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Mind Matters

Mind Matters

De: Discovery Institute Center on Natural and Artificial Intelligence
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On the Mind Matters podcast, Discovery Institute’s Walter Bradley Center for Natural and Artificial Intelligence considers the implications and misconceptions, the opportunities and limitations, and the applications and challenges presented by intelligent agents and their algorithms. Episode notes and archives available at mindmatters.ai/podcast.© Discovery Institute Ciencias Sociales Filosofía
Episodios
  • Science, God, and Truth: Michael Shermer and Michael Egnor

    Science, God, and Truth: Michael Shermer and Michael Egnor
    Apr 2 2026
    On this episode of the Mind Matters News podcast, host and neurosurgeon Dr. Michael Egnor welcomes Michael Shermer, historian of science and founder of Skeptic magazine, to discuss Shermer’s new book Truth: What It Is, How to Find It, and Why It Still Matters. The conversation quickly evolves into a deep philosophical debate between Egnor and Shermer over whether truths about morality and the universe are created by humans or discovered as objective features of reality.

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    1 h y 10 m
  • Why Logic and Cognition Set Us Apart from Machines

    Why Logic and Cognition Set Us Apart from Machines
    Mar 21 2026
    Is consciousness the exclusive domain of human beings? Proponents of a view known as integrative information theory argue that AI will eventually achieve that same level of consciousness as systems build up and integrate more knowledge in the future. On this archive episode of Mind Matters News, guest host Pat Flynn welcomes Dr. Selmer Bringsjord to discuss some of the flaws in this theory as well as a possible alternative.

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    1 h y 12 m
  • Beyond Imitation: Testing for True Artificial General Intelligence

    Beyond Imitation: Testing for True Artificial General Intelligence
    Mar 4 2026
    On this episode of the Mind Matters News podcast, join host Robert J. Marks as he sits down with Dr. Giorgios Mappouras for a deep dive into the philosophical and technical boundaries that define the gap between human minds and silicon machines. The pair look at why the classic Turing Test is no longer a sufficient measure of machine intelligence in the age of large language models. They explore Giorgio's proposal for a more rigorous framework that can better evaluate AI's abilities.

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    1 h y 36 m
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