trucking

How will AI affect inequality?

PNRJ current events, ethics, futurism, inequality, public policy , , , , , , , , , , , ,

Oct 15 JDN 2460233

Will AI make inequality worse, or better? Could it do a bit of both? Does it depend on how we use it?

This is of course an extremely big question. In some sense it is the big economic question of the 21st century. The difference between the neofeudalist cyberpunk dystopia of Neuromancer and the social democratic utopia of Star Trek just about hinges on whether AI becomes a force for higher or lower inequality.

Krugman seems quite optimistic: Based on forecasts by Goldman Sachs, AI seems poised to automate more high-paying white-collar jobs than low-paying blue-collar ones.

But, well, it should be obvious that Goldman Sachs is not an impartial observer here. They do have reasons to get their forecasts right—their customers are literally invested in those forecasts—but like anyone who immensely profits from the status quo, they also have a broader agenda of telling the world that everything is going great and there’s no need to worry or change anything.

And when I look a bit closer at their graphs, it seems pretty clear that they aren’t actually answering the right question. They estimate an “exposure to AI” coefficient (somehow; their methodology is not clearly explained and lots of it is proprietary), and if it’s between 10% and 49% they call it “complementary” while if it’s 50% or above they call it “replacement”.

But that is not how complements and substitutes work. It isn’t a question of “how much of the work can be done by machine” (whatever that means). It’s a question of whether you will still need the expert human.

It could be that the machine does 90% of the work, but you still need a human being there to tell it what to do, and that would be complementary. (Indeed, this basically is how finance works right now, and I see no reason to think it will change any time soon.) Conversely, it could be that the machine only does 20% of the work, but that was the 20% that required expert skill, and so a once comfortable high-paying job can now be replaced by low-paid temp workers. (This is more or less what’s happening at Amazon warehouses: They are basically managed by AI, but humans still do most of the actual labor, and get paid peanuts for it.)

For their category “computer and mathematical”, they call it “complementary”, and I agree: We are still going to need people who can code. We’re still going to need people who know how to multiply matrices. We’re still going to need people who understand search algorithms. Indeed, if the past is any indicator, we’re going to need more and more of those people, and they’re going to keep getting paid higher and higher salaries. Someone has to make the AI, after all.

Yet I’m not quite so sure about the “mathematical” part in many cases. We may not need people who can solve differential equations, actually: maybe a few to design the algorithms, but honestly even then, a software program with a simple finite-difference algorithm can often solve much more interesting problems than one with a full-fledged differential equation solver, because one of the dirty secrets of differential equations is that for some of the most important ones (like the Navier-Stokes Equations), we simply do not know how to solve them. Once you have enough computing power, you often can stop trying to be clever and just brute-force the damn thing.

Yet for “transportation and material movement”—that is, trucking—Goldman Sachs confidently forecasts mostly “no automation” with a bit of “complementary”. Yet this year—not at some distant point in the future, not in some sci-fi novel, this year in the actual world—the Governor of California already vetoed a bill that would have required automated trucks to have human drivers. The trucks aren’t on the roads yet—but if we already are making laws about them, they’re going to be, soon. (State legislatures are not known for their brilliant foresight or excessive long-term thinking.) And if the law doesn’t require them to have human drivers, they probably won’t; which means that hundreds of thousands of long-haul truckers will suddenly be out of work.

It’s also important to differentiate between different types of jobs that may fall under the same category or industry.

Neurosurgeons are not going anywhere, and improved robotics will only allow them to perform better, safer laparoscopic surgeries. Nor are nurses going anywhere, because some things just need an actual person physically there with the patient. But general practictioners, psychotherapists, and even radiologists are already seeing many of their tasks automated. So is “medicine” being automated or not? That depends what sort of medicine you mean. And yet it clearly means an increase in inequality, because it’s the middle-paying jobs (like GPs) that are going away, while the high-paying jobs (like neurosurgeons) and the low-paying jobs (like nurses) that remain.

Likewise, consider “legal services”, which is one of the few industries that Goldman Sachs thinks will be substantially replaced by AI. Are high-stakes trial lawyers like Sam Bernstein getting replaced? Clearly not. Nor would I expect most corporate lawyers to disappear. Human lawyers will still continue to perform at least a little bit better than AI law systems, and the rich will continue to use them, because a few million dollars for a few percentage points better odds of winning is absolutely worth it when billions of dollars are on the line. So which law services are going to get replaced by AI? First, routine legal questions, like how to renew your work visa or set up a living will—it’s already happening. Next, someone will probably decide that public defenders aren’t worth the cost and start automating the legal defenses of poor people who get accused of crimes. (And to be honest, it may not be much worse than how things currently are in the public defender system.) The advantage of such a change is that it will most likely bring court costs down—and that is desperately needed. But it may also tilt the courts even further in favor of the rich. It may also make it even harder to start a career as a lawyer, cutting off the bottom of the ladder.

Or consider “management”, which Goldman Sachs thinks will be “complementary”. Are CEOs going to get replaced by AI? No, because the CEOs are the ones making that decision. Certainly this is true for any closely-held firm: No CEO is going to fire himself. Theoretically, if shareholders and boards of directors pushed hard enough, they might be able to get a CEO of a publicly-traded corporation ousted in favor of an AI, and if the world were really made of neoclassical rational agents, that might actually happen. But in the real world, the rich have tremendous solidarity for each other (and only each other), and very few billionaires are going to take aim at other billionaires when it comes time to decide whose jobs should be replaced. Yet, there are a lot of levels of management below the CEO and board of directors, and many of those are already in the process of being replaced: Instead of relying on the expert judgment of a human manager, it’s increasingly common to develop “performance metrics”, feed them into an algorithm, and use that result to decide who gets raises and who gets fired. It all feels very “objective” and “impartial” and “scientific”—and usually ends up being both dehumanizing and ultimately not even effective at increasing profits. At some point, many corporations are going to realize that their middle managers aren’t actually making any important decisions anymore, and they’ll feed that into the algorithm, and it will tell them to fire the middle managers.

Thus, even though we think of “medicine”, “law”, and “management” as high-paying careers, the effect of AI is largely going to be to increase inequality within those industries. It isn’t the really high-paid doctors, managers, and lawyers who are going to get replaced.

I am therefore much less optimistic than Krugman about this. I do believe there are many ways that technology, including artificial intelligence, could be used to make life better for everyone, and even perhaps one day lead us into a glorious utopian future.

But I don’t see most of the people who have the authority to make important decisions for our society actually working towards such a future. They seem much more interested in maximizing their own profits or advancing narrow-minded ideologies. (Or, as most right-wing political parties do today: Advancing narrow-minded ideologies about maximizing the profits of rich people.) And if we simply continue on the track we’ve been on, our future is looking a lot more like Neuromancer than it is like Star Trek.

Will robots take our jobs? Not “if” but “when”.

PNRJ current events, futurism , , , , , , , , , , ,

Jan 5 JDN 2458853

The prospect of technological unemployment—in short, robots taking our jobs—is a very controversial one among economists.

For most of human history, technological advances have destroyed some jobs and created others, causing change, instability, conflict—but ultimately, not unemployment. Many economists believe that this trend will continue well into the 21st century.

Yet I am not so sure, ever since I read this chilling paragraph by Gregory Clark, which I first encountered in The Atlantic:

There was a type of employee at the beginning of the Industrial Revolution whose job and livelihood largely vanished in the early twentieth century. This was the horse. The population of working horses actually peaked in England long after the Industrial Revolution, in 1901, when 3.25 million were at work. Though they had been replaced by rail for long-distance haulage and by steam engines for driving machinery, they still plowed fields, hauled wagons and carriages short distances, pulled boats on the canals, toiled in the pits, and carried armies into battle. But the arrival of the internal combustion engine in the late nineteenth century rapidly displaced these workers, so that by 1924 there were fewer than two million. There was always a wage at which all these horses could have remained employed. But that wage was so low that it did not pay for their feed.

Based on the statistics, what actually seems to be happening right now is that automation is bifurcating the workforce: It’s allowing some people with advanced high-tech skills to make mind-boggling amounts of money in engineering and software development, while those who lack such skills get pushed ever further into the margins, forced to take whatever jobs they can get. This skill-biased technical change is far from a complete explanation for our rising inequality, but it’s clearly a contributing factor, and I expect it will become more important over time.

Indeed, in some sense I think the replacement of most human labor with robots is inevitable. It’s not a question of “if”, but only a question of “when”. In a thousand years—if we survive at all, and if we remain recognizable as human—we’re not going to have employment in the same sense we do today. In the best-case scenario, we’ll live in the Culture, all playing games, making art, singing songs, and writing stories while the robots do all the hard labor.

But a thousand years is a very long time; we’ll be dead, and so will our children and our grandchildren. Most of us are thus understandably a lot more concerned about what happens in say 20 or 50 years.

I’m quite certain that not all human work will be replaced within the next 20 years. In fact, I am skeptical even of the estimates that half of all work will be automated within the next 40 years, though some very qualified experts are making such estimates. A lot of jobs are safe for now.

Indeed, my job is probably pretty safe: While there has been a disturbing trend in universities toward adjunct faculty, people are definitely still going to need economists for the foreseeable future. (Indeed, if Asimov is right, behavioral economists will one day rule the galaxy.)

Creative jobs are also quite safe; it’s going to be at least a century, maybe more, before robots can seriously compete with artists, authors, or musicians. (Robot Beethoven is a publicity stunt, not a serious business plan.) Indeed, by the time robots reach that level, I think we’ll have to start treating them as people—so in that sense, people will still be doing those jobs.

Even construction work is also relatively safe—actually projected to grow faster than employment in general for the next decade. This is probably because increased construction productivity tends to lead to more construction, rather than less employment. We can pretty much always use more or bigger houses, as long as we can afford them. Really, we should be hoping for technological advances in construction, which might finally bring down our astronomical housing prices, especially here in California.

But a lot of jobs are clearly going to disappear, sooner than most people seem to grasp.

The one that worries me the most is truck drivers. Truck drivers are a huge number of people. Trucking employs over 1.5 million Americans, accounting for about 1% of all US workers. It’s one of the few remaining jobs that pays a middle-class salary with entry-level skills and doesn’t require an advanced education. It’s also culturally coded as highly masculine, which is advantageous in a world where a large number of men suffer so deeply from fragile masculinity (a major correlate of support for Donald Trump, by the way, as well as a source of a never-ending array of cringeworthy marketing) that they can’t bear to take even the most promising “pink collar” jobs.

And yet, long-haul trucking is probably not going to exist in 20 years. Short-haul and delivery trucking will probably last a bit longer, since it’s helpful to have a human being to drive around complicated city streets and carry deliveries. Automated trucks are already here, and they are just… better. While human drivers need rest, sleep, food, and bathroom breaks, rarely exceeding 11 hours of actual driving per day (which still sounds exhausting!), an automated long-haul truck can stay on the road for over 22 hours per day, even including fuel and maintenance. The capital cost of an automated truck is currently much higher than an ordinary truck, but when that changes, trucking companies aren’t going to keep around a human driver when their robots can deliver twice as fast and don’t expect to be paid wages. Automated vehicles are also safer than human drivers, which will save several thousand lives per year. For this to happen, we don’t even need truly full automation; we just need to get past our current level 3 automation and reach level 4. Prototypes of this level of automation are already under development; in about 10 years they’ll start hitting the road. The shift won’t be instantaneous; once a company has already invested in a truck and a driver, they’ll keep them around for several years. But in 20 years from now, I don’t expect to see a lot of human-driven trucks left.

I’m pleased to see that the government is taking this matter seriously, already trying to develop plans for what to do when long-haul trucks become fully robotic. I hope they can come up with a good plan in time.

Some jobs that will be automated away deserve to be automated away. I can’t shed very many tears for the loss of fast-food workers and grocery cashiers (which we can already see happening around us—been to a Taco Bell lately?); those are terrible jobs that no human being should have to do. And my only concern about automated telemarketing is that it makes telemarketing cheaper and therefore more common; I certainly am not worried about the fact that people won’t be working as telemarketers anymore.

But a lot of good jobs, even white-collar jobs, are at risk of automation. Algorithms are already performing at about the same level as human radiologists, contract reviewers, and insurance underwriters, and once they get substantially better, companies are going to have trouble justifying why they would hire a human who costs more and performs worse. Indeed, the very first job to be automated by information technology was a white-collar job: computer used to be a profession, not a machine.

Technological advancement is inherently difficult to predict: If we knew how future technology will work, we’d make it now. So any such prediction should contain large error bars: “20 years away” could mean we make a breakthrough next year, or it could stay “20 years away” for the next 50 years.

If we had a robust social safety net—a basic income, perhaps?—this would be fine. But our culture decided somewhere along the way that people only deserve to live well if they are currently performing paid services for a corporation, and as robots get better, corporations will find they don’t need so many people performing services. We could face up to this fact and use it as an opportunity for deeper reforms; but I fear that instead we’ll wait to act until the crisis is already upon us.