~1983 I read two articles that inspired me to change my career. One was by Ted Nelson on hypertext publishing, and the other by Doug Lenat on artificial intelligence. So I quit my U. of Chicago physics Ph.D. program and headed to Silicon Valley, for a job doing AI at Lockheed, and a hobby doing hypertext with Nelson’s Xanadu group.
I don't think natural language technology is as advanced as it seems. Machines cannot read and have no understanding of the text given to them. The advances reported, like IBM Watson winning jeopardy, spam detection, irony detection, the detection of tone of a document etc. is based on relatively simple statistical or probabilistic processes trained on very large numbers of documents. It is impressive, but the experience of the end user is a useful illusion of intelligence. It seems much more impressive than it is. You have to look under the hood to be underwhelmed.
Many big AI problems could turn out to be AI-complete (like visual perception, for instance). If so, we'd need to solve the problem of general AI before we have machines capable of automating a lot of occupations.
I predict that by 2044, employment in what were the top 15 industries in 2012 will be reduced by more than 50 percent. The biggest percentage losers I expect to be tractor trailer drivers, cashiers, and material movers (such as loading dock workers). I see all three declining by about 90 percent.
But I don't think the drops will be particularly noticeable for another ~10 years.
Do you suppose that using the federal government as a battering ram to reduce health care spending will improve current rates of life expectancy increase or not?
I think if U.S. spending on health care was increasing life expectancy at birth by 6 months per year, or even better one year per year, people would be a lot happier with the increasing health care expenditures.
It's weird that public sentiment simultaneously holds that mass unemployment due to automation is a serious danger and that we need to reduce spending on health care, one of the most labor intensive of industries.
Here are some of the most common jobs in the U.S. in 2012, with the number of people, in millions:
#1 Retail salespeople = 4.2 m
#2 Cashiers = 3.4 m#4 Fast food preparation and service = 2.7 m#9 Janitors = 2.1 m#12 Bookkeeping, accounting = 1.8 m#14 Tractor trailer drivers = 1.6 m#15 Elementary school teachers = 1.5 m
Robin of 1984 might have predicted that many of them would be gone due to AI in 2014. But they're obviously not. But is this time different? What are peoples' predictions for what the number of people in the U.S. employed in those sectors in 2024, 2034, and 2044?
I've already typed my predictions into a blog post on my blog. I'll hit the publish when some folks (hopefully especially Robin) have made predictions here.
P.S. A potential format for the predictions would be the value in 2012 in millions (just a repeat of the numbers above), followed by the predicted values in 2024, 2034, and 2044. For example, using hypothetical numbers only:
I don't see any bottlenecks but we are currently in a steady fall. Labor's share of income has been falling around the world: http://www.economist.com/ne...
And it can't be blamed on offshoring since it is also happening in places like Mexico and China.
I think it is true that we are a very long way from automating all professions. But we can automate a very significant percentage of jobs (>20% for example) while not automating a majority of professions.
Professional drivers alone are between 5 and 6 million jobs in the US. But it's just one profession. Only a handful of professions automated like that could result in an unemployment rate higher than during the great depression.
I worked on a project once for a warehouse management software company, which sold software and hardware to make human laborers more effective. Their competitive advantage was that they were very good at simulation and optimization; they could take actual order data that the warehouse had received over the last six months and say "this is how we would have arranged your flow, and it would have saved you 17%" whereas the robot companies would say "we think it'll save you 20%, maybe," and the non-engineers who didn't get the toy joy out of buying new robots would price the risk at much more than 3% and go with the simulation company.
The thing I found fascinating about it, though, is that warehouse workers had three relevant organs: eyes, hands, and feet. It's very difficult to replace the eyes and hands--humans are much better at grabbing one box of pens from the big box of pens than a robot--but it's not as difficult to replace the feet (these are the Kiva robots that pick up and move shelves to bring them to the picker, and they were bought by Amazon around the time I was working on this project).
Turns out, about 80% of a picker's time is spent walking. So as the picker job transitions from walking through lines to fill boxes to standing in place and filling boxes, about 80% of picker jobs go to the Kiva robots. It seems to me that this is the visible low-tech version of the general human-computer synthesis argument; as computers make humans better at their jobs by reducing the tedious work, we need less humans to do those jobs (both because there's less tedious work to do, *and* we move from the best 10 pickers to the best 2 pickers, who probably have higher average productivity).
(It also makes it obvious how a drastic local transition--one warehouse switches and fires 80% of its picker workforce--can become a smooth global transition, as the warehouses switch over one by one.)
You have any data to support this claim? Or even particular places and time periods you claim these bottleneck bursts happened during?For example, chart 17 here of US farming employment in the 19th century shows a pretty steady fall - no bursts. http://www.bls.gov/opub/mlr...
I think we have seen exactly that. The jobs that were fundamentally about the application of physical force all got automated away fairly quickly. So did most of the agricultural jobs, which had largely been bottlenecked by harvesting, leading to dust bowls and socially disruptive flooding of the cities, and massive changes in the nature of government to accommodate.
It seems to me, Robin, that you look at history and see little abrupt technological change, while I see lots of abrupt technological change, very locally, and political resistance spreading it out and mitigating its impact. People who say that something must be done are saying that such political solutions will again be needed, as they have been in the past, not that nothing will be done so DOOM.
This discussion is meaningless without agreeing on the defintion of "work" or "automation". Surely automation has replaced many, many jobs in the past, I'd even go as far to say a majority of jobs that existed in 1900 have been replaced by automation. By that standard "the machines" have already taken our jobs. But so many new jobs have been invented that we aren't all unemployed. That trend may continue for a while even after machines become capable enough to do most of today's jobs. If you're talking about an era when automation proceeds faster than the creation of new jobs (and should we also compensate for working hours and percentage of lifetime spent in employment?) over a long period then yes, that indeed won't happen anytime soon, but people should be clear about what they mean exactly in this discussion.
I’ve since learned that we’ve seen “booms” like the one I was caught up in then every few decades for centuries. -
Faster than every few decades. I'd say it comes about once every ten years now, usually during an economic downturn with high unemployment. I remember Jeremy Rifkin had the misfortune to pen The End of Work about this topic in 1995, just as things were getting better in terms of employment, growth, and wages across the board in the US.
Yes machines are vastly better than they were before, but they must get far more vastly better to displace most human workers. -
I could see them replacing many of the existing jobs today eventually (key word being "eventually"), although I can't see them really displacing human work in general* - especially since the definition of "work" can change. For more than half of free Americans before 1860, "work" meant "farm/small business/professional/artisan/etc". We live in an "employee" society now, but it may not stay that way forever.
Plus, it seems like you could always figure out ways to put humans in a managerial/supervisory role over ever increasing layers of machinery underneath their control.
Seems to work in other places
I don't think natural language technology is as advanced as it seems. Machines cannot read and have no understanding of the text given to them. The advances reported, like IBM Watson winning jeopardy, spam detection, irony detection, the detection of tone of a document etc. is based on relatively simple statistical or probabilistic processes trained on very large numbers of documents. It is impressive, but the experience of the end user is a useful illusion of intelligence. It seems much more impressive than it is. You have to look under the hood to be underwhelmed.
Many big AI problems could turn out to be AI-complete (like visual perception, for instance). If so, we'd need to solve the problem of general AI before we have machines capable of automating a lot of occupations.
Hi,
I made my predictions:
http://markbahner.typepad.c...
I predict that by 2044, employment in what were the top 15 industries in 2012 will be reduced by more than 50 percent. The biggest percentage losers I expect to be tractor trailer drivers, cashiers, and material movers (such as loading dock workers). I see all three declining by about 90 percent.
But I don't think the drops will be particularly noticeable for another ~10 years.
Ok, but here's a question for you:
Do you suppose that using the federal government as a battering ram to reduce health care spending will improve current rates of life expectancy increase or not?
I think if U.S. spending on health care was increasing life expectancy at birth by 6 months per year, or even better one year per year, people would be a lot happier with the increasing health care expenditures.
It's weird that public sentiment simultaneously holds that mass unemployment due to automation is a serious danger and that we need to reduce spending on health care, one of the most labor intensive of industries.
Hi
Here are some of the most common jobs in the U.S. in 2012, with the number of people, in millions:
#1 Retail salespeople = 4.2 m
#2 Cashiers = 3.4 m#4 Fast food preparation and service = 2.7 m#9 Janitors = 2.1 m#12 Bookkeeping, accounting = 1.8 m#14 Tractor trailer drivers = 1.6 m#15 Elementary school teachers = 1.5 m
Robin of 1984 might have predicted that many of them would be gone due to AI in 2014. But they're obviously not. But is this time different? What are peoples' predictions for what the number of people in the U.S. employed in those sectors in 2024, 2034, and 2044?
I've already typed my predictions into a blog post on my blog. I'll hit the publish when some folks (hopefully especially Robin) have made predictions here.
P.S. A potential format for the predictions would be the value in 2012 in millions (just a repeat of the numbers above), followed by the predicted values in 2024, 2034, and 2044. For example, using hypothetical numbers only:
#1 Retail salespeople = 4.2, 4.3, 4.4, 4.5.
#2 Cashiers = 3.4, 3.6, 3.5, 3.4.
I don't see any bottlenecks but we are currently in a steady fall. Labor's share of income has been falling around the world: http://www.economist.com/ne...
And it can't be blamed on offshoring since it is also happening in places like Mexico and China.
I think it is true that we are a very long way from automating all professions. But we can automate a very significant percentage of jobs (>20% for example) while not automating a majority of professions.
Professional drivers alone are between 5 and 6 million jobs in the US. But it's just one profession. Only a handful of professions automated like that could result in an unemployment rate higher than during the great depression.
Sure. But there's no reason to believe the knee of the curve happens to be near us now.
I worked on a project once for a warehouse management software company, which sold software and hardware to make human laborers more effective. Their competitive advantage was that they were very good at simulation and optimization; they could take actual order data that the warehouse had received over the last six months and say "this is how we would have arranged your flow, and it would have saved you 17%" whereas the robot companies would say "we think it'll save you 20%, maybe," and the non-engineers who didn't get the toy joy out of buying new robots would price the risk at much more than 3% and go with the simulation company.
The thing I found fascinating about it, though, is that warehouse workers had three relevant organs: eyes, hands, and feet. It's very difficult to replace the eyes and hands--humans are much better at grabbing one box of pens from the big box of pens than a robot--but it's not as difficult to replace the feet (these are the Kiva robots that pick up and move shelves to bring them to the picker, and they were bought by Amazon around the time I was working on this project).
Turns out, about 80% of a picker's time is spent walking. So as the picker job transitions from walking through lines to fill boxes to standing in place and filling boxes, about 80% of picker jobs go to the Kiva robots. It seems to me that this is the visible low-tech version of the general human-computer synthesis argument; as computers make humans better at their jobs by reducing the tedious work, we need less humans to do those jobs (both because there's less tedious work to do, *and* we move from the best 10 pickers to the best 2 pickers, who probably have higher average productivity).
(It also makes it obvious how a drastic local transition--one warehouse switches and fires 80% of its picker workforce--can become a smooth global transition, as the warehouses switch over one by one.)
You have any data to support this claim? Or even particular places and time periods you claim these bottleneck bursts happened during?For example, chart 17 here of US farming employment in the 19th century shows a pretty steady fall - no bursts. http://www.bls.gov/opub/mlr...
I think we have seen exactly that. The jobs that were fundamentally about the application of physical force all got automated away fairly quickly. So did most of the agricultural jobs, which had largely been bottlenecked by harvesting, leading to dust bowls and socially disruptive flooding of the cities, and massive changes in the nature of government to accommodate.
It seems to me, Robin, that you look at history and see little abrupt technological change, while I see lots of abrupt technological change, very locally, and political resistance spreading it out and mitigating its impact. People who say that something must be done are saying that such political solutions will again be needed, as they have been in the past, not that nothing will be done so DOOM.
This discussion is meaningless without agreeing on the defintion of "work" or "automation". Surely automation has replaced many, many jobs in the past, I'd even go as far to say a majority of jobs that existed in 1900 have been replaced by automation. By that standard "the machines" have already taken our jobs. But so many new jobs have been invented that we aren't all unemployed. That trend may continue for a while even after machines become capable enough to do most of today's jobs. If you're talking about an era when automation proceeds faster than the creation of new jobs (and should we also compensate for working hours and percentage of lifetime spent in employment?) over a long period then yes, that indeed won't happen anytime soon, but people should be clear about what they mean exactly in this discussion.
I’ve since learned that we’ve seen “booms” like the one I was caught up in then every few decades for centuries. -
Faster than every few decades. I'd say it comes about once every ten years now, usually during an economic downturn with high unemployment. I remember Jeremy Rifkin had the misfortune to pen The End of Work about this topic in 1995, just as things were getting better in terms of employment, growth, and wages across the board in the US.
Yes machines are vastly better than they were before, but they must get far more vastly better to displace most human workers. -
I could see them replacing many of the existing jobs today eventually (key word being "eventually"), although I can't see them really displacing human work in general* - especially since the definition of "work" can change. For more than half of free Americans before 1860, "work" meant "farm/small business/professional/artisan/etc". We live in an "employee" society now, but it may not stay that way forever.
Plus, it seems like you could always figure out ways to put humans in a managerial/supervisory role over ever increasing layers of machinery underneath their control.