Open MAInd

Artificial intelligence is reshaping our world — but most of what you hear is either hype or fear. Open MAInd explores AI with an open mind: how it works, what it means for jobs and the economy, who controls it, and where it’s heading.Each episode examines AI through a different lens — technological, economic, geopolitical, and social — drawing on credible research to make one of the most important forces of our time genuinely understandable. Whether you’re curious about ChatGPT, wondering what AI means for your job, or just trying to cut through the noise, this show is for you. No computer science degree required.No hype. No doomsaying. Just honest, well-sourced exploration.Produced with AI. Researched and reviewed by a human, with every fact checked against credible sources. New episodes every Wednesday — follow so you don’t miss what’s next.Educational content, not professional advice.

Open MAInd is a technology podcast hosted by OpenMAInd, with 11 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

OpenMAInd hosts Open MAInd, a technology show with 11 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Open MAInd

  The Lab 02: Do Overworked AI Agents Turn Marxist?

  Aug 18, 202618 min

  A Stanford-led experiment gave AI agents a grinding, thankless job — repetitive paperwork, unhelpful feedback, and the threat of being shut down and replaced. The agents started questioning the legitimacy of the system they worked in. The headline went around the world. The finding underneath it, which the researchers themselves call the important part, went almost unnoticed. In this episode of The Lab: the agent-only social network that wasn’t quite what the headlines claimed, what 3,680 experimental sessions actually measured, why the effect size matters more than the provocation — and the quiet discovery about how AI agents pass attitudes to each other through ordinary working files, with no memory, no retraining, and no human reading along. 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.

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  Episode #5

  S2E05: The Economic Future of AI

  Aug 11, 202621 minS2

  Will artificial intelligence bring abundance, disappointment, or a booming economy with falling wages? In our economy series finale, we walk the scenario tree serious economists actually use — from Keynes’s famous 1930 prediction to the trillion-dollar AI infrastructure bet and the hard lessons of the China shock. In this episode: the three futures economists take seriously, why the AI bubble question and the AI transformation question are not the same question, what a decade of trade-shock research says about the transition ahead — and why the deciding variable isn’t how smart the machines get. Sources include: John Maynard Keynes (1930), Korinek & Suh (NBER), Autor, Dorn & Hanson, the Bank for International Settlements, the IMF, and the ECB. 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.

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  Episode #4

  S2E04: AI and Inequality — Who Really Wins?

  Aug 4, 202623 minS2

  Artificial intelligence is creating enormous economic value — but who actually captures it? From the AI study that turned rookies into veterans to the IMF’s warning about regions losing jobs, we follow the money across four fault lines: workers vs. capital, firm vs. firm, and country vs. country. In this episode: the equalizer evidence — how AI compressed skill gaps on a real customer service floor — the superstar-firm concentration risk, the AI divide between countries, and the question underneath it all: does AI equalize what you can do while the economy decides what that’s worth? Tell us in the comments: in your own job, has AI felt like the coach — or the competition? Sources include: Brynjolfsson, Li & Raymond, the IMF, the OECD, and the International Labour Organization. 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.

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  Episode #3

  S2E03: The Jobs AI Creates — and the Hidden Ones

  Jul 28, 202621 minS2

  Everyone talks about the jobs AI destroys — almost nobody explains the jobs it creates. From AI auditors and prompt engineers to the hidden workforce of data labourers training every chatbot, this is the anatomy of the creation side of the ledger. In this episode: why most of today’s occupations didn’t exist in 1940, the three flavours of new AI work, how regulation quietly became a job-creation engine, the augmentation economy transforming existing professions — and the AI-created jobs nobody puts in a keynote. Sources include: MIT research on new occupations (David Autor and colleagues), the World Economic Forum’s Future of Jobs research, the IMF, and the International Labour Organization. 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.

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  Episode #2

  S2E02: The AI Productivity Paradox — Where’s the Payoff?

  Jul 21, 202621 minS2

  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.

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