Erik Brynjolfsson has a challenge for anyone worried about artificial
intelligence: Stop asking what AI will do to us, and start asking what
we will do with AI.
In this episode, the Stanford University economist explains why technology isn’t the biggest barrier to progress — people, organizations, and institutions are. Drawing on new research into AI’s impact on jobs, productivity, and economic growth, he argues that the future isn’t predetermined: It will be shaped by the choices we make today. This is a timely conversation about human agency, shared prosperity, and why the most important AI breakthroughs may have less to do with technology than with how we use it. Read the episode transcript here.
Guest bio: Erik Brynjolfsson is the Jerry Yang and Akiko Yamazaki Professor and senior fellow at the Stanford Institute for Human-Centered AI, and
director of the Stanford Digital Economy Lab. He is also the Ralph
Landau Senior Fellow at the Stanford Institute for Economic Policy
Research, 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.
A best-selling author, Brynjolfsson focuses his research on examining the effects of information technologies on business strategy, productivity and performance, digital commerce, and intangible assets.
Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder.
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This week, feuding between some of the biggest tech companies spilled into public view. We discuss Apple’s accusation that OpenAI tried to steal secrets about Apple’s hardware business, as well as share our reactions about OpenAI’s new model, Sol, and Anthropic’s decision to extend access to its model Fable.
Then, we unpack the loudest warning yet about A.I. and jobs. We talk with Erik Brynjolfsson, a Stanford economist, about a statement he helped organize that implores economists and A.I. researchers to “act now” to steer A.I. in a direction that complements humans.
And finally, we play a round of HatGPT.
Guest:
Erik Brynjolfsson, senior fellow at the Stanford Institute for Human-Centered A.I., and director of the Stanford Digital Economy Lab.
Additional Reading:
Apple Sues OpenAI, Accusing It of Stealing Company Secrets
OpenAI’s First Device Will Be Movable, Screenless Speaker Built as A.I. Companion
Nearly 200 Economists and Tech Leaders Warn of A.I. Threats
The loudest warning about A.I. and jobs yet
OpenAI Is Showing Kalshi’s World Cup Odds in ChatGPT
New York Enacts Nation’s First Statewide Moratorium on Data Centers
Brown Professor Suspects Majority of His Class Used A.I. to Cheat
MiniMax CEO Vows to Forgo Salary Until Achieving A.G.I.
Lorde Speaks Out — With Expletives — Against A.I. Glasses
Nearly 6 in 10 Young Women Get Health and Wellness Information from Influencers
Meta Removes A.I. Feature on Instagram After Days of Backlash
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We here at Marketplace love indicators that give us insights into which direction the economy is moving. But AI is evolving fast and it can be hard for the data — and the people looking to it for clues about AI's effects — to keep up. So the Stanford Digital Economy Lab, with help from the payroll firm ADP, recently launched its own AI Economic Indicators. They track things like AI adoption, productivity, and of course, jobs. Marketplace’s Meghan McCarty Carino spoke with Connacher Murphy, research manager at Stanford Digital Economy Lab, to learn more about the database and what researchers call the Canary Dashboard for jobs.
When the computer scientist Ben Zhao learned that artists were having their work stolen by A.I. models, he invented a tool to thwart the machines. He also knows how to foil an eavesdropping Alexa and how to guard your online footprint. The big news, he says, is that the A.I. bubble is bursting.
SOURCES:Erik Brynjolfsson, professor of economics at Stanford University
Ben Zhao, professor of computer science at the University of Chicago
RESOURCES:"The AI lab waging a guerrilla war over exploitative AI," by Melissa Heikkilä (MIT Technology Review, 2024)
"Glaze: Protecting Artists from Style Mimicry by Text-to-Image Models," by Shawn Shan, Jenna Cryan, Emily Wenger, Haitao Zheng, Rana Hanocka, and Ben Y. Zhao (Cornell University, 2023)
"Nightshade: Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models," by Shawn Shan, Wenxin Ding, Josephine Passananti, Stanley Wu, Haitao Zheng, and Ben Y. Zhao (Cornell University, 2023)
"A Brief History of Artificial Intelligence: What It Is, Where We Are, and Where We Are Going," by Michael Woodridge (2021)
EXTRAS:"Nuclear Power Isn’t Perfect. Is It Good Enough?" by Freakonomics Radio (2022)
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Stephen Dubner, live on stage, mixes it up with outbound mayor London Breed, and asks economists whether A.I. can be “human-centered” and if Tang is a gateway drug.
SOURCES:London Breed, former mayor of San Francisco.
Erik Brynjolfsson, professor of economics at Stanford University
Koleman Strumpf, professor of economics at Wake Forest University
RESOURCES:"SF crime rate at lowest point in more than 20 years, mayor says," by George Kelly (The San Francisco Standard, 2025)
"How the Trump Whale and Prediction Markets Beat the Pollsters in 2024," by Niall Ferguson and Manny Rincon-Cruz (Wall Street Journal, 2024)
"Artificial Intelligence, Scientific Discovery, and Product Innovation," by Aidan Toner-Rodgers (MIT Department of Economics, 2024)
EXTRAS:"Why Are Cities (Still) So Expensive?" by Freakonomics Radio (2020)
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Erik Brynjolfsson is the director of the Stanford Digital Economy Lab and professor at the Stanford Institute for Human-Centered AI. He joins Big Technology Podcast for a discussion of why our fears that artificial intelligence would take human jobs haven't yet come to fruition. We also cover how humans and AI can work together and how AI is changing work already. Stay tuned for the second half where we discuss the latest on robotic process automation and address why we're working at all in the age of machines.
Check out Prof. Brynjolfsson's paper: The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence
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Erik Brynjolfsson is an economist at Stanford. Please support this podcast by checking out our sponsors:
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EPISODE LINKS:
Erik’s Twitter: https://twitter.com/erikbryn
Erik’s Website: https://www.brynjolfsson.com/
The Second Machine Age (book): https://amzn.to/33f1Pk2
Machine, Platform, Crowd (book): https://amzn.to/3miJZ76
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OUTLINE:
Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
(00:00) – Introduction
(08:23) – Exponential growth
(12:51) – Elon Musk exponential thinking
(15:08) – Moore’s law is a series of revolutions
(20:31) – GPT-3
(22:09) – Autonomous vehicles
(29:11) – Electricity
(33:40) – Productivity
(38:47) – Why is Twitter and Facebook free?
(49:03) – Dismantling the nature of truth
(52:24) – Nutpicking and Cancel Culture
(58:39) – How will AI change our world
(1:04:40) – Existential threats
(1:06:33) – AI and the nature of work
(1:12:39) – Thoughts on Andrew Yang and UBI
(1:18:30) – Economics of innovation
(1:24:37) – Effect of COVID on the economy
(1:33:50) – MIT and Stanford
(1:38:23) – Book recommendations
(1:41:28) – Meaning of life
Is a network -- whether a crowd or blockchain-based entity -- going to replace the firm anytime soon? Not yet, argue Andrew McAfee and Erik Brynjolfsson in the new book Machine, Platform, Crowd. But that title is a bit misleading, because the real questions most companies and people wrestle with are more "machine vs. mind", "platform vs. product", and "crowd vs. core". They're really a set of dichotomies.
Yet the most successful systems are rarely all one or all the other. So how then do companies make choices, tradeoffs in designing products between humans and machines, whether it's sales people vs. chatbots, or doctors vs. AIs? How can companies combine the fundamental building blocks of businesses -- such as network effects, platforms, crowds, and more -- in a way that lets them get ahead on the chessboard against the Red Queen? And then finally, at a macro level, how do we plan for the future without falling for the "fatal conceit" (which has now, arguably flipped from radical centralization to radical decentralization) ... and just run a ton of experiments to get there?
We (Frank Chen and Sonal Chokshi) discuss all this and more with Brynjolfsson and McAfee, who also founded MIT's Initiative on the Global Economy -- and previously wrote the popular The Second Machine Age and Race Against the Machine. Maybe there's a better way to stay ahead without having to run faster and faster just to stay in place like Alice in a tech Wonderland.
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