have a basic many people basically misunderstand what automation means for jobs. It is commonly assumed if a job if some tasks are automated, jobs are lost in the occupation. That is simply not true. We can look at manufacturing and we are well aware that lots of manufacturing jobs have been lost automation. In the 1940s, half a million textile workers in the u. S. Now there are only 16,000. Most of that difference is from automation, something global trade. That has clearly had a dramatic effect on many communities, on many workers and their families. The thing to remember is automation can increase jobs. We only got to have 500,000 textile workers because for the previous hundred years before 1940 automation was accompanied by job growth. How can automation sometimes create more jobs and sometimes eliminate jobs . What is going on and what does that mean . It comes down to command demand. When you look at textile automation, in the beginning of the 19 century the average person at one set of clothing. Automation met the price of cloth went down and people could afford more. Demand was elastic so they bought more. They bought so much more that even though they needed fewer workers to produce the cloth, many were employed because they were buying that much more cloth. In the 20th century people have closets full of clothing, further price decline is simply not going to produce much more demand for cloth. And the have automation net effect of eliminating jobs. What is happening with computer automation, we see lots of evidence of examples where computer automation, just like the early textile automation is creating jobs. One of my favorite examples is the bank teller. There is a great untapped demand, war there was a demand for getting cash at remote locations. The atm machine came along and people assumed it will wipe out the bank teller. We have more bank tellers since the atm was installed. The reason is it made it cheaper to operate a bank branch. Thanks could open up more branches and serve more people. There was a market demand for that. They built so many more branches that even though they needed fewer tellers per branch, they were employing many more. That is the pattern we are going to continue to see in many sectors of the economy. Not in manufacturing over the next 1020 years. That is what i think the Immediate Response is going to be to a. I. As well. Diane, do you say accelerating change in a. I. Will generate more jobs were quickly. That is counter to what others say. Eric for example his book a couple of years ago said one of the differences is the rate of change is not allowing industries to catch up. By allowing the labor market to catch up. You are saying the opposite, right . The faster the changes, the better . James yes and no. A faster change will if you have elastic demand and you were making faster change so productivity improvements will ring job growth, if you make faster, you will have faster job growth. At least for the period of time that is occurring. It will be disruptive. I was may be overly optimistic in the way i described things. When the question is, are we going to be seeing mass unemployment, the answer is no. Are we going to see individual jobs destroyed . Yes, but others will be created. As that accelerates that is disruptive. The textile workers in North Carolina need to find jobs, need to have skills. There are jobs opening up in the rest of the economy. And the same thing everywhere else. We will continue to see jobs eliminated. The acceleration will put more stress on our ability to transition people, to retrain them, to relocate them. Scott diane, i know you were much more less optimistic. Diane i would just ask this. Book04, a guy read a called the jobtraining charade. What he talked about was that we were losing a lot of manufacturing jobs. The way we talk about that is these people need to be retrained in other jobs. We will train them to be acres and bakers. There is only so much bread and pastries we can eat and there were not enough of these other jobs are people to take. The language of job retraining started to change from teaching people new Technical Skills to enter different jobs, to focusing on what they call soft skills. People started to be told the reason you dont have a job is because you are lacking Technical Skills, for your communication skills are not very good. You dont work well on a team. It started to put on workers for their lack of soft skills rather than recognizing we had a structural shift in the economy and what kind of jobs were available. I was asked about two weeks ago to sit on a National Academies of Engineering Panel to talk about engineering workforce and how they needed to be more adaptive to survive in this new economy we are going to be seeing. I work at a large public institution, the university of texas. Getting an invite to sit on the National Academy of Engineering Panel is a big deal. That means i can put it on my tv in my get a 3 raise set of my 2 raise. I have some skin in the game. I turned it down. I turned it down because i told them i do not believe in the premise of the panel. They thought they were putting the onus on engineers to become more adaptable, be a quick learner. They are telling all of us these things instead of saying well start seeing fundamental shifts in the economy and maybe we ought to start planning for that. As all of us, not just us individuals becoming more adaptive and quicker learners and moving up the scale. There is only so much room at the top. If what we think about a. I. Might be true, there will be only so many jobs and not all of us are quick to go up the ladder. That worries me, what will be left for everyone. I think there are a lot of problems with job training. We have issues with geographic relocation. You see a lot of jobs appearing is not really see unemployment. You also have a great difficulty. My book is called learning by doing. A lot of new Technology Related skills have to be learned on the job. It is not a matter of the classroom entirely. We have to come up with new ways of getting people experience. But i think we do see plenty of sectors where there are knit skilled jobs emerging mi dskilled jobs emerging. Nursing jobs have been in great demand for a long time. Yet it is often very difficult for people to transition into those. We dontt have understand what is involved in making all these transitions. Scott you are bringing in the longer term talk. I want to say a word about this jobtraining issue. Jobs are here and the skills are here, you bring the skills of to the demand or you bring the job down. There is a lot of that going on through technology because it used to be to be a cashier you had to know how to make change. To be a taxi driver he had to know how to navigate around town. Not necessary anymore. To be a veterinarian you had to identify one of 250 breeds of dogs. Not necessary anymore. You can do that with a. I. Or your phone for that matter. This cognitive assist is a big deal because it allows the onthejob training you are talking about. You drive around town and learn your way. You learn how to make change because the machine tells you. The breeds of dogs on the phone. There are a lot of delivery mechanisms that are extremely efficient in the onthejob delivery of education. Look at you to. There are 500 million video views per day of howto videos on youtube. I will that you almost everyone in this audience has asked something in her house by going and looking at a youtube video. These are not just highlevel cognitive skills like solving quadratic equations. They are important, manual labor skills that people can learn how to weld, how to replace a screen door, how to hang the window. Scott if i were to play devils advocate, that is a lot to prepare people who were not called in to get work. Repair people who did not get called in to do work. Hal when you look at the next part of my talk we talk about what happens to them. I want to talk about the theme that released to this discussion. We talk about the demand for label and the areas the theory is a. I. Will reduce the demand for labor. On the other hand, if you look at the supply of labor, we can find a different story because that is only one social science they can predict 10 years ahead. That is tomography. Everything kind of pales besides that. 1946, that is when the baby boom started. 1946 to 1964. After that, there was a baby bust. Then there was the echo of the baby boom. You can look through this whole series of population changes and add 65 years to it and we see what is happening now. When all those baby boomers are retiring, that is followed by the baby bust. What does that mean . The labor force is growing at half the rate of the population. 20202sade of the you will see the lowest growth in the labor force since world war ii. If look at the labor force, you restrict immigration, it is actually going to decline. All those baby boomers are retiring. They expect to continue consuming. You need some workers somewhere to be producing this stuff they need to consume. You have this race going on between automation, which is increasing productivity, and you have the supply of labor which is very, very low to decline. We have a good in the u. S. , japan, korea,a germany, italy. They are seeing outright declines in the labor force. From very, very worrisome the point of view of the future of their economies. Look at robots. What countries of the most investment in robots . China, japan, korea, germany, italy. They have to have those robots. They have to have some improved efficiency and productivity to produce the stuff their population will be demanding. That is true is a worldwide phenomenon. Unless there is a really big surprises on the, you will see surprises on the automation side, you will see this in the next 25 years. Scott how far down the line you see that . Hal 20 look at the figures around 2060, bc the labor force growing at the same rate as the population. It is interesting to think this is all because of this huge shock of world war ii. It created this gigantic demographic event that does not work itself out for 100 years. Scott it is the baby boomers fault . Hal of course. Scott it seems like so far there are four issues. What is a general shortterm versus longterm. Is there anything you can do for people who might be im not sure what the right word is displaced in the short run . Does jobtraining play a role when we learned about the effectiveness of that . The distribution affects, shortterm and longterm. And over time the demographic and demand for labor, which will swamp everything. Diane and the inequality issue, whether it benefits just accrue to a small group. Diane, you turned down this position at the academy. Their projectink should have focused on to address her concerns . Your concerns . Diane we should be paying attention to power dynamics. You hear a lot if you read about books on a. I. And predictions about jobs, look at the bureau of labor Statistics Data that describes jobs. Describes the tasks and jobs. Based on that description we will tell you some percentage of jobs are going to be automated or replaced by a. I. Within some period of time. They are doing that based on description of what people do. No job is just what you do. Every job takes place in an environment that is surrounded by, for example, all kinds of occupational norms and perhaps regulations. I spent a decade studying how engineers are using new computational techniques and software. Things like finite element analysis. I wanted to understand how it was changing design and analysis in that field and what it was doing to the workforce. I will give you two quick examples that point out issues of power and when workers have power and how they control Technology Choices made for them and when they are not in power. It people who chose power, is power held by the government somewhat. If you look at Civil Engineers to design Building Structures like the one we are in, their solutions are governed by a strict law and regulation that involves things like peerreviewed and accounting review of plans for building. Because of this building were to fall down, those of us who survived would sue. Is theson responsible Senior Engineer who put his professional stamp on the drawings for this building. And because that person faces professional liability, they are very careful about using automation in their work because they know Computer Software programs can yield unrealistic unfeasibleased on assumptions. For Civil Engineers everything is about those assumptions of how a load travel through buildings. That guides designs. They rejected a lot of automation. It is not like they use the techniques, but they dont use any automation between the steps of Engineering Design and analysis that we see in other fields. Now i got automotive engineers. Scott are you portraying that as a positive thing about engineering . Does that necessarily make us safer or less safe . Diane i think it makes as much safer. I would hesitate to write in an elevator that a computer had designed, and all the Civil Engineers i watched would tell you the same thing. It is because you have to watch i can go to countless e