Soon a Robot Will Be Writing This Headline 1

Technology, Automation, and How We Should Respond
By Daniel Susskind

Fearing that a newfangled technology would put them out of work, neighbors broke into the house of James Hargreaves, the inventor of the spinning jenny, and destroyed the machine and also his furniture in 18th-century England. Queen Elizabeth I denied an English priest a patent for an invention that knitted wool, arguing that it would turn her subjects into unemployed beggars. A city council dictated that Anton Möller, who invented the ribbon loom in the 16th century, should be strangled for his efforts.

But centuries of predictions that machines would put humans out of work for good — a scenario that economists call “technological unemployment” — have always turned out to be wrong. Technology eliminated some jobs, but new work arose, and it was often less grueling or dangerous than the old. Machines may have replaced weavers, but yesterday’s would-be weavers are now working jobs their forefathers couldn’t have imagined, as marketing managers and computer programmers and fashion designers. Over the past few centuries, technology has helped human workers become more productive than ever, ushering in unprecedented economic prosperity and raising living standards. The American economy, for instance, grew 15,241-fold between 1700 and 2000.

But if humans’ fears that technology would replace them have been unfounded in the past, this time is different. So argues Daniel Susskind, a fellow in economics at Oxford, in his new book, “A World Without Work: Technology, Automation, and How We Should Respond.” Susskind declares that machines are getting so smart that they’ll soon replace humans at a growing list of jobs, potentially including doctors, bricklayers and insurance adjusters, thus ending what he calls the “Age of Labor.” Without some sort of intervention, he says, the inequality inherent in today’s economy will metastasize into an even greater divide between the haves and have-nots.

This argument flies against the face of much modern economic thought. As Susskind succinctly summarizes, economists largely agree that while machines have sometimes completely substituted for everything a worker does (think of elevator operators), more frequently, they complement workers’ jobs, taking over some routine and predictable tasks but in the end making workers more productive. Bank tellers feared the advent of automated teller machines, for example, but A.T.M.s actually motivated customers to use banks more, and so increased the number of bank branches and also the number of bank tellers, who were freed up to do tasks other than dispensing cash.

What’s different this time around, Susskind insists, is a new type of artificial intelligence that challenges the assumption that humans will always be better than machines at some jobs. In the past, humans programmed robots to mimic human behavior, and so robots could most easily do routine, repeatable tasks that were easily explained. That’s meant automation has mostly impacted middle-skill jobs, while unpredictable ones, like building houses or diagnosing diseases, have been relatively unaffected. But now, Susskind argues, people working at the frontiers of artificial intelligence are teaching machines to draw on vast amounts of processing power and data to solve problems in ways humans couldn’t. Thus an IBM system beat Garry Kasparov in chess not by copying his strategy, but by drawing on a database of 330 million moves in a second, and picking which ones had the highest likelihood of beating him. Future machines like this one “will open up peaks in capability well beyond the reach of even the most competent human beings alive today,” he writes.

Susskind’s thorough examples are compelling evidence that this could be a scenario in the future. A machine at Stanford can draw on a database of nearly 130,000 cases to tell whether a freckle is cancerous. A Google program can diagnose more than 50 eye diseases with an error rate better than that of many clinical experts. A Chinese insurance company uses algorithms to read facial expressions and determine whether loan applicants are being dishonest. Listeners at the University of Oregon could not tell the difference between a Bach composition and one written by a computer program.

Susskind’s predictions will likely make his book catnip to supporters of the presidential candidate Andrew Yang, whose campaign focuses on solutions to technological unemployment. But the book should be required reading for any potential presidential candidate thinking about the economy of the future. That’s because Susskind also turns to one of the biggest consequences of technological change — inequality — and what can be done about it. “Today’s inequalities are the birth pangs of tomorrow’s technological unemployment,” Susskind writes, and he has a point.

Indeed, some of the inequalities inherent in a society more dependent on technology are evident today. Where all humans could once sell their skills and services, some types of this human capital are losing value, and may soon become as worthless as Confederate money after the Civil War. Instead, prosperity is accruing to the owners of traditional capital, who have access to stocks and real estate and technology, and to people who have certain hard-to-find skills. Already, prosperity is being shared among fewer people: In 1964, AT&T, the most valuable company in the United States, had 758,611 employees; Microsoft, the most valuable company in the United States until it was recently unseated by Amazon, employs just 144,000. Instagram had just 13 employees when Facebook acquired it for $1 billion in 2012.

Susskind’s solutions to a world without work, which occupy the last third of the book, are not necessarily novel, but they are thought-provoking, especially at a time when younger generations are nurturing a growing interest in socialism. Since for-profit companies have not proved adept at sharing the fruits of their spoils — instead voiding employee ownership plans and taking advantage of loopholes to evade taxes — the state will need to take a bigger role in redistributing wealth as inequality grows, Susskind writes. In addition, he believes that the state could more efficiently tax winners and losers while creating leisure policies to help people occupy themselves in a world without work. The government could become a shareholder in valuable companies — creating what Susskind calls a citizens’ wealth fund — so the profits from the winners in today’s economy are shared among more people.

Even if Susskind’s prediction is wrong — that machines will soon render many humans irrelevant in the labor market — his book provides a useful exercise in planning for a more unequal future. The dire predictions of workers losing their jobs to machines have not come true in the past. That doesn’t mean they never will.