Technology Might Finally Cause the ‘Great Disruption’

Relax. If you’re a fraud examiner, machine learning probably won’t eliminate your job. Probably. “In terms of your own career, the best advice I can give is to avoid doing something that’s routine and repetitive; you want to be good at something that involves engaging other people or something that involves creativity,” said Martin Ford, the Monday lunch keynoter. Ford is a futurist and author of The New York Times best-seller “Rise of the Robots: Technology and the Threat of a Jobless Future.”    

Ford says we could be on the leading edge of a massive disruption of global economies and societies — precipitated by technology — that could decimate jobs and increase fraud.

So, if you engage in say, interviewing subjects, there’s a good chance that no computer — hyped up on artificial intelligence (AI) — will replace you. But if you sit in front of a screen analyzing routine numbers, watch out.

Ford says that many experts, especially economists, are still doubtful that we’re in for high-tech disorder. The U.S. federal Ad Hoc Committee on the Triple Revolution — consisting of prominent academics, journalists and technologists — gave its report to the U.S. President that warned about the dangers of technology. The report, Ford writes in “Rise of the Robots,” predicted that “cybernation” (or automation) would soon result in an economy where “potentially unlimited output can be achieved by systems of machines [and] will require little cooperation from human beings.” The committee prepared that report in 1964. And the president who reviewed it was Lyndon Johnson. You can see why economists would suspect a crying wolf.

However, Ford believes that this time the prognostications might just come true. He says these are the different, crucial factors in technology now:

Ongoing process of exponential acceleration
“Moore’s Law says that every two years or so computers roughly double in power,” Ford said. This acceleration has been going on for decades. Since the 1950s integrated circuits, we’ve seen something like 30 doublings in computer power. “If you get into your car and start driving really slowly, like 5 mph, and you gradually double your speed to 10, to 20, to 40. If you do that just a handful of times, you’ll soon need a race track and a faster car. If you could do that 30 times, it would be something out of science fiction. You’d need some kind of space ship that we actually haven’t built yet that would be traveling billions of miles per hour. … In coming decades we’ll probably see things that astonish us.”

Machines, in a limited sense, are beginning to think
“Machines are taking on cognitive ability,” Ford said. “They’re making decisions, taking on problems, and, most importantly, they’re learning.” Ford explained that Google’s DeepMind division mastered the ancient Chinese board game, “Go,” about 10 years before most computer scientists thought it was possible. The game is extraordinarily complex — much more than chess. The number of configurations in “Go” are greater than the number of atoms in the universe, he said. No computer could be constructed to compete in “Go” as have been built to play chess. A “Go” champion says that she often uses her intuitive feelings and not her logic to compete and win. And yet, Google has designed a “system that not only taught itself through machine learning but rapidly became superhuman,” Ford said.

Information technology, including artificial intelligence, is increasingly becoming applicable for every use.
It will impact every sector and industry and become as ubiquitous as electricity.

“Many industries will be upended by technology, but at the same time there will be entirely new industries that will arise as the result of technology progress,” Ford said. But many of these new industries might not be labor-intensive. In 2012, Google, for example, generated a profit of nearly $14 billion while employing fewer than 38,000. He said at General Motors’ peak employment in 1979, the company had nearly 840,000 workers but earned only about $11 billion — 20% less than what Google earned. And that’s adjusted for inflation. GM created a lot of opportunities for average people, he says, but Google is creating far fewer jobs for just elite employees.

Ford shared that new technology is increasing productivity but is probably stifling wage increases. Those who are losing their jobs because of technology might not be able to assume the new created jobs, regardless of available retraining. The current low unemployment rates might be indicative of people taking low-wage, low-status jobs and those who have given up looking for jobs that are comparable to those they lost. Conditions like this can breed fraud, Ford advised.

The inevitable solution might be for governments to explore some type of “universal basic income” so that economies won’t have large numbers of unemployables who can’t consume and sustain healthy economies. However, Ford said, even liberal Scandinavia is having trouble implementing that type of program.

“My purpose in coming here in talking to you and also writing about it is to get you engaged and hope that you will … really think about what kind of future we’re building. … A society and economy that works for everyone at every level rather than the few people at the very top.”

The upshot? We’ll see if Ford is right, and technology might finally usher in the Great Disruption. Fraud examiners: Keep your human-interacting, creative jobs.