Sign up to save your podcasts
Or
Share S2E02: The AI Productivity Paradox — Where’s the Payoff?
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
S2E02: The AI Productivity Paradox — Where’s the Payoff?
Trillions are being spent on the promise that AI will make us more productive — so why are the economic statistics nearly silent? From Robert Solow’s famous 1987 one-liner to the electric dynamo that took decades to pay off, we unpack the AI productivity paradox and the diffusion race that will decide who wins the AI economy.
In this episode: why general-purpose technologies pay off twice, what randomised trials of AI coding assistants actually measured, the honest case from the skeptics — including MIT economist Daron Acemoglu’s arithmetic — and the US Census data showing how few businesses truly use AI today.
Sources include: Paul David (American Economic Review), Brynjolfsson, Rock & Syverson, Daron Acemoglu (NBER), the OECD, and the US Census Bureau.
Open MAInd is created with the help of AI tools, including AI-generated voices. Educational content, not professional advice.
Open MAInd is for educational and informational purposes only and does not constitute professional advice. While we strive for accuracy and verify against credible sources, we make no warranty that all content is error-free.
View all episodes
By OpenMAIndTrillions are being spent on the promise that AI will make us more productive — so why are the economic statistics nearly silent? From Robert Solow’s famous 1987 one-liner to the electric dynamo that took decades to pay off, we unpack the AI productivity paradox and the diffusion race that will decide who wins the AI economy.
In this episode: why general-purpose technologies pay off twice, what randomised trials of AI coding assistants actually measured, the honest case from the skeptics — including MIT economist Daron Acemoglu’s arithmetic — and the US Census data showing how few businesses truly use AI today.
Sources include: Paul David (American Economic Review), Brynjolfsson, Rock & Syverson, Daron Acemoglu (NBER), the OECD, and the US Census Bureau.
Open MAInd is created with the help of AI tools, including AI-generated voices. Educational content, not professional advice.
Open MAInd is for educational and informational purposes only and does not constitute professional advice. While we strive for accuracy and verify against credible sources, we make no warranty that all content is error-free.