Our Robot Future

I was a child in the 1960’s, and one of my favorite cartoons was “The Jetsons.” 

I expected that my future would look like the world portrayed in the show—I particularly wanted to jet around in my personal rocket ship. (I didn’t play too much attention to how boringly conventional the family structure was—dad goes to a dull job while mom goes shopping.)

In the 1950s and 60s the technological advances of the twentieth century inspired dreams of a future of leisure. “Design for Dreaming” wonderfully illustrates these dreams  (This is the MST3K version and well worth watching!), including technology that liberates women from the drudgery of housework. And that has come true: I can remember my mother laboriously defrosting our refrigerator on a regular basis. Now my refrigerator does the work for me.

But as the century wore on it seemed like the grandiose dreams of the future were just a fantasy. What happened to our personal rocket ships? We did get lots of new technologies, like computers and smartphones that have made life more interesting and productive, but they have also made our lives more complex and caused us to work more, not less.

What happened to that dream of leisure?

Kevin Drum warns in a recent Mother Jones magazine article (May/June 2013, “Welcome Robot Overlords. Please Don't Fire Us?”), that most of us will soon be living lives of leisure, but it’s not going to be pleasant.

He provides a fascinating analogy to describe how the foundation for this future has been building so slowly that we are mostly oblivious to it; but we are just a decade or so away from seeing it transform our world (see the bottom of the article for a description of this analogy).

The essence is that artificial intelligence (AI) and robots have been steadily increasing in computational ability and numbers, and they are about to put almost everyone out of work. In fact, Drum suggests that this is already happening: this is why the unemployment rate has stayed so stubbornly high in the last few years.

When is the last time someone pumped your gas for you? Think of how many service station attendant jobs have been eliminated. Grocery store cashiers are soon to be obsolete. How many receptionists have been put out of work by businesses using interactive phone answering software?

Some new products coming that will reduce the need for humans in other jobs: driverless cars mean we’ll no longer need taxi drivers; implants that sense an impending heart attack and call 911 via your smartphone will reduce the need for all kinds of medical services; computers that grade student’s papers and scan legal documents eliminate the need for teacher’s assistants and lawyers.

Paul Krugman wrote in a 2011 column, “Degrees and Dollars”:

It is a truth universally acknowledged that education is the key to economic success. Everyone knows that the jobs of the future will require ever-higher levels of skill… 

But what everyone knows is wrong.

The Times [recently] published an article about the growing use of software to perform legal research. Computers, it turns out, can quickly analyze millions of documents, cheaply performing a task that used to require armies of lawyers and paralegals. In this case, then, technological progress is actually reducing the demand for highly educated workers.
And legal research isn’t an isolated example. As the article points out, software has also been replacing engineers in such tasks as chip design. More broadly, the idea that modern technology eliminates only menial jobs, that well-educated workers are clear winners, may dominate popular discussion, but it’s actually decades out of date. 

Some years ago the economists David Autor, Frank Levy and Richard Murnane argued that this was the wrong way to think about it. Computers, they pointed out, excel at routine tasks, “cognitive and manual tasks that can be accomplished by following explicit rules.” Therefore, any routine task — a category that includes many white-collar, nonmanual jobs — is in the firing line. Conversely, jobs that can’t be carried out by following explicit rules — a category that includes many kinds of manual labor, from truck drivers to janitors — will tend to grow even in the face of technological progress.

The new AI technology is capital-intensive, and economics predicts that with this kind of “capital-biased” production the owners of capital will get rich while the workers will suffer. So perhaps this also explains the rising income inequality we have seen in recent decades. As the unemployment rate is not just a consequence of the financial crash, rising income inequality isn’t just a reflection of the lower taxes and lax regulation of the last thirty years. What we are seeing is the natural outcome of the roboticization of the workforce. And it’s going to get worse.

Just recently I’ve seen news reports that confirm Mr. Drum’s predictions. Manufacturing is returning to this country because it has become highly automated and does not require as much labor. High U.S. labor costs are meaningless when robots do all the work.

The percentage of young people employed is at an all-time low. “The Idled Young Americans” published this week in the New York Times, documents the jobless nature of the “recovery” we’re now in:

Over the last 12 years, the United States has gone from having the highest share of employed 25- to 34-year-olds among large, wealthy economies to having among the lowest. 

The grim shift — “a historic turnaround,” says Robert A. Moffitt, a Johns Hopkins University economist — stems from two underappreciated aspects of our long economic slump. First, it has exacted the harshest toll on the young — even harsher than on people in their 50s and 60s, who have also suffered. And while the American economy has come back more robustly than some of its global rivals in terms of overall production, the recovery has been strangely light on new jobs, even after Friday’s better-than-expected unemployment report. American companies are doing more with less. 

“This still is a very big puzzle,” said Lawrence F. Katz, a Harvard professor who was chief economist at the Labor Department during the Clinton administration. He called the severe downturn in jobs “the million-dollar question” for the economy.

This quote from Professor Katz brings me to one of the scarier parts of Mr. Drum’s article: he says economists have not been addressing the coming change in our economic structure at all. Just recently Paul Krugman realized it was time to start paying attention; in late 2012 he wrote a blog post addressing the consequences of the “Rise of the Robots”:

This is an old concern in economics; it’s “capital-biased technological change,” which tends to shift the distribution of income away from workers to the owners of capital… 

If this is the wave of the future, it makes nonsense of just about all the conventional wisdom on reducing inequality. Better education won’t do much to reduce inequality if the big rewards simply go to those with the most assets. Creating an “opportunity society”, or whatever it is the likes of Paul Ryan etc. are selling this week, won’t do much if the most important asset you can have in life is, well, lots of assets inherited from your parents. And so on. 

I think our eyes have been averted from the capital/labor dimension of inequality, for several reasons. It didn’t seem crucial back in the 1990s, and not enough people (me included!) have looked up to notice that things have changed. It has echoes of old-fashioned Marxism — which shouldn’t be a reason to ignore facts, but too often is. And it has really uncomfortable implications. 

But I think we’d better start paying attention to those implications.

What are the implications of large numbers of people losing their jobs?

The New York Times just published a disturbing article: the suicide rate has jumped in this country, particularly among men in their 50s (50% increase) and women in their 60s (60% increase). If you read the comments section (which I highly recommend), you will find personal accounts of people losing loved ones to suicide; these people had lost their jobs at age 50 or older and spent years fruitlessly searching for a new job, exhausting their savings. They faced a destitute old age. Death seemed the better alternative.

In the Mother Jones article Mr. Drum suggests two mechanisms for dealing with the massive unemployment we will see in the next decade or two: (a) massive redistribution through taxation so people are paid to “loaf,” or (b) the gift to every child when they are born of an equity stake in robots. This last is completely ridiculous because in no time huge enterprises would arise to steal that equity from unsuspecting young people.

Mr. Drum predicts that roboticization will eventually bring paradise, but it’s going to be a rough transition. Unions had power because workers had the leverage of withholding labor. Capitalists won’t need our labor anymore, so how do we exert power? We the people are going to have to stand up to the powerful elites now running the world somehow. Perhaps when the unemployed include large numbers of highly educated people, like engineers, lawyers, and doctors, the task of challenging the robot-owners will become much easier.

Here’s the analogy for the growth of AI: imagine that it’s 1940 and Lake Michigan has been magically drained. Now imagine that you have to fill it up following this rule: you can add water every eighteen months, starting with one fluid ounce and doubling the amount each time. That is, one ounce on Jan. 1, 1940, two ounces July 1, 1941, four ounces Jan. 1, 1943, etc. By 1950 you have added a gallon. In 1960, its 150 gallons. In 1970, it’s 16,000 gallons, about as much as a backyard swimming pool.

Fast forward to 2010. There’s maybe a few inches of water on the lake floor. Seventy years and it looks like no progress at all has been made. But that’s an illusion. In 2020 there’s 40 feet of water. In 2025 the job is done.

As Mr. Drum writes, “After 70 years you had nothing. Fifteen years later, the job was finished.”

To anyone conversant with computers, this analogy is obviously based on Moore’s Law, which states that computing power doubles approximately every 18 months. And, Mr. Drum says, he chose Lake Michigan “because its size, in fluid ounces, is roughly the same as the computing power of the human brain measured in calculations per second.”