Third, there is a misconception that highly theoretical tasks done by skilled experts will be among the last to go. But due to their theoretical nature such tasks are fairly easy represent virtually.
Actually I think he may be right, since this is basically a consequence of Moravec’s paradox.
“The main lesson of thirty-five years of AI research is that the hard problems are easy and the easy problems are hard. The mental abilities of a four-year-old that we take for granted – recognizing a face, lifting a pencil, walking across a room, answering a question – in fact solve some of the hardest engineering problems ever conceived.… As the new generation of intelligent devices appears, it will be the stock analysts and petrochemical engineers and parole board members who are in danger of being replaced by machines. The gardeners, receptionists, and cooks are secure in their jobs for decades to come. “[2]
But why might this be so?
“Encoded in the large, highly evolved sensory and motor portions of the human brain is a billion years of experience about the nature of the world and how to survive in it. The deliberate process we call reasoning is, I believe, the thinnest veneer of human thought, effective only because it is supported by this much older and much powerful, though usually unconscious, sensorimotor knowledge. We are all prodigious olympians in perceptual and motor areas, so good that we make the difficult look easy. Abstract thought, though, is a new trick, perhaps less than 100 thousand years old. We have not yet mastered it. It is not all that intrinsically difficult; it just seems so when we do it.”[4]
I agree with the theory, but not with the practical conclusions. Yes, we invented automatic provers before automatic gardeners, because there are were some harder problems involved. But at this point they both seem with reach—for example, take a look at progress in self-driving cars just over the last 6 years. Driving is very similar to other natural problems. Cooking example is just silly in the first place. Well, maybe creative cooking will be harder, but cooking by emulation should be really easy for machines.
… not to mention that a lot of food is being produced by machines, or at least in a heavily automated environment. I’ve visited food factories, I don’t remember seeing many cooks. Even home cooking has been automated to a certain degree.
All these labor saving devices, even factories, are integrated by humans. While the productivity per worker skyrockets (fewer workers needed per X units of output), there is no factory that runs without people who do generally very easy tasks that are very difficult to automate.
The summer after high school I worked in a spray bottle factory. Yes, we made the spray nozzles like come on a bottle of windex. My job was to keep the bins full of the little parts that fed into the machine that assembled them. I also helped unload the boxes of the parts from the carts and stacked them near the bin where they needed to go. Someone else somewhere had a job to handle the “raw” plastic for machine that melted and molded the parts I needed. Someone else put the different parts in different boxes sorted for the cart driver.
These tasks were of course absurdly easy for any human to do with about five minutes of training. Somehow automating all this together into a single factory chain would have presented enormous challenges though. Because the labor is so cheap I could easily imagine that factory will run the same way for the next fifty years.
I suspect the driving forces behind automating that sort of thing will ultimately be, not labor costs, but the relative slowness, messiness, and unreliability of humans.
That said, I also expect that the technology that can do those sorts of jobs more quickly, cleanly, and reliably than humans will be developed for different applications where minimally trained human labor just isn’t practical (say, automated underwater mining) and then applied to other industries once it’s gotten pretty good.
Maybe but its still easily 50 years away. People are “messy” but they are so cheap and you need so few of them—there is no capital tied up in them at all its just a month-to-month expense. Even if you lease equipment you are still paying for the cost of the capital tied up in it. The diminishing returns for automating such a small cost will ensure its continuity for quite some time I think.
Predictions in years are less and less meaningful to me as I go along. I’d give .6 confidence that we’re no more than 5 tech-generations away from being able to build a fully automated mining facility (just to pick a concrete example), and no more than 3 generations from there to being able to build one in a way that would be cost-effective (given current-day labor costs and raw materials prices) for at least some application… perhaps underwater mining of rare earths.
I also expect that along the way, selected raw materials prices will increase enough (in inflation-adjusted currency) that using current-day prices is absurdly conservative. Then again, I also expect that along the way we’ll see several failures of such equipment that cause as much as half a commute-year (current-day) of environmental damage, which might set the whole project back by decades. So, who knows?
A commute-year, incidentally, is a measure of risk (e.g., death and property/environmental damage) equal to that caused by people commuting to and from their jobs in a given year. My guess is that half a commute-year is typically more than enough to cause the majority of Americans to insist that a new project is way too dangerous to even consider. (Of course, that doesn’t apply to the project of actually commuting to work.)
Actually I think he may be right, since this is basically a consequence of Moravec’s paradox.
But why might this be so?
I agree with the theory, but not with the practical conclusions. Yes, we invented automatic provers before automatic gardeners, because there are were some harder problems involved. But at this point they both seem with reach—for example, take a look at progress in self-driving cars just over the last 6 years. Driving is very similar to other natural problems. Cooking example is just silly in the first place. Well, maybe creative cooking will be harder, but cooking by emulation should be really easy for machines.
… not to mention that a lot of food is being produced by machines, or at least in a heavily automated environment. I’ve visited food factories, I don’t remember seeing many cooks. Even home cooking has been automated to a certain degree.
All these labor saving devices, even factories, are integrated by humans. While the productivity per worker skyrockets (fewer workers needed per X units of output), there is no factory that runs without people who do generally very easy tasks that are very difficult to automate.
The summer after high school I worked in a spray bottle factory. Yes, we made the spray nozzles like come on a bottle of windex. My job was to keep the bins full of the little parts that fed into the machine that assembled them. I also helped unload the boxes of the parts from the carts and stacked them near the bin where they needed to go. Someone else somewhere had a job to handle the “raw” plastic for machine that melted and molded the parts I needed. Someone else put the different parts in different boxes sorted for the cart driver.
These tasks were of course absurdly easy for any human to do with about five minutes of training. Somehow automating all this together into a single factory chain would have presented enormous challenges though. Because the labor is so cheap I could easily imagine that factory will run the same way for the next fifty years.
I suspect the driving forces behind automating that sort of thing will ultimately be, not labor costs, but the relative slowness, messiness, and unreliability of humans.
That said, I also expect that the technology that can do those sorts of jobs more quickly, cleanly, and reliably than humans will be developed for different applications where minimally trained human labor just isn’t practical (say, automated underwater mining) and then applied to other industries once it’s gotten pretty good.
Maybe but its still easily 50 years away. People are “messy” but they are so cheap and you need so few of them—there is no capital tied up in them at all its just a month-to-month expense. Even if you lease equipment you are still paying for the cost of the capital tied up in it. The diminishing returns for automating such a small cost will ensure its continuity for quite some time I think.
Predictions in years are less and less meaningful to me as I go along. I’d give .6 confidence that we’re no more than 5 tech-generations away from being able to build a fully automated mining facility (just to pick a concrete example), and no more than 3 generations from there to being able to build one in a way that would be cost-effective (given current-day labor costs and raw materials prices) for at least some application… perhaps underwater mining of rare earths.
I also expect that along the way, selected raw materials prices will increase enough (in inflation-adjusted currency) that using current-day prices is absurdly conservative. Then again, I also expect that along the way we’ll see several failures of such equipment that cause as much as half a commute-year (current-day) of environmental damage, which might set the whole project back by decades. So, who knows?
A commute-year, incidentally, is a measure of risk (e.g., death and property/environmental damage) equal to that caused by people commuting to and from their jobs in a given year. My guess is that half a commute-year is typically more than enough to cause the majority of Americans to insist that a new project is way too dangerous to even consider. (Of course, that doesn’t apply to the project of actually commuting to work.)