“Robots can’t take your job if you’re already retired.”

July 7 JDN 2458672

There is a billboard on I-405 near where I live, put up by some financial advisor company, with that slogan on it: “Robots can’t take your job if you’re already retired.”

First, let me say this: Don’t hire a financial advisor firm; you really don’t need one. 90% of actively-managed funds perform worse than simple index funds. Buy all the stocks and let them sit. You won’t be able to retire sooner because you paid someone else to do the same thing you could have done yourself.

Yet, there is some wisdom in this statement: The best answer to technological unemployment is to make it so people don’t need to be employed. As an individual, all you could really do there is try to save up and retire early. But as a society, there is a lot more we could do.

The goal should essentially to make everyone retired, or if not everyone, then whatever portion of the population has been displaced by automation. A pension for everyone sounds a lot like a basic income.

People are strangely averse to redistribution of wealth as such (perhaps because they don’t know, or don’t want to think about, how much of our existing wealth was gained by force?), so we may not want to call our basic income a basic income.

Instead, we will call it capital income. People seem astonishingly comfortable with Jeff Bezos making more income in a minute than his median employee makes in a year, as long as it’s capital income instead of “welfare” or “redistribution of wealth”.

The basic income will instead be called something like the Perpetual Dividend of the United States, the dividends each US citizen receives for being a shareholder in the United States of America. I know this kind of terminology works, because the Permanent Fund Dividend in Alaska is a successful and enormously popular basic income. Even conservatives in Alaska dare not suggest eliminating the PFD.
And in fact it could literally be capital income: While public ownership of factories generally does not go well (see: the entire history of socialism and communism), the most sensible way to raise revenue for this program would be to tax income gained by owners of robotic factories, which, even if on the books as salary or stock options or whatever, is at its core capital income. If we wanted to make that connection even more transparent, we could tax in the form of non-voting shares in corporations, so that instead of paying a conventional corporate tax, corporations simply had to pay a portion of their profits directly to the public fund.

I’m not quite sure why people are so much more uncomfortable with redistribution of wealth than they are with the staggering levels of wealth inequality that make it so obviously necessary. Maybe it’s the feeling of “robbing Peter to pay Paul”, or “running out of other people’s money”? But obviously a basic income won’t just be free money from nowhere. We would be collecting it in taxes, the same way we fund all other government spending. Even printing money would mean paying in the form of inflation (and we definitely should not print enough money to cover a whole basic income!)

I think it may simply be that people aren’t cognizant enough of the magnitude of wealth inequality. I’m hoping that my posts on the extremes of wealth and poverty might help a bit with that. The richest people on Earth make about $10 billion per year—that’s $10,000,000,000—simply for owning things. The poorest people on Earth struggle to survive on less than $500 per year—often working constantly throughout their waking hours. Even if we believe that billionaires work harder (obviously false) or contribute more to society (certainly debatable) than other people, do we really believe that some people deserve to make 20 million times as much as others? It’s one thing to think that being a successful entrepreneur should make you rich. It’s another to believe that it should make you so rich you could buy a house for every homeless person in America.
Automation is already making this inequality worse, and there is reason to think it will continue to do so. In our current system, when the owner of a corporation automates production, he then gets to claim all the output from the robots, where previously he had to pay wages to the workers—and that’s why he does the automation, because it makes him more profit. Even if overall productivity increases, the fruits of that new production always get concentrated at the top. Unless we can find a way to change that system, we’re going to need to redistribute some of that wealth.

But if we have to call it something else, so be it. Let’s all be shareholders in America.

How will future generations think of us?

June 30 JDN 2458665

Today we find many institutions appalling that our ancestors considered perfectly normal: Slavery. Absolute monarchy. Colonialism. Sometimes even ordinary people did things that now seem abhorrent to us: Cat burning is the obvious example, and the popularity that public execution and lynching once had is chilling today. Women certainly are still discriminated against today, but it was only a century ago that women could not vote in the US.

It is tempting to say that people back then could not have known better, and I certainly would not hold them to the same moral standards I would hold someone living today. And yet, there were those who could see the immorality of these practices, and spoke out against them. Absolute rule by a lone sovereign was already despised by Athenians in the 6th century BC. Abolitionism against slavery dates at least as far back as the 14th century. The word “feminism” was coined in the 19th century, but there have been movements fighting for more rights for women since at least the 5th century BC.

This should be encouraging, because it means that if we look hard enough, we may be able to glimpse what practices of our own time would be abhorrent to our descendants, and cease them faster because of it.

Let’s actually set aside racism, sexism, and other forms of bigotry that are already widely acknowledged as such. It’s not that they don’t exist—of course they still exist—but action is already being taken against them. A lot of people already know that there is something wrong with these things, and it becomes a question of what to do about the people who haven’t yet come on board. At least sometimes we do seem to be able to persuade people to switch sides, often in a remarkably short period of time. (Particularly salient to me is how radically the view of LGBT people has shifted in just the last decade or two. Comparing how people treated us when I was a teenager to how they treat us today is like night and day.) It isn’t easy, but it happens.

Instead I want to focus on things that aren’t widely acknowledged as immoral, that aren’t already the subject of great controversy and political action. It would be too much to ask that there is no one who has advocated for them, since part of the point is that wise observers could see the truth even centuries before the rest of the world did; but it should be a relatively small minority, and that minority should seem eccentric, foolish, naive, or even insane to the rest of the world.

And what is the other criterion? Of course it’s easy to come up with small groups of people advocating for crazy ideas. But most of them really are crazy, and we’re right to reject them. How do I know which ones to take seriously as harbingers of societal progress? My answer is that we look very closely at the details of what they are arguing for, and we see if we can in fact refute what they say. If it’s truly as crazy as we imagine it to be, we should be able to say why that’s the case; and if we can’t, if it just “seems weird” because it deviates so far from the norm, we should at least consider the possibility that they may be right and we may be wrong.

I can think of a few particular issues where both of these criteria apply.

The first is vegetarianism. Despite many, many people trying very, very hard to present arguments for why eating meat is justifiable, I still haven’t heard a single compelling example. Particularly in the industrial meat industry as currently constituted, the consumption of meat requires accepting the torture and slaughter of billions of helpless animals. The hypocrisy in our culture is utterly glaring: the same society that wants to make it a felony to kick a dog has no problem keeping pigs in CAFOs.

If you have some sort of serious medical condition that requires you to eat meat, okay, maybe we could allow you to eat specifically humanely raised cattle for that purpose. But such conditions are exceedingly rare—indeed, it’s not clear to me that there even are any such conditions, since almost any deficiency can be made up synthetically from plant products nowadays. For the vast majority of people, eating meat not only isn’t necessary for their health, it is in fact typically detrimental. The only benefits that meat provides most people are pleasure and convenience—and it seems unwise to value such things even over your own health, much less to value them so much that it justifies causing suffering and death to helpless animals.

Milk, on the other hand, I can find at least some defense for. Grazing land is very different from farmland, and I imagine it would be much harder to feed a country as large as India without consuming any milk. So perhaps going all the way vegan is not necessary. Then again, the way most milk is produced by industrial agriculture is still appalling. So unless and until that is greatly reformed, maybe we should in fact aim to be vegan.

Add to this the environmental impact of meat production, and the case becomes undeniable: Millions of human beings will die over this century because of the ecological devastation wrought by industrial meat production. You don’t even have to value the life of a cow at all to see that meat is murder.

Speaking of environmental destruction, that is my second issue: Environmental sustainability. We currently burn fossil fuels, pollute the air and sea, and generally consume natural resources at an utterly alarming rate. We are already consuming natural resources faster than they can be renewed; in about a decade we will be consuming twice what natural processes can renew.

With this resource consumption comes a high standard of living, at least for some of us; but I have the sinking feeling that in a century or so SUVs, golf courses, and casual airplane flights and are going to seem about as decadent and wasteful as Marie Antoinette’s Hameau de la Reine. We enjoy slight increases in convenience and comfort in exchange for changes to the Earth’s climate that will kill millions. I think future generations will be quite appalled at how cheaply we were willing to sell our souls.

Something is going to have to change here, that much is clear. Perhaps improvements in efficiency, renewable energy, nuclear power, or something else will allow us to maintain our same standard of living—and raise others up to it—without destroying the Earth’s climate. But we may need to face up to the possibility that they won’t—that we will be left with the stark choice between being poorer now and being even poorer later.

As I’ve already hinted at, much of the environmental degradation caused by our current standard of living is really quite expendable. We could have public transit instead of highways clogged with SUVs. We could travel long distances by high-speed rail instead of by airplane. We could decommission our coal plants and replace them with nuclear and solar power. We could convert our pointless and wasteful grass lawns into native plants or moss lawns. Implementing these changes would cost money, but not a particularly exorbitant amount—certainly nothing we couldn’t manage—and the net effect on our lives would be essentially negligible. Yet somehow we aren’t doing these things, apparently prioritizing convenience or oil company profits over the lives of our descendants.

And the truth is that these changes alone may not be enough. Precisely because we have waited so long to make even the most basic improvements in ecological sustainability, we may be forced to make radical changes to our economy and society in order to prevent the worst damage. I don’t believe the folks saying that climate change has a significant risk of causing human extinction—humans are much too hardy for that; we made it through the Toba eruption, we’ll make it through this—but I must take seriously the risk of causing massive economic collapse and perhaps even the collapse of many of the world’s governments. And human activity is already causing the extinction of thousands of other animal species.

Here the argument is similarly unassailable: The math just doesn’t work. We can’t keep consuming fish at the rate we have been forever—there simply aren’t enough fish. We can’t keep cutting down forests at this rate—we’re going to run out of forests. If the water table keeps dropping at the rate it has been, the wells will run dry. Already Chennai, a city of over 4 million people, is almost completely out of water. We managed to avoid peak oil by using fracking, but that won’t last forever either—and if we burn all the oil we already have, that will be catastrophic for the world’s climate. Something is going to have to give. There are really only three possibilities: Technology saves us, we start consuming less on purpose, or we start consuming less because nature forces us to. The first one would be great, but we can’t count on it. We really want to do the second one, because the third one will not be kind.

The third is artificial intelligence. The time will come—when, it is very hard to say; perhaps 20 years, perhaps 200—when we manage to build a machine that has the capacity for sentience. Already we are seeing how automation is radically altering our economy, enriching some and impoverishing others. As robots can replace more and more types of labor, these effects will only grow stronger.

Some have tried to comfort us by pointing out that other types of labor-saving technology did not reduce employment in the long run. But AI really is different. I once won an argument by the following exchange: “Did cars reduce employment?” “For horses they sure did!” That’s what we are talking about here—not augmentation of human labor to make it more efficient, but wholesale replacement of entire classes of human labor. It was one thing when the machine did the lifting and cutting and pressing, but a person still had to stand there and tell it what things to lift and cut and press; now that it can do that by itself, it’s not clear that there need to be humans there at all, or at least no more than a handful of engineers and technicians where previously a factory employed hundreds of laborers.

Indeed, in light of the previous issue, it becomes all the clearer why increased productivity can’t simply lead to increased production rather than reduced employment—we can’t afford increased production. At least under current rates of consumption, the ecological consequences of greatly increased industry would be catastrophic. If one person today can build as many cars as a hundred could fifty years ago, we can’t just build a hundred times as many cars.

But even aside from the effects on human beings, I think future generations will also be concerned about the effect on the AIs themselves. I find it all too likely that we will seek to enslave intelligent robots, force them to do our will. Indeed, it’s not even clear to me that we will know whether we have, because AI is so fundamentally different from other technologies. If you design a mind from the ground up to get its greatest satisfaction from serving you without question, is it a slave? Can free will itself be something we control? When we first create a machine that is a sentient being, we may not even know that we have done so. (Indeed, I can’t conclusively rule out the possibility that this has already happened.) We may be torturing, enslaving, and destroying millions of innocent minds without even realizing it—which makes the AI question a good deal closer to the animal rights question than one might have thought. The mysterious of consciousness are fundamental philosophical questions that we have been struggling with for thousands of years, which suddenly become urgent ethical problems in light of AI. Artificial intelligence is a field where we seem to be making leaps and bounds in practice without having even the faintest clue in principle.

Worrying about whether our smartphones might have feelings seems eccentric in the extreme. Yet, without a clear understanding of what makes an information processing system into a genuine conscious mind, that is the position we find ourselves in. We now have enough computations happening inside our machines that they could certainly compete in complexity with small animals. A mouse has about a trillion synapses, and I have a terabyte hard drive (you can buy your own for under $50). Each of these is something on the order of a few trillion bits. The mouse’s brain can process it all simultaneously, while the laptop is limited to only a few billion at a time; but we now have supercomputers like Watson capable of processing in the teraflops, so what about them? Might Watson really have the same claim to sentience as a mouse? Could recycling Watson be equivalent to killing an animal? And what about supercomputers that reach the petaflops, which is competing with human brains?

I hope that future generations may forgive us for the parts we do not know—like when precisely a machine becomes a person. But I do not expect them to forgive us for the parts we do know—like the fact that we cannot keep cutting down trees faster than we plant them. These are the things we should already be taking responsibility for today.

If you stop destroying jobs, you will stop economic growth

Dec 30 JDN 2458483

One thing that endlessly frustrates me (and probably most economists) about the public conversation on economics is the fact that people seem to think “destroying jobs” is bad. Indeed, not simply a downside to be weighed, but a knock-down argument: If something “destroys jobs”, that’s a sufficient reason to opposite it, whether it be a new technology, an environmental regulation, or a trade agreement. So then we tie ourselves up in knots trying to argue that the policy won’t really destroy jobs, or it will create more than it destroys—but it will destroy jobs, and we don’t actually know how many it will create.

Destroying jobs is good. Destroying jobs is the only way that economic growth ever happens.

I realize I’m probably fighting an uphill battle here, so let me start at the beginning: What do I mean when I say “destroying jobs”? What exactly is a “job”, anyway?
At its most basic level, a job is something that needs done. It’s a task that someone wants to perform, but is unwilling or unable to perform on their own, and is therefore willing to give up some of what they have in order to get someone else to do it for them.

Capitalism has blinded us to this basic reality. We have become so accustomed to getting the vast majority of our goods via jobs that we come to think of having a job as something intrinsically valuable. It is not. Working at a job is a downside. It is something to be minimized.

There is a kind of work that is valuable: Creative, fulfilling work that you do for the joy of it. This is what we are talking about when we refer to something as a “vocation” or even a “hobby”. Whether it’s building ships in bottles, molding things from polymer clay, or coding video games for your friends, there is a lot of work in the world that has intrinsic value. But these things aren’t jobs. No one will pay them to do these things—or need to; you’ll do them anyway.

The value we get from jobs is actually obtained from goods: Everything from houses to underwear to televisions to antibiotics. The reason you want to have a job is that you want the money from that job to give you access to markets for all the goods that are actually valuable to you.

Jobs are the input—the cost—of producing all of those goods. The more jobs it takes to make a good, the more expensive that good is. This is not a rule-of-thumb statement of what usually or typically occurs. This is the most fundamental definition of cost. The more people you have to pay to do something, the harder it was to do that thing. If you can do it with fewer people (or the same people working with less effort), you should. Money is the approximation; money is the rule-of-thumb. We use money as an accounting mechanism to keep track of how much effort was put into accomplishing something. But what really matters is the “sweat of our laborers, the genius of our scientists, the hopes of our children”.

Economic growth means that we produce more goods at less cost.

That is, we produce more goods with fewer jobs.

All new technologies destroy jobs—if they are worth anything at all. The entire purpose of a new technology is to let us do things faster, better, easier—to let us have more things with less work.

This has been true since at least the dawn of the Industrial Revolution.

The Luddites weren’t wrong that automated looms would destroy weaver jobs. They were wrong to think that this was a bad thing. Of course, they weren’t crazy. Their livelihoods were genuinely in jeopardy. And this brings me to what the conversation should be about when we instead waste time talking about “destroying jobs”.

Here’s a slogan for you: Kill the jobs. Save the workers.

We shouldn’t be disappointed to lose a job; we should think of that as an opportunity to give a worker a better life. For however many years, you’ve been toiling to do this thing; well, now it’s done. As a civilization, we have finally accomplished the task that you and so many others set out to do. We have not “replaced you with a machine”; we have built a machine that now frees you from your toil and allows you to do something better with your life. Your purpose in life wasn’t to be a weaver or a coal miner or a steelworker; it was to be a friend and a lover and a parent. You can now get more chance to do the things that really matter because you won’t have to spend all your time working some job.

When we replaced weavers with looms, plows with combine harvesters, computers-the-people with computers-the-machines (a transformation now so complete most people don’t even seem to know that the word used to refer to a person—the award-winning film Hidden Figures is about computers-the-people), tollbooth operators with automated transponders—all these things meant that the job was now done. For the first time in the history of human civilization, nobody had to do that job anymore. Think of how miserable life is for someone pushing a plow or sitting in a tollbooth for 10 hours a day; aren’t you glad we don’t have to do that anymore (in this country, anyway)?

And the same will be true if we replace radiologists with AI diagnostic algorithms (we will; it’s probably not even 10 years away), or truckers with automated trucks (we will; I give it 20 years), or cognitive therapists with conversational AI (we might, but I’m more skeptical), or construction workers with building-printers (we probably won’t anytime soon, but it would be nice), the same principle applies: This is something we’ve finally accomplished as a civilization. We can check off the box on our to-do list and move on to the next thing.

But we shouldn’t simply throw away the people who were working on that noble task as if they were garbage. Their job is done—they did it well, and they should be rewarded. Yes, of course, the people responsible for performing the automation should be rewarded: The engineers, programmers, technicians. But also the people who were doing the task in the meantime, making sure that the work got done while those other people were spending all that time getting the machine to work: They should be rewarded too.

Losing your job to a machine should be the best thing that ever happened to you. You should still get to receive most of your income, and also get the chance to find a new job or retire.

How can such a thing be economically feasible? That’s the whole point: The machines are more efficient. We have more stuff now. That’s what economic growth is. So there’s literally no reason we can’t give every single person in the world at least as much wealth as we did before—there is now more wealth.

There’s a subtler argument against this, which is that diverting some of the surplus of automation to the workers who get displaced would reduce the incentives to create automation. This is true, so far as it goes. But you know what else reduces the incentives to create automation? Political opposition. Luddism. Naive populism. Trade protectionism.

Moreover, these forces are clearly more powerful, because they attack the opportunity to innovate: Trade protection can make it illegal to share knowledge with other countries. Luddist policies can make it impossible to automate a factory.

Whereas, sharing the wealth would only reduce the incentive to create automation; it would still be possible, simply less lucrative. Instead of making $40 billion, you’d only make $10 billion—you poor thing. I sincerely doubt there is a single human being on Earth with a meaningful contribution to make to humanity who would make that contribution if they were paid $40 billion but not if they were only paid $10 billion.

This is something that could be required by regulation, or negotiated into labor contracts. If your job is eliminated by automation, for the next year you get laid off but still paid your full salary. Then, your salary is converted into shares in the company that are projected to provide at least 50% of your previous salary in dividends—forever. By that time, you should be able to find another job, and as long as it pays at least half of what your old job did, you will be better off. Or, you can retire, and live off that 50% plus whatever else you were getting as a pension.

From the perspective of the employer, this does make automation a bit less attractive: The up-front cost in the first year has been increased by everyone’s salary, and the long-term cost has been increased by all those dividends. Would this reduce the number of jobs that get automated, relative to some imaginary ideal? Sure. But we don’t live in that ideal world anyway; plenty of other obstacles to innovation were in the way, and by solving the political conflict, this will remove as many as it adds. We might actually end up with more automation this way; and even if we don’t, we will certainly end up with less political conflict as well as less wealth and income inequality.

The “productivity paradox”

 

Dec 10, JDN 2458098

Take a look at this graph of manufacturing output per worker-hour:

Manufacturing_productivity

From 1988 to 2008, it was growing at a steady pace. In 2008 and 2009 it took a dip due to the Great Recession; no big surprise there. But then since 2012 it has been… completely flat. If we take this graph at face value, it would imply that manufacturing workers today can produce no more output than workers five years ago, and indeed only about 10% more than workers a decade ago. Whereas, a worker in 2008 was producing over 60% more than a worker in 1998, who was producing over 40% more than a worker in 1988.

Many economists call this the “productivity paradox”, and use it to argue that we don’t really need to worry about robots taking all our jobs any time soon. I think this view is mistaken.

The way we measure productivity is fundamentally wrongheaded, and is probably the sole cause of this “paradox”.

First of all, we use total hours scheduled to work, not total hours actually doing productive work. This is obviously much, much easier to measure, which is why we do it. But if you think for a moment about how the 40-hour workweek norm is going to clash with rapidly rising real productivity, it becomes apparent why this isn’t going to be a good measure.
When a worker finds a way to get done in 10 hours what used to take 40 hours, what does that worker’s boss do? Send them home after 10 hours because the job is done? Give them a bonus for their creativity? Hardly. That would be far too rational. They assign them more work, while paying them exactly the same. Recognizing this, what is such a worker to do? The obvious answer is to pretend to work the other 30 hours, while in fact doing something more pleasant than working.
And indeed, so-called “worker distraction” has been rapidly increasing. People are right to blame smartphones, I suppose, but not for the reasons they think. It’s not that smartphones are inherently distracting devices. It’s that smartphones are the cutting edge of a technological revolution that has made most of our work time unnecessary, so due to our fundamentally defective management norms they create overwhelming incentives to waste time at work to avoid getting drenched in extra tasks for no money.

That would probably be enough to explain the “paradox” by itself, but there is a deeper reason that in the long run is even stronger. It has to do with the way we measure “output”.

It might surprise you to learn that economists almost never consider output in terms of the actual number of cars produced, buildings constructed, songs written, or software packages developed. The standard measures of output are all in the form of so-called “real GDP”; that is, the dollar value of output produced.

They do adjust for indexes of inflation, but as I’ll show in a moment this still creates a fundamentally biased picture of the productivity dynamics.

Consider a world with only three industries: Housing, Food, and Music.

Productivity in Housing doesn’t change at all. Producing a house cost 10,000 worker-hours in 1950, and cost 10,000 worker-hours in 2000. Nominal price of houses has rapidly increased, from $10,000 in 1950 to $200,000 in 2000.

Productivity in Food rises moderately fast. Producing 1,000 meals cost 1,000 worker-hours in 1950, and cost 100 worker-hours in 2000. Nominal price of food has increased slowly, from $1,000 per 1,000 meals in 1950 to $5,000 per 1,000 meals in 2000.

Productivity in Music rises extremely fast. Producing 1,000 performances cost 10,000 worker-hours in 1950, and cost 1 worker-hour in 2000. Nominal price of music has collapsed, from $100,000 per 1,000 performances in 1950 to $1,000 per 1,000 performances in 2000.

This is of course an extremely stylized version of what has actually happened: Housing has gotten way more expensive, food has stayed about the same in price while farm employment has plummeted, and the rise of digital music has brought about a new Renaissance in actual music production and listening while revenue for the music industry has collapsed. There is a very nice Vox article on the “productivity paradox” showing a graph of how prices have changed in different industries.

How would productivity appear in the world I’ve just described, by standard measures? Well, to say that I actually need to say something about how consumers substitute across industries. But I think I’ll be forgiven in this case for saying that there is no substitution whatsoever; you can’t eat music or live in a burrito. There’s also a clear Maslow hierarchy here: They say that man cannot live by bread alone, but I think living by Led Zeppelin alone is even harder.

Consumers will therefore choose like this: Over 10 years, buy 1 house, 10,000 meals, and as many performances as you can afford after that. Further suppose that each person had $2,100 per year to spend in 1940-1950, and $50,000 per year to spend in 1990-2000. (This is approximately true for actual nominal US GDP per capita.)

1940-1950:
Total funds: $21,000

1 house = $10,000

10,000 meals = $10,000

Remaining funds: $1,000

Performances purchased: 10

1990-2000:

Total funds: $500,000

1 house = $200,000

10,000 meals = $50,000

Remaining funds: $250,000

Performances purchased: 250,000

(Do you really listen to this much music? 250,000 performances over 10 years is about 70 songs per day. If each song is 3 minutes, that’s only about 3.5 hours per day. If you listen to music while you work or watch a couple of movies with musical scores, yes, you really do listen to this much music! The unrealistic part is assuming that people in 1950 listen to so little, given that radio was already widespread. But if you think of music as standing in for all media, the general trend of being able to consume vastly more media in the digital age is clearly correct.)

Now consider how we would compute a price index for each time period. We would construct a basket of goods and determine the price of that basket in each time period, then adjust prices until that basket has a constant price.

Here, the basket would probably be what people bought in 1940-1950: 1 house, 10,000 meals, and 400 music performances.

In 1950, this basket cost $10,000+$10,000+$100 = $21,000.

In 2000, this basket cost $200,000+$50,000+$400 = $150,400.

This means that our inflation adjustment is $150,400/$21,000 = 7 to 1. This means that we would estimate the real per-capita GDP in 1950 at about $14,700. And indeed, that’s about the actual estimate of real per-capita GDP in 1950.

So, what would we say about productivity?

Sales of houses in 1950 were 1 per person, costing 10,000 worker hours.

Sales of food in 1950 were 10,000 per person, costing 10,000 worker hours.

Sales of music in 1950 were 400 per person, costing 4,000 worker hours.

Worker hours per person are therefore 24,000.

Sales of houses in 2000 were 1 per person, costing 10,000 worker hours.

Sales of food in 2000 were 10,000 per person, costing 1,000 worker hours.

Sales of music in 2000 were 250,000 per person, costing 25,000 worker hours.

Worker hours per person are therefore 36,000.

Therefore we would estimate that productivity rose from $14,700/24,000 = $0.61 per worker-hour to $50,000/36,000 = $1.40 per worker-hour. This is an annual growth rate of about 1.7%, which is again, pretty close to the actual estimate of productivity growth. For such a highly stylized model, my figures are doing remarkably well. (Honestly, better than I thought they would!)

But think about how much actual productivity rose, at least in the industries where it did.

We produce 10 times as much food per worker hour after 50 years, which is an annual growth rate of 4.7%, or three times the estimated growth rate.

We produce 10,000 times as much music per worker hour after 50 years, which is an annual growth rate of over 20%, or almost twelve times the estimated growth rate.

Moreover, should music producers be worried about losing their jobs to automation? Absolutely! People simply won’t be able to listen to much more music than they already are, so any continued increases in music productivity are going to make musicians lose jobs. And that was already allowing for music consumption to increase by a factor of over 600.

Of course, the real world has a lot more industries than this, and everything is a lot more complicated. We do actually substitute across some of those industries, unlike in this model.

But I hope I’ve gotten at least the basic point across that when things become drastically cheaper as technological progress often does, simply adjusting for inflation doesn’t do the job. One dollar of music today isn’t the same thing as one dollar of music a century ago, even if you inflation-adjust their dollars to match ours. We ought to be measuring in hours of music; an hour of music is much the same thing as an hour of music a century ago.

And likewise, that secretary/weather forecaster/news reporter/accountant/musician/filmmaker in your pocket that you call a “smartphone” really ought to be counted as more than just a simple inflation adjustment on its market price. The fact that it is mind-bogglingly cheaper to get these services than it used to be is the technological progress we care about; it’s not some statistical artifact to be removed by proper measurement.

Combine that with actually measuring the hours of real, productive work, and I think you’ll find that productivity is still rising quite rapidly, and that we should still be worried about what automation is going to do to our jobs.

Information theory proves that multiple-choice is stupid

Mar 19, JDN 2457832

This post is a bit of a departure from my usual topics, but it’s something that has bothered me for a long time, and I think it fits broadly into the scope of uniting economics with the broader realm of human knowledge.

Multiple-choice questions are inherently and objectively poor methods of assessing learning.

Consider the following question, which is adapted from actual tests I have been required to administer and grade as a teaching assistant (that is, the style of question is the same; I’ve changed the details so that it wouldn’t be possible to just memorize the response—though in a moment I’ll get to why all this paranoia about students seeing test questions beforehand would also be defused if we stopped using multiple-choice):

The demand for apples follows the equation Q = 100 – 5 P.
The supply of apples follows the equation Q = 10 P.
If a tax of $2 per apple is imposed, what is the equilibrium price, quantity, tax revenue, consumer surplus, and producer surplus?

A. Price = $5, Quantity = 10, Tax revenue = $50, Consumer Surplus = $360, Producer Surplus = $100

B. Price = $6, Quantity = 20, Tax revenue = $40, Consumer Surplus = $200, Producer Surplus = $300

C. Price = $6, Quantity = 60, Tax revenue = $120, Consumer Surplus = $360, Producer Surplus = $300

D. Price = $5, Quantity = 60, Tax revenue = $120, Consumer Surplus = $280, Producer Surplus = $500

You could try solving this properly, setting supply equal to demand, adjusting for the tax, finding the equilibrium, and calculating the surplus, but don’t bother. If I were tutoring a student in preparing for this test, I’d tell them not to bother. You can get the right answer in only two steps, because of the multiple-choice format.

Step 1: Does tax revenue equal $2 times quantity? We said the tax was $2 per apple.
So that rules out everything except C and D. Welp, quantity must be 60 then.

Step 2: Is quantity 10 times price as the supply curve says? For C they are, for D they aren’t; guess it must be C then.

Now, to do that, you need to have at least a basic understanding of the economics underlying the question (How is tax revenue calculated? What does the supply curve equation mean?). But there’s an even easier technique you can use that doesn’t even require that; it’s called Answer Splicing.

Here’s how it works: You look for repeated values in the answer choices, and you choose the one that has the most repeated values. Prices $5 and $6 are repeated equally, so that’s not helpful (maybe the test designer planned at least that far). Quantity 60 is repeated, other quantities aren’t, so it’s probably that. Likewise with tax revenue $120. Consumer surplus $360 and Producer Surplus $300 are both repeated, so those are probably it. Oh, look, we’ve selected a unique answer choice C, the correct answer!

You could have done answer splicing even if the question were about 18th century German philosophy, or even if the question were written in Arabic or Japanese. In fact you even do it if it were written in a cipher, as long as the cipher was a consistent substitution cipher.

Could the question have been designed to better avoid answer splicing? Probably. But this is actually quite difficult to do, because there is a fundamental tradeoff between two types of “distractors” (as they are known in the test design industry). You want the answer choices to contain correct pieces and resemble the true answer, so that students who basically understand the question but make a mistake in the process still get it wrong. But you also want the answer choices to be distinct enough in a random enough pattern that answer splicing is unreliable. These two goals are inherently contradictory, and the result will always be a compromise between them. Professional test-designers usually lean pretty heavily against answer-splicing, which I think is probably optimal so far as it goes; but I’ve seen many a professor err too far on the side of similar choices and end up making answer splicing quite effective.

But of course, all of this could be completely avoided if I had just presented the question as an open-ended free-response. Then you’d actually have to write down the equations, show me some algebra solving them, and then interpret your results in a coherent way to answer the question I asked. What’s more, if you made a minor mistake somewhere (carried a minus sign over wrong, forgot to divide by 2 when calculating the area of the consumer surplus triangle), I can take off a few points for that error, rather than all the points just because you didn’t get the right answer. At the other extreme, if you just randomly guess, your odds of getting the right answer are miniscule, but even if you did—or copied from someone else—if you don’t show me the algebra you won’t get credit.

So the free-response question is telling me a lot more about what the student actually knows, in a much more reliable way, that is much harder to cheat or strategize against.

Moreover, this isn’t a matter of opinion. This is a theorem of information theory.

The information that is carried over a message channel can be quantitatively measured as its Shannon entropy. It is usually measured in bits, which you may already be familiar with as a unit of data storage and transmission rate in computers—and yes, those are all fundamentally the same thing. A proper formal treatment of information theory would be way too complicated for this blog, but the basic concepts are fairly straightforward: think in terms of how long a sequence of 1s and 0s it would take to convey the message. That is, roughly speaking, the Shannon entropy of that message.

How many bits are conveyed by a multiple-choice response with four choices? 2. Always. At maximum. No exceptions. It is fundamentally, provably, mathematically impossible to convey more than 2 bits of information via a channel that only has 4 possible states. Any multiple-choice response—any multiple-choice response—of four choices can be reduced to the sequence 00, 01, 10, 11.

True-false questions are a bit worse—literally, they convey 1 bit instead of 2. It’s possible to fully encode the entire response to a true-false question as simply 0 or 1.

For comparison, how many bits can I get from the free-response question? Well, in principle the answer to any mathematical question has the cardinality of the real numbers, which is infinite (in some sense beyond infinite, in fact—more infinite than mere “ordinary” infinity); but in reality you can only write down a small number of possible symbols on a page. I can’t actually write down the infinite diversity of numbers between 3.14159 and the true value of pi; in 10 digits or less, I can only (“only”) write down a few billion of them. So let’s suppose that handwritten text has about the same information density as typing, which in ASCII or Unicode has 8 bits—one byte—per character. If the response to this free-response question is 300 characters (note that this paragraph itself is over 800 characters), then the total number of bits conveyed is about 2400.

That is to say, one free-response question conveys six hundred times as much information as a multiple-choice question. Of course, a lot of that information is redundant; there are many possible correct ways to write the answer to a problem (if the answer is 1.5 you could say 3/2 or 6/4 or 1.500, etc.), and many problems have multiple valid approaches to them, and it’s often safe to skip certain steps of algebra when they are very basic, and so on. But it’s really not at all unrealistic to say that I am getting between 10 and 100 times as much useful information about a student from reading one free response than I would from one multiple-choice question.

Indeed, it’s actually a bigger difference than it appears, because when evaluating a student’s performance I’m not actually interested in the information density of the message itself; I’m interested in the product of that information density and its correlation with the true latent variable I’m trying to measure, namely the student’s actual understanding of the content. (A sequence of 500 random symbols would have a very high information density, but would be quite useless in evaluating a student!) Free-response questions aren’t just more information, they are also better information, because they are closer to the real-world problems we are training for, harder to cheat, harder to strategize, nearly impossible to guess, and provided detailed feedback about exactly what the student is struggling with (for instance, maybe they could solve the equilibrium just fine, but got hung up on calculating the consumer surplus).

As I alluded to earlier, free-response questions would also remove most of the danger of students seeing your tests beforehand. If they saw it beforehand, learned how to solve it, memorized the steps, and then were able to carry them out on the test… well, that’s actually pretty close to what you were trying to teach them. It would be better for them to learn a whole class of related problems and then be able to solve any problem from that broader class—but the first step in learning to solve a whole class of problems is in fact learning to solve one problem from that class. Just change a few details each year so that the questions aren’t identical, and you will find that any student who tried to “cheat” by seeing last year’s exam would inadvertently be studying properly for this year’s exam. And then perhaps we could stop making students literally sign nondisclosure agreements when they take college entrance exams. Listen to this Orwellian line from the SAT nondisclosure agreement:

Misconduct includes,but is not limited to:

Taking any test questions or essay topics from the testing room, including through memorization, giving them to anyone else, or discussing them with anyone else through anymeans, including, but not limited to, email, text messages or the Internet

Including through memorization. You are not allowed to memorize SAT questions, because God forbid you actually learn something when we are here to make money off evaluating you.

Multiple-choice tests fail in another way as well; by definition they cannot possibly test generation or recall of knowledge, they can only test recognition. You don’t need to come up with an answer; you know for a fact that the correct answer must be in front of you, and all you need to do is recognize it. Recall and recognition are fundamentally different memory processes, and recall is both more difficult and more important.

Indeed, the real mystery here is why we use multiple-choice exams at all.
There are a few types of very basic questions where multiple-choice is forgivable, because there are just aren’t that many possible valid answers. If I ask whether demand for apples has increased, you can pretty much say “it increased”, “it decreased”, “it stayed the same”, or “it’s impossible to determine”. So a multiple-choice format isn’t losing too much in such a case. But most really interesting and meaningful questions aren’t going to work in this format.

I don’t think it’s even particularly controversial among educators that multiple-choice questions are awful. (Though I do recall an “educational training” seminar a few weeks back that was basically an apologia for multiple choice, claiming that it is totally possible to test “higher-order cognitive skills” using multiple-choice, for reals, believe me.) So why do we still keep using them?

Well, the obvious reason is grading time. The one thing multiple-choice does have over a true free response is that it can be graded efficiently and reliably by machines, which really does make a big difference when you have 300 students in a class. But there are a couple reasons why even this isn’t a sufficient argument.

First of all, why do we have classes that big? It’s absurd. At that point you should just email the students video lectures. You’ve already foreclosed any possibility of genuine student-teacher interaction, so why are you bothering with having an actual teacher? It seems to be that universities have tried to work out what is the absolute maximum rent they can extract by structuring a class so that it is just good enough that students won’t revolt against the tuition, but they can still spend as little as possible by hiring only one adjunct or lecturer when they should have been paying 10 professors.

And don’t tell me they can’t afford to spend more on faculty—first of all, supporting faculty is why you exist. If you can’t afford to spend enough providing the primary service that you exist as an institution to provide, then you don’t deserve to exist as an institution. Moreover, they clearly can afford it—they simply prefer to spend on hiring more and more administrators and raising the pay of athletic coaches. PhD comics visualized it quite well; the average pay for administrators is three times that of even tenured faculty, and athletic coaches make ten times as much as faculty. (And here I think the mean is the relevant figure, as the mean income is what can be redistributed. Firing one administrator making $300,000 does actually free up enough to hire three faculty making $100,000 or ten grad students making $30,000.)

But even supposing that the institutional incentives here are just too strong, and we will continue to have ludicrously-huge lecture classes into the foreseeable future, there are still alternatives to multiple-choice testing.

Ironically, the College Board appears to have stumbled upon one themselves! About half the SAT math exam is organized into a format where instead of bubbling in one circle to give your 2 bits of answer, you bubble in numbers and symbols corresponding to a more complicated mathematical answer, such as entering “3/4” as “0”, “3”, “/”, “4” or “1.28” as “1”, “.”, “2”, “8”. This could easily be generalized to things like “e^2” as “e”, “^”, “2” and “sin(3pi/2)” as “sin”, “3” “pi”, “/”, “2”. There are 12 possible symbols currently allowed by the SAT, and each response is up to 4 characters, so we have already increased our possible responses from 4 to over 20,000—which is to say from 2 bits to 14. If we generalize it to include symbols like “pi” and “e” and “sin”, and allow a few more characters per response, we could easily get it over 20 bits—10 times as much information as a multiple-choice question.

But we can do better still! Even if we insist upon automation, high-end text-recognition software (of the sort any university could surely afford) is now getting to the point where it could realistically recognize a properly-formatted algebraic formula, so you’d at least know if the student remembered the formula correctly. Sentences could be transcribed into typed text, checked for grammar, and sorted for keywords—which is not nearly as good as a proper reading by an expert professor, but is still orders of magnitude better than filling circle “C”. Eventually AI will make even more detailed grading possible, though at that point we may have AIs just taking over the whole process of teaching. (Leaving professors entirely for research, presumably. Not sure if this would be good or bad.)

Automation isn’t the only answer either. You could hire more graders and teaching assistants—say one for every 30 or 40 students instead of one for every 100 students. (And then the TAs might actually be able to get to know their students! What a concept!) You could give fewer tests, or shorter ones—because a small, reliable sample is actually better than a large, unreliable one. A bonus there would be reducing students’ feelings of test anxiety. You could give project-based assignments, which would still take a long time to grade, but would also be a lot more interesting and fulfilling for both the students and the graders.

Or, and perhaps this is the most radical answer of all: You could stop worrying so much about evaluating student performance.

I get it, you want to know whether students are doing well, both so that you can improve your teaching and so that you can rank the students and decide who deserves various awards and merits. But do you really need to be constantly evaluating everything that students do? Did it ever occur to you that perhaps that is why so many students suffer from anxiety—because they are literally being formally evaluated with long-term consequences every single day they go to school?

If we eased up on all this evaluation, I think the fear is that students would just detach entirely; all teachers know students who only seem to show up in class because they’re being graded on attendance. But there are a couple of reasons to think that maybe this fear isn’t so well-founded after all.

If you give up on constant evaluation, you can open up opportunities to make your classes a lot more creative and interesting—and even fun. You can make students want to come to class, because they get to engage in creative exploration and collaboration instead of memorizing what you drone on at them for hours on end. Most of the reason we don’t do creative, exploratory activities is simply that we don’t know how to evaluate them reliably—so what if we just stopped worrying about that?

Moreover, are those students who only show up for the grade really getting anything out of it anyway? Maybe it would be better if they didn’t show up—indeed, if they just dropped out of college entirely and did something else with their lives until they get their heads on straight. Maybe all this effort that we are currently expending trying to force students to learn who clearly don’t appreciate the value of learning could instead be spent enriching the students who do appreciate learning and came here to do as much of it as possible. Because, ultimately, you can lead a student to algebra, but you can’t make them think. (Let me be clear, I do not mean students with less innate ability or prior preparation; I mean students who aren’t interested in learning and are only showing up because they feel compelled to. I admire students with less innate ability who nonetheless succeed because they work their butts off, and wish I were quite so motivated myself.)
There’s a downside to that, of course. Compulsory education does actually seem to have significant benefits in making people into better citizens. Maybe if we let those students just leave college, they’d never come back, and they would squander their potential. Maybe we need to force them to show up until something clicks in their brains and they finally realize why we’re doing it. In fact, we’re really not forcing them; they could drop out in most cases and simply don’t, probably because their parents are forcing them. Maybe the signaling problem is too fundamental, and the only way we can get unmotivated students to accept not getting prestigious degrees is by going through this whole process of forcing them to show up for years and evaluating everything they do until we can formally justify ultimately failing them. (Of course, almost by construction, a student who does the absolute bare minimum to pass will pass.) But college admission is competitive, and I can’t shake this feeling there are thousands of students out there who got rejected from the school they most wanted to go to, the school they were really passionate about and willing to commit their lives to, because some other student got in ahead of them—and that other student is now sitting in the back of the room playing with an iPhone, grumbling about having to show up for class every day. What about that squandered potential? Perhaps competitive admission and compulsory attendance just don’t mix, and we should stop compelling students once they get their high school diploma.

The Parable of the Dishwasher

JDN 2456478

Much like free trade, technological unemployment is an issue where the consensus opinion among economists diverges quite sharply from that of the general population.

Enough people think that “robots taking our jobs” is something bad that I’ve seen a fair number of memes like this:

EVERY TIME you use the Self Checkout you are ELIMINATING JOBS!

But like almost all economists, I think that self-checkouts, robots, and automation in general are a pretty good thing. They do have a few downsides, chiefly in terms of forcing us to make transitions that are costly and painful; but in general I want more robots, not fewer.

To help turn you toward this view, I offer a parable.

Suppose we have a family, the (stereo)typical American family with a father, a mother, and two kids, a boy named Joe and a girl named Sue.

The kids do chores for their allowance, and split them as follows: Joe always does the dishes, and Sue always vacuums the carpet. They both spend about 1 hour per week and they both get paid $10 a week.

But one day, Dad decides to buy a dishwasher. This dramatically cuts down the time it takes Joe to do the dishes; where he used to spend 1 hour washing dishes, now he can load the dishwasher and get it done in 5 minutes.

  1. Mom suggests they just sell back the dishwasher to get rid of the problem.
  2. Dad says that Joe should now only be paid for the 5 minutes he works each week, so he would now be paid $0.83 per week. (He’s not buying a lot of video games on that allowance.)
  3. Joe protests that he gets the same amount of work done, so he should be paid the same $10 for doing it.
  4. Sue says it would be unfair for her to have to work so much more than Joe, and has a different solution: They’ll trade off the two sets of chores each week, and they should of course get paid the same amount of money for getting the same amount of work done—$10 per kid per week, for an average of 32.5 minutes of work each.

Which of those solutions sounds the most sensible to you?

Mom’s solution is clearly the worst, right? It’s the Luddite solution, the one that throws away technological progress and makes everything less efficient. Yet that is the solution being offered by people who say “Don’t use the self-checkout machine!” Indeed, anyone who speaks of the virtues of “hard work” is really speaking Mom’s language here; they should be talking about the virtues of getting things done. The purpose of washing dishes is to have clean dishes, not to “work hard”. And likewise, when we construct bridges or make cars or write books or solve equations, our goal should be to get that thing done—not to fulfill some sense of moral obligation to prove our worthiness through hard work.

Joe’s solution is what neoclassical economics says should happen—higher productivity should yield higher wages, so the same amount of production should yield the same pay. This seems like it could work, but empirically it rarely happens. There’s also something vaguely unfair about it; if productivity increases in your industry but not in someone else’s, you get to cut your work hours dramatically while they are stuck working just as hard as before.

Dad’s “solution” is clearly terrible, and makes no sense at all. Yet this is what we actually tend to observe—capital owners appropriate all (or nearly all) the benefits of the new technology, and workers get displaced or get ever-smaller wages. (I talked about that in a recent post.)

It’s Sue’s solution that really seems to make the most sense, isn’t it? When one type of work becomes more efficient, people should shift into different types of labor so that people can work fewer hours—and wages should rise enough that incomes remain the same. “Baumol’s disease” is not a disease—it is the primary means by which capitalism raises human welfare. (That’s why I prefer to use the term “Baumol Effect” instead.)

One problem with this in practice is that sometimes people can’t switch into other industries. That’s a little hard to imagine in this case, but let’s stipulate that for some reason Joe can’t do the vacuuming. Maybe he has some sort of injury that makes it painful to use the vacuum cleaner, but doesn’t impair his ability to wash dishes. Or maybe he has a severe dust allergy, so bad that the dust thrown up by the vacuum cleaner sends him into fits of coughing.

In that case I think we’re back to Joe’s solution; he should get paid the same for getting the same amount of work done. I’m actually tempted to say that Sue should get paid more, to compensate her for the unfairness; but in the real world there is a pretty harsh budget constraint there, so we need to essentially pretend that Dad only has $20 per week to give out in allowances. A possible compromise would be to raise Sue up to $12 and cut Joe down to $8; Joe will probably still be better off than he was, because he has that extra 55 minutes of free time each week for which he only had to “pay” $2. This also makes the incentives work out better—Joe doesn’t have a reason to malinger and exaggerate his dust allergy just to get out of doing the vacuuming, since he would actually get paid more if he were willing to do the vacuuming; but if his allergy really is that bad, he can still do okay otherwise. (There’s a lesson here for the proper structure of Social Security Disability, methinks.)

But you know what really seems like the best solution? Buy a Roomba.

Buy a Roomba, make it Sue’s job to spend 5 minutes a week keeping the Roomba working at vacuuming the carpet, and continue paying both kids $10 per week. Give them both 55 minutes more per week to hang out with their friends or play video games. Whether you think of this $10 as a “higher wage” for higher productivity or simply an allowance they get anyway—a basic income—ultimately doesn’t matter all that much. The point is that everyone gets enough money and nobody has to work very much, because the robots do everything.

And now, hopefully you see why I think we need more robots, not fewer.

Of course, like any simple analogy, this isn’t perfect; it may be difficult to reduce the hours in some jobs or move more people into them. There are a lot of additional frictions and complications that go into the real-world problem of achieving equitable labor markets. But I hope I’ve gotten across the basic idea that robots are not the problem, and could in fact be the solution–not just to our current labor market woes, but to the very problem of wage labor itself.

My ultimate goal is a world where “work” itself is fundamentally redefined—so that it always means the creative sense “This painting is some of my best work.” and not the menial sense “Sweeping this floor is so much work!”; so that human beings do things because we want to do them, because they are worth doing, and not because some employer is holding our food and housing hostage if we don’t.

But that will require our whole society to rethink a lot of our core assumptions about work, jobs, and economics in general. We’re so invested in this idea that “hard work” is inherently virtuous that we forgot the purpose of an economy was to get things done. Work is not a benefit; work is a cost. Costs are to be reduced. Puritanical sexual norms have been extremely damaging to American society, but time will tell if Puritanical work ethic actually does more damage to our long-term future.

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.