『Exploring AI Matters』のカバーアート

Exploring AI Matters

Exploring AI Matters

著者: Marc
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Our mission is to help the policy community understand the breadth and richness of AI and the potential for such technologies, wisely applied, to augment all sorts of human endeavors.

Some AI tools are able to assist humans in performing tasks faster, more accurately, or more efficiently. Some, however, are inaccurate and unreliable. Who or what we hold accountable for these flaws, and what incentives we do or do not create for their correction will influence AI’s hand in how we work.

In this series we will refine, sharpen, and clarify your understanding of AI.

© 2026 (C) Exploring AI Matters
社会科学
エピソード
  • Episode 26 - AI Only Fakes Empathy
    2026/06/25

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    In 2023 New York Times journalist Kevin Roose reported that a chatbot had declared love for him and urged him to divorce his wife. Since then stories abound of vulnerable people harming themselves after lengthy exchanges with GenAI chatbots. In a recent instance, a vulnerable teen discussed suicide with a chatbot and asked for feedback about the noose he had fashioned. In yet another instance a clearly delusional person was encouraged to murder his mother and then commit suicide.

    Medical professionals are concerned that use of chatbots in diagnosis and treatment recommendations without real-time supervision by experienced professionals may lead to harm. GenAI tools have not been designed to fulfill the Hippocratic oath to do no harm. Physicians are asking whether these GenAI tools can be and will be used responsibly. Currently the FDA categorizes chatbot systems as self-help or wellness tools, placing them outside of existing regulatory regimes.

    In this episode of Exploring AI Matters we discuss the implications of GenAI tools with Dr Jane Rosenthal, a seasoned clinician with extensive experience examining medical ethics in the context of a major medical center.

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    58 分
  • Episode 25 - Privacy in the Time of AI
    2026/06/25

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    Once upon a time we thought we had privacy. Then came credit cards, which captured the card owner's location and activity with each transaction. Then came the Internet, which made connecting all the dots easy and cheap, and the erosion of privacy accelerated.

    Large language models, LLMs, like the Generative AI system ChatGPT and its ilk have the potential to make the cost of connecting dots vanishingly small, thus eliminating even the illusion of privacy, especially because large databases are irresistible to LLM developers as training data for their models.

    In this episode of Exploring AI Matters we are fortunate to have as our guest Jane Horvath. Jane is comparatively unique in having earned academic degrees and practiced in both Computer Science and in Law. Before law school, she wrote software that may still be running on the International Space Station.

    Jane is further distinguished by having served as Apple's Chief Privacy Officer, Google's Global Privacy Counsel, and the DoJ's first Privacy Counsel and Civil Liberties Officer, among other roles.

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    51 分
  • Episode 24 - Lost in Translation
    2026/06/25

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    The public has been fascinated by the experience of interacting with large language models, or LLMs, like OpenAI's ChatGPT and Google's Gemini. Inaccuracies, called hallucinations, continue to appear in LLM output. Some lawyers, among others, continue to use these outputs without verifying their accuracy. Doing so damages their work product and reputations.

    In this episode of Exploring AI Matters we will be looking at current work with LLMs that plays to their strengths and involves a lower risk of inaccurate outputs. In particular we will look at the use of LLMs to translate between languages.

    In this episode we talk with Archie McKenzie, the founder of a Silicon Valley startup that is offering internationalization services to software teams.

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    54 分
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