How will AI affect inequality?

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?

JDN 2457451
I briefly discussed this topic before, but I thought it deserved a little more depth. Also, the SF author in me really likes writing this sort of post where I get to speculate about futures that are utopian, dystopian, or (most likely) somewhere in between.

The fear is quite widespread, but how realistic is it? Will robots in fact take all our jobs?

Most economists do not think so. Robert Solow famously quipped, “You can see the computer age everywhere but in the productivity statistics.” (It never quite seemed to occur to him that this might be a flaw in the way we measure productivity statistics.)

By the usual measure of labor productivity, robots do not appear to have had a large impact. Indeed, their impact appears to have been smaller than almost any other major technological innovation.

Using BLS data (which was formatted badly and thus a pain to clean, by the way—albeit not as bad as the World Bank data I used on my master’s thesis, which was awful), I made this graph of the growth rate of labor productivity as usually measured:

Productivity_growth

The fluctuations are really jagged due to measurement errors, so I also made an annually smoothed version:

Productivity_growth_smooth

Based on this standard measure, productivity has grown more or less steadily during my lifetime, fluctuating with the business cycle around a value of about 3.5% per year (3.4 log points). If anything, the growth rate seems to be slowing down; in recent years it’s been around 1.5% (1.5 lp).

This was clearly the time during which robots became ubiquitous—autonomous robots did not emerge until the 1970s and 1980s, and robots became widespread in factories in the 1980s. Then there’s the fact that computing power has been doubling every 1.5 years during this period, which is an annual growth rate of 59% (46 lp). So why hasn’t productivity grown at anywhere near that rate?

I think the main problem is that we’re measuring productivity all wrong. We measure it in terms of money instead of in terms of services. Yes, we try to correct for inflation; but we fail to account for the fact that computers have allowed us to perform literally billions of services every day that could not have been performed without them. You can’t adjust that away by plugging into the CPI or the GDP deflator.

Think about it: Your computer provides you the services of all the following:

  1. A decent typesetter and layout artist
  2. A truly spectacular computer (remember, that used to be a profession!)
  3. A highly skilled statistician (who takes no initiative—you must tell her what calculations to do)
  4. A painting studio
  5. A photographer
  6. A video camera operator
  7. A professional orchestra of the highest quality
  8. A decent audio recording studio
  9. Thousands of books, articles, and textbooks
  10. Ideal seats at every sports stadium in the world

And that’s not even counting things like social media and video games that can’t even be readily compared to services that were provided before computers.

If you added up the value of all of those jobs, the amount you would have had to pay in order to hire all those people to do all those things for you before computers existed, your computer easily provides you with at least $1 million in professional services every year. Put another way, your computer has taken jobs that would have provided $1 million in wages. You do the work of a hundred people with the help of your computer.

This isn’t counted in our productivity statistics precisely because it’s so efficient. If we still had to pay that much for all these services, it would be included in our GDP and then our GDP per worker would properly reflect all this work that is getting done. But then… whom would we be paying? And how would we have enough to pay that? Capitalism isn’t actually set up to handle this sort of dramatic increase in productivity—no system is, really—and thus the market price for work has almost no real relation to the productive capacity of the technology that makes that work possible.

Instead it has to do with scarcity of work—if you are the only one in the world who can do something (e.g. write Harry Potter books), you can make an awful lot of money doing that thing, while something that is far more important but can be done by almost anyone (e.g. feed babies) will pay nothing or next to nothing. At best we could say it has to do with marginal productivity, but marginal in the sense of your additional contribution over and above what everyone else could already do—not in the sense of the value actually provided by the work that you are doing. Anyone who thinks that markets automatically reward hard work or “pay you what you’re worth” clearly does not understand how markets function in the real world.

So, let’s ask again: Will robots take our jobs?

Well, they’ve already taken many jobs already. There isn’t even a clear high-skill/low-skill dichotomy here; robots are just as likely to make pharmacists obsolete as they are truck drivers, just as likely to replace surgeons as they are cashiers.

Labor force participation is declining, though slowly:

Labor_force_participation

Yet I think this also underestimates the effect of technology. As David Graeber points out, most of the new jobs we’ve been creating seem to be for lack of a better term bullshit jobs—jobs that really don’t seem like they need to be done, other than to provide people with something to do so that we can justify paying them salaries.

As he puts it:

Again, an objective measure is hard to find, but one easy way to get a sense is to ask: what would happen were this entire class of people to simply disappear? Say what you like about nurses, garbage collectors, or mechanics, it’s obvious that were they to vanish in a puff of smoke, the results would be immediate and catastrophic. A world without teachers or dock-workers would soon be in trouble, and even one without science fiction writers or ska musicians would clearly be a lesser place. It’s not entirely clear how humanity would suffer were all private equity CEOs, lobbyists, PR researchers, actuaries, telemarketers, bailiffs or legal consultants to similarly vanish. (Many suspect it might markedly improve.)

The paragon of all bullshit jobs is sales. Sales is a job that simply should not exist. If something is worth buying, you should be able to present it to the market and people should choose to buy it. If there are many choices for a given product, maybe we could have some sort of independent product rating agencies that decide which ones are the best. But sales means trying to convince people to buy your product—you have an absolutely overwhelming conflict of interest that makes your statements to customers so utterly unreliable that they are literally not even information anymore. The vast majority of advertising, marketing, and sales is thus, in a fundamental sense, literally noise. Sales contributes absolutely nothing to our economy, and because we spend so much effort on it and advertising occupies so much of our time and attention, takes a great deal away. But sales is one of our most steadily growing labor sectors; once we figure out how to make things without people, we employ the people in trying to convince customers to buy the new things we’ve made. Sales is also absolutely miserable for many of the people who do it, as I know from personal experience in two different sales jobs that I had to quit before the end of the first week.

Fortunately we have not yet reached the point where sales is the fastest growing labor sector. Currently the fastest-growing jobs fall into three categories: Medicine, green energy, and of course computers—but actually mostly medicine. Yet even this is unlikely to last; one of the easiest ways to reduce medical costs would be to replace more and more medical staff with automated systems. A nursing robot may not be quite as pleasant as a real professional nurse—but if by switching to robots the hospital can save several million dollars a year, they’re quite likely to do so.

Certain tasks are harder to automate than others—particularly anything requiring creativity and originality is very hard to replace, which is why I believe that in the 2050s or so there will be a Revenge of the Humanities Majors as all the supposedly so stable and forward-thinking STEM jobs disappear and the only jobs that are left are for artists, authors, musicians, game designers and graphic designers. (Also, by that point, very likely holographic designers, VR game designers, and perhaps even neurostim artists.) Being good at math won’t mean anything anymore—frankly it probably shouldn’t right now. No human being, not even great mathematical savants, is anywhere near as good at arithmetic as a pocket calculator. There will still be a place for scientists and mathematicians, but it will be the creative aspects of science and math that persist—design of experiments, development of new theories, mathematical intuition to develop new concepts. The grunt work of cleaning data and churning through statistical models will be fully automated.

Most economists appear to believe that we will continue to find tasks for human beings to perform, and this improved productivity will simply raise our overall standard of living. As any ECON 101 textbook will tell you, “scarcity is a fundamental fact of the universe, because human needs are unlimited and resources are finite.”

In fact, neither of those claims are true. Human needs are not unlimited; indeed, on Maslow’s hierarchy of needs First World countries have essentially reached the point where we could provide the entire population with the whole pyramid, guaranteed, all the time—if we were willing and able to fundamentally reform our economic system.

Resources are not even finite; what constitutes a “resource” depends on technology, as does how accessible or available any given source of resources will be. When we were hunter-gatherers, our only resources were the plants and animals around us. Agriculture turned seeds and arable land into a vital resource. Whale oil used to be a major scarce resource, until we found ways to use petroleum. Petroleum in turn is becoming increasingly irrelevant (and cheap) as solar and wind power mature. Soon the waters of the oceans themselves will be our power source as we refine the deuterium for fusion. Eventually we’ll find we need something for interstellar travel that we used to throw away as garbage (perhaps it will in fact be dilithium!) I suppose that if the universe is finite or if FTL is impossible, we will be bound by what is available in the cosmic horizon… but even that is not finite, as the universe continues to expand! If the universe is open (as it probably is) and one day we can harness the dark energy that seethes through the ever-expanding vacuum, our total energy consumption can grow without bound just as the universe does. Perhaps we could even stave off the heat death of the universe this way—we after all have billions of years to figure out how.

If scarcity were indeed this fundamental law that we could rely on, then more jobs would always continue to emerge, producing whatever is next on the list of needs ordered by marginal utility. Life would always get better, but there would always be more work to be done. But in fact, we are basically already at the point where our needs are satiated; we continue to try to make more not because there isn’t enough stuff, but because nobody will let us have it unless we do enough work to convince them that we deserve it.

We could continue on this route, making more and more bullshit jobs, pretending that this is work that needs done so that we don’t have to adjust our moral framework which requires that people be constantly working for money in order to deserve to live. It’s quite likely in fact that we will, at least for the foreseeable future. In this future, robots will not take our jobs, because we’ll make up excuses to create more.

But that future is more on the dystopian end, in my opinion; there is another way, a better way, the world could be. As technology makes it ever easier to produce as much wealth as we need, we could learn to share that wealth. As robots take our jobs, we could get rid of the idea of jobs as something people must have in order to live. We could build a new economic system: One where we don’t ask ourselves whether children deserve to eat before we feed them, where we don’t expect adults to spend most of their waking hours pushing papers around in order to justify letting them have homes, where we don’t require students to take out loans they’ll need decades to repay before we teach them history and calculus.

This second vision is admittedly utopian, and perhaps in the worst way—perhaps there’s simply no way to make human beings actually live like this. Perhaps our brains, evolved for the all-too-real scarcity of the ancient savannah, simply are not plastic enough to live without that scarcity, and so create imaginary scarcity by whatever means they can. It is indeed hard to believe that we can make so fundamental a shift. But for a Homo erectus in 500,000 BP, the idea that our descendants would one day turn rocks into thinking machines that travel to other worlds would be pretty hard to believe too.

Will robots take our jobs? Let’s hope so.