Here’s the latest edition of Mini-Heap—10 recent items from the Daily Nous Heap of Links, our regularly updated list of material from around the web that philosophers may want to check out.

(The Heap of Links consists partly of suggestions from readers; if you find something online that you think would be of interest to the philosophical community, please send it in for consideration for the Heap.)

  1. The significance of philosophy to mathematics — Richard Zach (Calgary) points to good account
  2. “What could a philosopher have to offer a modern business?” — Scotty Hendricks covers some real-world examples
  3. “Epistemic bubbles are rather ramshackle; they go up easily, and they collapse easily, too. Echo chambers are far more pernicious and far more robust” — a fascinating look at the social and psychological elements of our epistemic situation and its discontents, from C. Thi Nguyen (Utah Valley)
  4. The call for a new academic discipline: Machine Behavior — we need to study not only machines’ source code and architecture, but also ethics, social effects, and the “opacity caused by complexity”
  5. Top 5 philosophy TAs ranked by how cool their leather jackets are — “You just know anybody who pops that baby on in the morning can really break down Plato’s Allegory of the Cave in a way that a freshman business major trying to fulfill their humanities requirement can really ‘get.'”
  6. The Blog of the APA begins new interview series on diversifying the philosophical canon — first up: Peter Adamson (LMU)
  7. What makes heavy metal music *heavy*? — Jay Miller (Warren Wilson College)
  8. The impact of artificial intelligence: a new era? — interviews with Luciano Floridi (Oxford), Huw Price (Cambridge), and others
  9. “Look, we find ourselves living under certain kinds of pressures to make the world sensible to ourselves. How much and what kind of theory do we need?” — a lengthy interview with Bernard Williams (published in Cogito in 1994)
  10. “When you think a sentence in your head, your brain sends signals to your mouth and jaw. MIT Media Lab’s headset reads those signals with 92 percent accuracy” — more “mind-reading” technology
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