『Thinking Out Loud: Dispatches on AI and Higher Education』のカバーアート

Thinking Out Loud: Dispatches on AI and Higher Education

Thinking Out Loud: Dispatches on AI and Higher Education

著者: Sam Jay
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Thinking Out Loud is a podcast about AI and higher education, hosted by Sam Jay and Larry Sampler from Metropolitan State University of Denver. Each episode is a real-time conversation about what generative AI is doing to universities, what it is asking of faculty and staff, and what the work of leading through it actually looks like from the inside.

This is not a show about AI hype or AI fear. It is a show about figuring it out. Sam and Larry lead MSU Denver's AI strategy and serve as advisors to the university's senior leadership team. Together they walk through the conversations, decisions, and unresolved questions that come with building AI capacity at a public, open-access university.

If you work in higher education, lead an AI initiative, or are trying to make sense of where this is all going, subscribe and send us the questions you are stuck on.

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経済学
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  • Andy Masley on Getting the AI-Related Words -and Numbers- Right
    2026/10/04

    Episode 4 welcomes Andy Masley, the independent writer and researcher behind one of the most widely read Substacks applying careful, numbers-first thinking to AI. A former high school Physics teacher with a background in philosophy, Masley has built a following by taking the claims everyone repeats and checking if they hold up.

    Dr. Samuel Jay and Larry Sampler begin with language itself. Masley argues that the two dominant framings of AI like "it is just a tool" and "it cannot really think because it is not human," are both broken, and that the metaphors we reach for quietly shape policy, teaching, and who gets held accountable. From there the conversation moves into harder territory: what interpretability research can and cannot tell us about what is happening inside a model, why visible chain-of-thought reasoning may be fading, and why "it just predicts the next word" badly misleads people about what these systems do.

    The back half turns to Masley's signature beat: AI and the environment. He walks through why the viral "a bottle of water per prompt" figure is wrong by roughly two orders of magnitude, where the real concerns actually sit (the green-energy transition, local gas turbines, electricity prices), and why contextless big numbers tell you nothing about any industry. Along the way: the higher-education cheating crisis, the geopolitics of whose values get trained into frontier models, the unglamorous work of fixing broken business practices before automating them, and a closing tour through effective altruism.

    A wide-ranging, occasionally unnerving hour about thinking more clearly.

    Check out Andy's Substack. It's a must-read, especially if you're playing a part in AI-related decision-making.

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    1 時間 18 分
  • We're Excited... And Exhausted
    2026/08/06

    In this episode of Thinking Out Loud, recorded on-site at the Ai4 Conference in Las Vegas, Sam and Larry sit down with Kevin Taylor, Chief Information Officer, and Mike Hart, Chief Information Security Officer, at MSU Denver. Together, we explore what it means to lead institutional IT and cybersecurity at a moment when advanced AI has moved out of the labs and into daily campus life. Kevin and Mike share how their thinking has shifted, where the real tensions sit between innovation and governance, and what it takes to balance faculty, staff, and student demand for AI access with the realities of maintaining a complex enterprise environment.

    Links mentioned during the interview:

    • Colorado Higher Ed Computing Organization (CHECO)
    • Terms of Service, Didn't Read
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    58 分
  • How To Eat an Elephant
    2026/06/18

    In episode three of Thinking Out Loud, Sam Jay and Larry Sampler recap their presentation to the MSU Denver Board of Trustees, subsequent discussion, and the work to be done over the summer as faculty, staff, and students prepare for a new academic year.

    Have any question, comments, ideas, or feedback? Email us at ai@msudenver.edu.

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    57 分
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