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Richard H. Serlin
Tucson
President, Summit Personal Finance Education and Credit Counseling, Adjunct Professor, Univ. of Arizona, MBA, Univ. of Michigan, ABD, Finance, Univ. of Arizona
Recent Activity
"The greatest number of emissions-related premature deaths came from road transportation, with 53,000 early deaths per year attributed to exhaust from the tailpipes of cars and trucks." At: http://lae.mit.edu/air-pollution-causes-200000-early-deaths-each-year-in-the-u-s/ This is tragically interesting. It looks like more people die from motor vehicle air pollution, even in the US, than accidents. Some recent data showing that air pollution much more harmful to health and longevity than previously thought. Definitely an issue in deciding where to live, the advantages and true costs of electric cars, and much more. Wish I had more time for blogging, but just hasn't been possible, lots of good ideas and half finished works, but 'tis how 'tis; you make the best. Hopefully I'll finish something this year, for all my reader.
Toggle Commented 2 days ago on Links for 10-16-17 at Economist's View
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Congratulations! Beautiful pictures.
Toggle Commented Sep 4, 2017 on They Grow Up at Economist's View
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Yes, the market is so incredibly efficient, EMH Baby! Fiscal stimulus? No effect, all people know exactly the spending effects and alter their saving perfectly to counter it! Their knowledge of all the public information in the world, and expertise in every area there is, is perfect (otherwise freshwater ideology and models would be a lot less valued)! "Almost 90% of Americans don’t know there’s scientific consensus on global warming" At: https://www.vox.com/science-and-health/2017/7/6/15924444/global-warming-consensus-survey
Toggle Commented Jul 11, 2017 on Links for 07-10-17 at Economist's View
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Why has the published rate of productivity growth been so low, at least so far, with all the advance in robots and computers? Here's an idea I have: Suppose you have a world with just three types of goods: (1) Manufactured hard goods, (2) Health care, and (3) Other services Now, suppose the manufactured goods market is highly competitive, but the other two types of goods have a great deal of monopoly power (In a model of this, you could just make them complete monopolists, who set the price at the profit maximizing level). Next: There's a huge productivity shock. The cost to make manufactured goods drops in half, and given that it's a competitive market, so does their price. But this allows the monopolists in the other markets to raise their prices greatly, given that consumers now have more ability to buy their products. Suppose the CPI basket stays unchanged. This may lead to the inflation measure being close to zero. But manufactured goods are weighted less heavily, as they are now very cheap, and Healthcare and other services, the monopoly goods that are increasingly expensive, more heavily. So, the high productivity goods get weighted increasingly less heavily, and the low productivity and monopoly goods, where the supply is always highly restricted no matter what anyway, are increasingly heavily weighted in the inflation measure. Thus, productivity may be greatly understated, TFP growth may be greatly understated. I'd love to do a complete model to explore and check this, but, of course, I probably won't have time until I'm long retired.
Toggle Commented Jun 8, 2017 on Links for 06-08-17 at Economist's View
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Larry should have noted that robot "wealth creators" are not like human "wealth creators". Robots are not subject to income and substitution effects, the backward bending labor supply curve, ginormouos positional/context/prestige externalities,... Larry probably thinks that he's being cute and appealing to the right with this, but Larry so so often is cute cause he loves to sound cute and clever, whether the marginal social benefit is dwarfed by the cost or not. You do not want to give in on this incentive point, you want to illuminate the truth of it, not continue the misleading to say, ha ha, so cute how I used that to appeal to the right.
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"Mr. Friedman underscored problems of asymmetry in regulation: People who especially benefit from a particular regulation will be inclined to lobby or bribe government officials for it. On the other hand, members of the general public, who might suffer from such regulations, will not be attentive to the many rules that affect them, each in a small way." -- Shiller article This is the same Milton Friedman who assumed people had perfect information and expertise on everything in the market. They were all electrical engineers who knew the exact schematics of every toaster and refrigerator to know if it would burn down their house, but they had no idea what any government regulations or policies were -- Hey, it's ok, and so scientific, to just assume anything you want about human beings, as long as there's lots of math and internal consistency and microfoundations -- And, of course, it makes libertarianism look better.
Toggle Commented Feb 19, 2017 on Links for 02-18-17 at Economist's View
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Haven't been posting much for various reasons, a huge one is being immersed in the study of AI and its implications. Should have some long posts on this in the coming year. But in the meantime, I'd like to get on record various thoughts and insights. First up, and I think this may be extremely big and profound, AI may plummet crime (in a reasonably non-corrupt and democratic government system). This technology can be, and I think very likely will be in the not too far future, incredibly powerful and cheap at catching criminals. The cost of cameras and other sensors has absolutely plummeted at the same time that quality has taken off. Digital cameras, for example, are incredible clearer and more accurate, yet far cheaper, compared to 10 and 20 years ago. So, basically, cheap, ultra-high-quality cameras and sensors can be everywhere at little cost. If anyone steals the vast majority of things, then a camera (and other sensors) will catch the act. Now, you may say this is common now, so what. Some grainy photo, that does very little to catch the thief. So I might reply, but now the photos are pretty clear. You reply, still, so what, how are you going to find the identity of the person in the picture? Put it up on some bulletin board hardly anyone looks at? But here is where the AI comes in. The AI looks at it, and has all the time in the world to look at everyone, as it can look at and analyze hundreds of cases per second. And the AI will be amazing at facial recognition, as well as recognition of other aspects of the person. It will scan the internet and records everywhere to find the person who fits the feed from the cameras and other sensors. Ok, you say, then people will just start wearing masks. But, I reply, it will still often find you from your voice, your body, even a close up picture of your finger prints from ultra-high-quality cameras everywhere that cost very little. Ok, you say, then people will wear baggy clothes and gloves. But, I reply, it will video the unique way you walk, how you move, down to very fine detail, and the next time you're walking in public, even hundreds of miles away, you will be picked up on a public camera, and the AI will see you and match the same unique movement and walk. It will use it's highly accurate modeling, to show there's a 99.9% probability it's you. That will be sufficient to get a warrant to take you in for questioning, the AI system will alert the police and send them to pick you up. It will be out of nowhere; you'll never know what hit you. You'll be asked to give voice prints; a search warrant will be issued for your home to find evidence, and in the end, almost surely all of the evidence amassed by the police and the AI will be beyond a reasonable doubt. It will just be very easy and cheap to find criminals. And this will largely extend to white collar crime too. Cheating on your taxes? Just about all transactions may be recorded digitally, and the AI can look and analyze every single one to see if, all data considered, it all fits the intents of the tax laws. This kind of examination would have taken massive human hours, and would pretty much always have been prohibitively expensive. But with the AI, and just about everything cheaply recorded, the cost will be insignificant, and can be done as a matter of course for the vast majority of people. So, basically, crime will get extremely rare, at least crime where the criminal is not caught. And, at the very same time AI and robotics will take over more and more of the lower skilled jobs (as well as some higher skilled), so more and more of the population will not have the education and skills to have a market wage above minimum (or even subsistence), and thus to be employed. So, the ramifications of these very possible technological developments over the coming 10-50 years are certainly something to consider. Again, a key thing I give, is that if you don't want to make decent employment hopeless for a large and growing percentage of the population, we're going to have to invest far more in education and Heckman-style early human development. That's always a huge part of my solution, and it looks pretty unavoidable. Post eventually, sometime in the next decade when I have time to do it really well, which will include still lots more AI study. One recent benefit of this study: After years of working with, and studying, Bayesian statistics, I now have what I think is a really deep understanding of basic intuitions. I'd love to do a post/article on this, something that I think would be really valuable that's not anywhere (or extremely rare and hard to find). Bayesian statistics is a very important part of AI, probably the most important AI tool today.
Toggle Commented Jan 19, 2017 on Links for 01-18-17 at Economist's View
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I do think that things like universal free education and training would help and resonate, both politically and economically. Universal free college, retraining, high quality preschool and day care for all children, would not be looked at as a handout; as working at the library, the computer, with the books at the kitchen table, in the mechanics training shop, in the machinist classroom, etc., few would call not working. This is a great part of the solution, and I think universal free high-quality education and training would have done well politically, and would make our country a lot more productive and wealthy. But let's also keep in mind that we lost by the slimmest of margins, and only then with the help of Russian hacking, a party apartchick in charge of the FBI outrageously breaking bureau rules for his party, and a candidate who was not nearly careful enough for this day and age. Duy acts like the Democrats are hopeless and must make massive changes to have any chance of winning, which is not true. Certainly, there is great room for improvement, but radical changes in policy are not required to win, just a recognition that things have really changed. Be ready for Comey's, and much more. Expect all of that, and be prepared well in advance. Be populist, but it can be in a way that really helps that Democrats agree on, that makes the country a lot more productive and strong, like universal free high quality education and training.
Toggle Commented Dec 6, 2016 on Trade, Facts, and Politics at Economist's View
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I don't see Tim offering a solution either. I would say that education and training are jobs, not a safety net or handout. If you give people free training, free college, with the support for living expenses to be able to do it, then they are working, and they feel they are working, in the library, at the books, at the computer, in the mechanics training shop room, etc., and that can resonate, and it does make them more skilled, and the country more wealthy and productive. So, I think free education and training is a big part of the solution; universal college, retraining, high quality preschool, etc. You may say some are too old to upgrade their job skills enough, but just the effort, and general education, helps, and it gives people work, and becoming more educated and skilled even when old sets a valuable example for your children and grandchildren.
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I don't see you offering a solution either. I would say that education and training are jobs, not a safety net or handout. If you give people free training, free college, with the support for living expenses to be able to do it, then they are working, and they feel they are working, in the library, at the books, at the computer, and that can resonate, and it does make them more skilled, and the country more wealthy and productive. So, I think free education and training is a big part of the solution; universal college, retraining, high quality preschool, etc.
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Interesting for economics and finance research: If the reasoning behind EMH is true, then not only should financial markets follow a random walk, but so should political candidate support. If human beings all possess all the public information, and the expertise to analyze it instantly and well, and they're 100% forward looking, then poll numbers would only change due to unexpected events, which would be random, independent of all previous information. So, political poll numbers would follow a random walk. If you can show through econometrics that these poll numbers do not follow a random walk, very substantially, then that would be (or should be) strong evidence against the EMH.
Toggle Commented Nov 2, 2016 on Links for 11-01-16 at Economist's View
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With regard to a Kevin Drum post today: "Reversion to the mean" Honestly, at this point it's hard for me to even watch (but I have to look at the basic facts each day, for responsibility reasons). But I will say this about "reversion to the mean". This is a pretty high-tech statistics concept. And it's often hotly debated whether it exists in a given situation. For example, those who argue that financial markets are extremely efficient, even perfectly efficient (I think almost always for ideological reasons, and/or because for that kind of theory they've had years of toil to get expert in, and so they don't want its value and prestige decreased), argue that real asset prices follow a (perfect, or near perfect) random walk, which means no reversion to the mean. Future events are independent of past ones, like coin flips, or dice rolls; same exact random process no matter if you previously flipped 10 heads in a row. It's still a 50% probability of a tail on the next flip. But my big political point here is that if there really is mean reversion – substantial mean reversion – and there really could be – these are human beings not coins or dice, then a political party could potentially gain a substantial advantage by hiring serious PhD statisticians to study and model it, to see when and how it occurs, and thus where and when to better deploy resources. Even further, if there really are pretty predictable patterns of this type; like mean reversion, but others as well, then sophisticated AI programs can study the data to find them, and perhaps point to substantially improved strategies. Of course, the party that actually believes in science and reason, and thinking beyond only simple-minded soundbite reasoning and dogma, would be more likely and able to take advantage of this kind of thing, so it might be something for the Democrats to look into, if they haven't already, with some serious academic firepower. Paging Sam Wang…
Toggle Commented Nov 2, 2016 on Links for 11-01-16 at Economist's View
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With regard to homeownership rates I think it's important to note that this is snapshot, not at any time in a persons life. If the median age is 37, and no one owns a home until 37, but everyone does from 37 on, then the homeownership rate is only 50%, but 100% will be homeowners during their lives, and from middle middle age on. It may usually make sense not to own your own home until you settle down and have children. Most people don't understand this, but it's usually much more costly, in money and time, and lowering of wealth accumulation, to own a home than to rent an apartment.
Toggle Commented Oct 23, 2016 on Links for 10-22-16 at Economist's View
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Some comments on the Turner skills post. I wish I had time now to really do a good thorough post on this. I think you really have to ask, what would it take with current technology to double a country's, or the world's, GDP. What are the bottlenecks with current technology? Raw materials? Very recyclable, if you have skilled people to run the recycling, because we don't lack the lower skilled. To me it looks like largely a matter of continuous returns to scale for a great deal, with recycling, or with just utilizing undeveloped raw materials. But what prevents this doubling of high tech production. The bottleneck appears to be high skilled people, engineers, managers, technicians,... Power can come from solar and nuclear, if you have the skilled people to greatly ramp up it's production. Read more Reply Comment Richard H. Serlin OCT 14, 2016 "If more people become more highly skilled lawyers, legal cases may be fought more effectively and expensively on both sides, but with no net increase in human welfare." But what if more people become physicians and nurses and dentists? In a reasonably well functioning economy, the price of health care should come down greatly, access and quality should go up. This can make a huge difference.Read more
Toggle Commented Oct 14, 2016 on Links for 10-13-16 at Economist's View
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Ok, here it is. Thank you for waiting (Mom). My reply to the Bank Underground post (which cited me): I have now had a chance to read your post carefully: If you look at my post in response to your first post ( http://richardhserlin.blogspot.com/2016/09/ai-and-krugmans-hot-dogs.html ), which is much more complete and polished than my comments, I think you'll see I've covered your points, and why I think they haven't been enough to stop a plummeting in income and employment security for low-skilled workers over the last two generations. And, why there is a substantial probability that AI and robotics will be catastrophic to the employment and wages of the unskilled over the next generation or two. But, I'd like to note some specifics here. You write: "The easiest way to think about this is to assume just one sector, so there’s nowhere for the displaced labour to go. Since production functions can be quite dry, perhaps a parable might help… ...Now there’s a technological innovation— firms come up with better netting. They can now catch the same amount of fish with less labour. The innovation is “labour saving” in that sense, but does it create unemployment? No. Firms use it to catch more fish. And because the marginal productivity of labour is raised, wages go up too, so there’s someone who can afford to buy them." As I noted in my post, there are possible problems with this. One is, if there are more than two products, say, you can hit inelasticities of demand. People can and will only eat so much fish. The price of fish can plummet, and so if the workers only have the skills to produce fish, and it's too expensive and/or difficult to obtain new skills, then they will be forced to accept plummeting wages. And the wage can easily drop below subsistence. Now, you may say, at least they will be able to eat fish, which would be as cheap as their wages, but: (1) Having fish, but nothing else makes for a short harsh life, as you don't have a home, medical care,… (2) Even adequate fish might not be affordable, as low-skilled labor is not the only input necessary to get fish. You also need relatively rare and expensive high-skilled labor, and raw materials to make the boats, refrigeration, radar, etc., to run and manage the enterprise. And so again we see the problem. If robots and AI's can now do 90% of the unskilled work, so that you would need 10% as many low-skilled humans supplied to keep the market wage the same, you can't just say ok we'll produce and eat 10 times as much fish. There are bottlenecks in high-skilled workers, raw materials, and other capital. And there is an inelasticity of demand. The people with money will shift to other products with their increased real income, and those will tend to be higher prestige goods, that may tend to require a greater percentage of skilled labor, not lesser. Supply of low-skilled labor may go up 10-fold or more, with the influx from Robotia and the AI Republic, but demand will not keep pace, and so the market wage will plunge. You acknowledge, "That’s consistent with a bit more substitutability- but also with many other explanations. For example, that US labour has been substituted not with machines but with Chinese labour" So this is key. If it can happen for low-skilled Chinese labor, then it can happen when robots and AI's get equivalent abilities to low-skilled Chinese laborers, and perhaps at a far lower wage than even they have. And with much higher quality and reliability. So, this is the key, how good will machines get at substituting for low-skilled human labor (higher skilled too, but from my study, low-skilled is the far bigger employment threat over the next 10 - 30 years). You write, "Perhaps in the distant future robots might displace large swathes of human labour. But unless there are rapid advances in medicine or time travel, I fear I won’t be there to see it…" But based on the age implied by your CV, and your photo, you should have at least 40 years. I'm stunned you could be as confident as you sound about how good – or actually not that good – AI and robotics will get over the next 40 years. Have you studied this technology extensively to be as confident as you sound? I have read thousands of pages from top experts, including AI textbooks. My opinion is that there is a very substantial probability that AI's and Robots will substitute for the vast majority of low-skilled human labor over the next 40 years. And, in fact, I think, there is a significant chance that substitution will be wide scale as soon as 10 years from now, with a far greater affect than that of Chinese labor. So, what evidence can I provide for this from my thousands of pages of reading and study over the last few years? A lot is in this post, which was in Mark Thoma's links: http://richardhserlin.blogspot.com/2015/11/robotai-revolution-decimating.html But I'll add something here. There are five major methods of machine learning (which basically is artificial intelligence), and all five can be powerfully combined: (1) Statistical modeling and methods, (2) Symbolic logic, deduction and induction, (3) Analogy (4) Neural networks, (5) Evolutionary learning, where algorithms compete for the highest utility score, and mutate, and may even reproduce sexually, mixing parts of the algorithm of each parent. Now, I'd like to focus here on (2) and (3), as our human brains use all five of these methods also to create intelligent thought, either implicitly or explicitly. Consider the computer driven car. When will we have reliable effective computer driven cars, as safe as a human, as fast as a human, as reliable and competent, as inexpensive as a human driver – or much more so for all of these things? What single group of people would know best the answer to this? The top experts working on it, or in related areas. And who are the best people who fit this bill? People who work at companies on projects to develop AI driving commercially; ultra-smart, ultra-educated specialists who have worked massive hours on this, lived it, for years. And what are they saying, where it really counts, with their money? And when their mouth being widely off can cost enormous money to their company, and personally to their career. Key companies are spending billions, and they would not do this if success were a maybe, maybe, it will happen in 80, 100 years. We all know how powerful the time value depreciates far future money at the very high discount rate you would apply if you thought this was very unlikely and risky. And yet, these companies are spending billions, tens of billions jointly, per year, and making projections for commercially available, affordable, mostly or completely autonomous cars in 5-20 years. Many things that could be cited to show this, but given time and space, I'll just start you out with this one: http://www.motherjones.com/kevin-drum/2016/08/heres-how-driverless-cars-will-happen Now let's use, (2) Symbolic logic, deduction and induction, and (3) Analogy and categorization. If an AI can drive a car, on dense, unpredictable, urban roads, faster, better, and cheaper, than a human, with the incredible sensory ability and judgement, and flexible thinking, that takes, then those same skills are basically what it takes to do almost any manual labor. It's very little stretch to then have a robot navigate a fast food restaurant, a home as a housekeeper, a yard as a landscaper, a grocery store as a stocker, and to watch and identify correctly what shoppers put in their carts, so no need for a human checker, … And as far as the dexterity of human hands, we're not that far from that now. Now, there's far more evidence and logic than this that makes me think that it could be within 10-30 years before most low-skilled human labor is substituted for, but as this is already the longest comment in history, I'll leave it at this. Please feel free to let me know if you'd like me to provide more.
Toggle Commented Oct 12, 2016 on Links for 10-11-16 at Economist's View
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From the New York Times today: "Donald J. Trump attacked the Federal Reserve on Monday night before the largest audience he has yet addressed, telling the millions of people watching the first presidential debate that the nation’s central bank is acting as an arm of the Democratic Party at the expense of the economy. It is an extraordinary accusation, backed by no evidence" At: http://www.nytimes.com/2016/09...®ion=top-news&WT.nav=top-news Look at the lack of "He said, She said" here, instead, conveying important well established facts so as not to mislead. It took a lot, an astounding amount, but mainstream journalism is finally starting to really care about conveying important news in an accurate and *nonmisleading* way. They're finally starting to realize that a definition of telling the truth that doesn't include *nonmisleading* has little meaning, and is profoundly harmful in a democracy.
Toggle Commented Sep 28, 2016 on Links for 09-27-16 at Economist's View
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The VoxEU article on robots in the new links refers to this paper, which concludes much less of a threat to automation than Frey and Osborne: Arntz, M, T Gregory and U Zierahn (2016) “The risk of automation for jobs in OECD countries: A comparative analysis”, OECD Social, Employment and Migration Working Papers, No 189, OECD Publishing, Paris. I don't know when I will have time for another big post, and lots of learning now, a lot of good new material, but I don't agree with this paper at all. You really need more qualitative analysis here. I know people love "objective", but that doesn't mean your "objective" measures are not horribly uncorrelated with what you care about, and that's the case in this paper. The measures and the formulaic way they're used are really bad for predicting the reach of these technologies over the next generation. "Objective" does not mean accurate at all. I could give my grades based on height. It would be super "objective", and completely uncorrelated with what I care about estimating, mastery of the material. Many more qualitative, less "objective" measures, would be ridiculously more accurate.
Toggle Commented Sep 22, 2016 on Links for 09-21-16 at Economist's View
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Please let Romer finally win the Nobel Prize.
Toggle Commented Sep 14, 2016 on Links for 09-14-16 at Economist's View
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"Macro models now use incredible assumptions to reach absurd conclusions." -- Romer The problem is not with the conclusions within the models, but the often ridiculously overliteral conclusions from those models to the real world.
Toggle Commented Sep 14, 2016 on Links for 09-14-16 at Economist's View
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"macroeconomic pseudoscience" -- Paul Romer Powerful words, from someone I've always been very impressed with.
Toggle Commented Sep 14, 2016 on Links for 09-14-16 at Economist's View
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I've been thinking that there are a lot of issues with the $15/hour minimum wage, but one is, would this be like a very large subsidy to R&D in AI and robotics. This might really boost the spending on R&D and investment in these technologies. It may really make a difference in the rate of advance. Something to think about. Some very useful economics would be to try to estimate the effect -- Dissertation idea #478 I'll never have time for.
Toggle Commented Sep 13, 2016 on Links for 09-13-16 at Economist's View
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If someones market wage dropped below $1/hour in the US, which it definitely could in the next 20-50 years for many without a college, you're homeless, and the homeless don't have a very long life expectancy. Plus, you're just unemployed with anything less than the current minimum wage, which AI's and robots may easily be able to go under for most low-skilled jobs in the next 10-50 years.
Toggle Commented Sep 13, 2016 on Links for 09-13-16 at Economist's View
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I mean the first place to see that this post is unthinking and knee-jerk is that it's irrelevant to the technology. What he says rules out mass unemployment no matter what the technology. We could have robots capable of doing everything any human in history has ever done for pennies an hour, doesn't matter; no matter what the technology, Branko's argument is, It's never happened yet in human history,... Over the long run, we find new needs and jobs,... You can see how unthinking that is when he doesn't even think about that his arguments are supposed to hold for any technology, even one that could do anything at all a human could do for one cent per hour. He doesn't even consider how good these AI's could get; none of that matters to him, Never in human history,..., We find new needs and jobs,...
Toggle Commented Sep 13, 2016 on Links for 09-13-16 at Economist's View
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The Branko post was very unthinking and inexpert, and only "members" can comment. So, I'll leave some comments here -- This kind of unthinking, inexpert,knee-jerk reaction is irritating: First, the people who talk about mass unemployment are not all unscientific and anthropomorphic. Many are top experts in these technologies who really understand the potential. Next, everything you've said with such confidence about how this is not a danger of massive unemployment to humans over the long run, you could have said about horses. For thousands of years of technological advance we never had massive horse unemployment. The number of horse workers just kept rising. But then, suddenly, about 100 years ago new technology did eliminate 99+% of horse jobs, permanently. What was the difference between horses and humans? With horses, the machines could do so much the horses could do, and far better and/or cheaper, that it was not possible to find enough alternative uses of high enough value for their market wage not to drop below subsistence without a 99+% drop in the supply of horses. With humans, there have always been too many alternative uses because the machines just have always still fell very short in many important things humans could still do, capabilities they have. But now, take low skilled humans. These AI’s and robots are very different. What is it, of pecuniary market value, that low skilled humans can do that these AI’s and robots may not be able to do in 10-50 years? There may be very very little, and this could easily plummet the market wage necessary to employ all unskilled humans, or even the least productive half of them, to well below the poverty, or even subsistence, level. I don't think you realize, or have thought about, how good these robots may, with significant probability, get over the next 30 years at all basic human movement and vision, at all, or almost all manual labor (and low-skilled cognitive labor as well), and at less than the cost of paying a human even minimum wage, or far less. Suppose at a grocery store cameras watch everything shoppers put in their baskets, and know what it is; the cart is mechanized and follows you, the cameras also recognize your face and have your payment info on file, dexterous robots can do the vast majority of stocking and unloading,… We are not at all far from most of this even today, and going the rest of the way looks not that hard at all in the next 30 years, from what I've learned of this technology after thousands of pages of reading and study. Then, about 90% of the grocery store jobs are gone. Where are those 90% going to be redeployed? They're low-skilled laborers, where they can be redeployed are similar places where robots can also do those kinds of manual jobs, fast food, manufacturing, waiting tables,… And, as we've seen, no, people are not willing to pay much more, in money and time, for the human touch, to be able to chat with the checker, or teller, or waiter. They'd rather have more badly needed time and money to spend with their own families and friends. These are not just clever ideas in one industry, so people go to another. These smart machines may start replacing whole classes of skill in every industry, just as was done for almost every skill a horse had. The same may be done for unskilled humans. With substantial probability the AI may get that good over the next generation. You could say, ok, the economy would expand to have just 10 times the production to utilize all these unemployed low skilled laborers, but you hit the bottleneck of lack of high-skilled laborers to do this; the high productivity methods are largely L-shaped; they require a certain proportion of high-skilled workers to low-skilled workers, and greatly increasing the proportion of high-skilled to low-skilled workers in the world would require a profound increase in governmental human capital investment, which may not happen for a very long time with the power of the right to block. In addition, you hit a lot of inelasticities of demand. Those who do still have jobs and money can only eat so much,… And costly raw materials can also become bottlenecks. So, this is not so easy to dismiss with, in the past,… We actually did in the past have to increase educational levels and skills to prevent mass unemployment with past technological advance. But, (1) Government rose to the challenge. We didn't have such a dominant and billionaire powered, government always bad, pure free market always good, right wing. And (2) The societal level of education and skill necessary with the kinds of robots and AI's we're probably going to see will be very high indeed, a very high bar to clear. It will take an incredible increase in human capital investment, from prenatal to college and beyond. Again, sadly, this is probably not going to happen anytime soon.
Toggle Commented Sep 13, 2016 on Links for 09-13-16 at Economist's View
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And yes, there's more. Next, I think there's something important to note with regard to your shipping containerization example. This caused a huge cut in the shipping jobs that existed at the time. But, these workers moved to other jobs, many still in shipping but different shipping jobs. So, all's well that ends well. Except that with the kinds of robots, machines, and AI's we may see in the future, it won't be just a clever idea that eliminates many specific jobs in a specific business, so demand increases in other businesses and workers move there, or to different jobs in the same business. It will, instead, be whole classes of work eliminated. A whole class of work, or skill, or ability – say dexterous movement and sorting with good visual recognition – will be eliminated from pretty much *every* business. It's *whole skills* that will be eliminated from employment by these new robots and AI's, across every business, not some specific jobs that will be eliminated in a specific business, so I'll take my skillset elsewhere. Your skillset may no longer be needed anywhere. It may be replaced everywhere, or replaced in 90% of businesses. And again, there are problems with, well, then production will just increase 10-fold to sop up all those low-skilled workers. There are very serious bottlenecks in high-skilled workers and raw materials, and there are inelasticities of demand, at least for certain types of products (and the other types may bottleneck with high-skilled labor and raw materials).
Toggle Commented Sep 12, 2016 on Links for 09-12-16 at Economist's View
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