Erik Brynjolfsson Discusses Why Robots Have Not Taken Our JobsPublication Date: December 22, 2022 5 minute read
“We are far from developing an AI-based general intelligence that can do most tasks that humans can do,” said Stanford Professor Erik Brynjolfsson on the Big Technology Podcast. He went on to say that while he does not see robots taking our jobs, artificial intelligence-based systems (AI) will shift the demand for labor and lead to economic restructuring.
Professor Brynjolfsson is Director of the Stanford Digital Economy Lab and Professor at the Stanford Institute for Human-Centered AI. His research examines the effects of information technologies on business strategy, productivity and performance, digital commerce, and intangible assets. He is the author of nine books including, with co-author Andrew McAfee, best-seller The Second Machine Age: Work, Progress and Prosperity in a Time of Brilliant Technologies.
Discussing “Wait, The Robots Didn't Take Our Jobs?” with Big Technology Podcast host Alex Kantrowitz, Professor Brynjolfsson also talked about how humans and AI can work together, and how AI is already changing work.
Below is an overview of the podcast, “Wait, The Robots Didn't Take Our Jobs?” with Professor Erik Brynjolfsson and Alex Kantrowitz. Recorded June 4, 2022.
Artificial intelligence-based systems (AI) will shift the demand for labor and lead to economic restructuring. Policy choices made over the next decade will determine whether new technologies increase prosperity for all.
- Key questions include the extent to which technology is causing changes in the economy, and what we can do to shape changes that lead to better outcomes.
- Deep learning techniques enable machine learning-based systems to do many tasks they have not previously been about to do; however, we are far from developing an AI-based general intelligence that can do most tasks that humans can do.
- For each job, AI can do some tasks better, but AI cannot not do all the tasks needed for any occupation, even for vulnerable jobs like radiologist; AI is unlikely to cause mass unemployment.
- AI will lead to substantial economic restructuring, as it will shift demand for certain skills; our focus should be on retraining and redeployment of workers.
- For jobs that involve substantial repetitive rote work, median wages are stagnating.
- Some workers might need income support, but not Universal Basic Income.
- Technology has a greater effect on wage structure than tax structure or globalization.
- The next wave of technology-related change will disproportionately affect low-skilled and middle-skilled workers, including bookkeepers, radiologists, and airline pilots.
- Using technology to replicate what humans already do will not significantly increase prosperity; progress comes from using technology to augment what humans do, allowing us to do new things.
- Use of technology to automate existing jobs leads to lower wages for workers and more income for capital owners.
- Use of technology to do entirely new things tends to raise wages and creates more widely shared prosperity.
- U.S. taxes on capital owners are low, while taxes on workers are high, creating excessive incentives for automation; alternately, policymakers could encourage technologies that augment human capacity rather than those that replace existing workers.
- Technological advances will not automatically benefit everyone; they can be used to create more prosperity and freedom, or can be used to concentrate wealth and reduce freedom.
- Today’s tools are more able to change the world than ever before, and policy choices over the next five or ten years will decide whether we are on the right path.
AI-based systems perform tasks they were never able to do before. However, analysis of tasks performed by human workers reveals that even jobs considered vulnerable to automation include tasks that AI cannot do. AI is unlikely to result in mass unemployment. AI will cause economic restructuring as the demand for some tasks declines. To help workers adapt, policymakers could consider retraining and income support. Also, policymakers could change tax policies that encourage firms to substitute technology for workers. Prosperity comes mainly from technologies that allow humans to do entirely new things, not from use of technologies that merely replace workers in existing tasks. Policy choices over the next decade will determine whether AI creates more prosperity and freedom, or less.
Listen to the Big Technology Podcast episode with Professor Erik Brynjolfsson, “Wait, The Robots Didn't Take Our Jobs?” Recorded June 4, 2022.
“The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence”
by Erik Brynjolfsson (Dædalus, Spring 2022)
From the Introduction
The promise and the peril of achieving human-like artificial intelligence (HLAI): building machines designed to pass the Turing Test and other, more sophisticated metrics of human-like intelligence. On the one hand, it is a path to unprecedented wealth, increased leisure, robust intelligence, and even a better understanding of ourselves. On the other hand, if HLAI leads machines to automate rather than augment human labor, it creates the risk of concentrating wealth and power. And with that concentration comes the peril of being trapped in an equilibrium where those without power have no way to improve their outcomes, a situation I call the Turing Trap.
Erik Brynjolfsson is the Jerry Yang and Akiko Yamazaki Professor and Senior Fellow at the Stanford Institute for Human-Centered AI (HAI), and Director of the Stanford Digital Economy Lab. He also is the Ralph Landau Senior Fellow at the Stanford Institute for Economic Policy Research (SIEPR), Professor by Courtesy at the Stanford Graduate School of Business and Stanford Department of Economics, and a Research Associate at the National Bureau of Economic Research (NBER). Professor Brynjolfsson’s research examines the effects of information technologies on business strategy, productivity and performance, digital commerce, and intangible assets. One of the most-cited authors on the economics of information, Professor Brynjolfsson was among the first researchers to measure productivity contributions of IT and the complementary role of organizational capital and other intangibles.
About Erik Brynjolfsson
Erik Brynjolfsson is the Jerry Yang and Akiko Yamazaki Professor and Senior Fellow at the Stanford Institute for Human-Centered AI (HAI), and Director of the Stanford Digital Economy Lab. He also is the Ralph Landau Senior Fellow at the Stanford Institute for Economic Policy Research (SIEPR), Professor by Courtesy at the Stanford Graduate School of Business and Stanford Department of Economics, and a Research Associate at the National Bureau of Economic Research (NBER).