Artificial Intelligence and the Future of Work
I took three Waymo rides this month while in San Francisco for an economics conference. The smooth trips made for a haunting vision of the potential future of artificial intelligence. Inside the cabs, there was gentle New Age music and no one in the driver’s seat.
Such could be the future of the economy in general if artificial intelligence substitutes for human labor in more and more occupations. The unemployed masses could come to depend on the charity of billionaires and trillionaires who own the means of intellectual production.
But A.I. could also be designed to empower people rather than replace them, as I wrote a year ago in a newsletter about the M.I.T. Shaping the Future of Work Initiative.
The Future of A.I. and Work
Which of those A.I. futures will be realized was a big topic at the San Francisco conference, which was the annual meeting of the American Economic Association, the American Finance Association and 65 smaller groups in the Allied Social Science Associations.
Erik Brynjolfsson of Stanford was one of the busiest economists at the conference, dashing from one panel to another to talk about his hopes for a human-centric A.I. and his warnings about what he has called the “Turing Trap.”
The Turing Trap
Alan Turing, the English mathematician and World War II code breaker, proposed in 1950 to evaluate the intelligence of computers by whether they could fool someone into thinking they were human. His “imitation game” led the field in an unfortunate direction, Brynjolfsson argues — toward creating machines that behaved as much like humans as possible, instead of like human helpers.
A Human-Centric Approach
Henry Ford didn’t set out to build a car that could mimic a person’s walk, so why should A.I. experts try to build systems that mimic a person’s mental abilities? Brynjolfsson asked at one session I attended.
Other economists have made similar points: Daron Acemoglu of M.I.T. and Pascual Restrepo of Boston University use the term “so-so technologies” for systems that replace human beings without meaningfully increasing productivity, such as self-checkout kiosks in supermarkets.
The Need for Education and Training
People will need a lot more education and training to take full advantage of A.I.’s immense power, so that they aren’t just elbowed aside by it. “In fact, for each dollar spent on machine learning technology, companies may need to spend nine dollars on intangible human capital,” Brynjolfsson wrote in 2022, citing research by him and others.
A Big Question
A big question is who will pay for all that education. Employers fear that if they train their work force, the employees might take their in-demand skills to a competitor. And the workers may not be able to afford it on their own. This implies, Brynjolfsson wrote, that governments “should directly provide this training or provide incentives for corporate training.”
Conclusion
The future of artificial intelligence and its impact on work is a topic of great concern. While there is a risk that A.I. could substitute for human labor and lead to unemployment, it is also possible that A.I. could be designed to empower people and make their lives easier. The key is to create a human-centric approach to A.I. development, one that focuses on building systems that assist and augment human capabilities rather than replacing them.
FAQs
Q: What is the Turing Trap?
A: The Turing Trap refers to the idea that A.I. development has focused too much on building machines that mimic human intelligence, rather than building systems that assist and augment human capabilities.
Q: What is a human-centric approach to A.I.?
A: A human-centric approach to A.I. focuses on building systems that assist and augment human capabilities, rather than replacing them. This approach prioritizes the well-being and empowerment of humans, rather than just seeking to build intelligent machines.
Q: Who will pay for education and training in the age of A.I.?
A: The cost of education and training in the age of A.I. is a big question. Employers may need to spend more money on training their workers, and governments may need to provide incentives for corporate training or directly provide education and training themselves.
