Pedagogy and the early modern syllabus

Ruth Boeker’s syllabus for teaching early modern philosophy is featured today at the Blog of the APA.

Ruth was a visiting assistant professor here in Albany several years ago, and her current practice reflects things she did here. Our campus teaching center has been a big promoter of Team-Based Learning for many years. She first encoutnered it here and recommends, as further reading on TBL for anyone interested, a pair of articles written by our local experts. (One of whom is Philosophy PhD alum Kimberly Van Orman.)

So, yay! Cheers to all.

Fallacies: Narcissan, pleonastic, and unnatural deceleration

Since February 1999, I’ve had a web page about fallacies. Rather than regurgitating all of the usual ones that one can find elaborated in critical thinking textbooks, I collect fallacies which an author names for just one occasion. These one-offs don’t appear on the usual lists. Authors usually do this to condemn some specific target, one who has committed not some generic error in reasoning but the specific if newly-named fallacy of such-and-so.

Prompted by John Holbo at Crooked Timber, I’ve added three new specimens. One is coined tongue-in-cheek by Holbo himself to mock a book review by David Bentley Hart, and the other two are coined by Hart in his would-be hatchet job on Daniel Dennett’s book From Bacteria to Bach and Back.

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Shagg Carpet would be a good name for a Shaggs cover band

via The New Yorker, I learn that the outsider rock band The Shaggs recently had a reunion just down the road from me. Writer Howard Fishman asks

Was it fair to even call this band the Shaggs? Or was it, rather, a Shaggs cover band providing a live karaoke soundtrack for the Wiggins to sing along with?

As someone who once judged a contest in which contestants tackled the question of whether a band can be its own cover band, I can’t let this pass as just a rhetorical question.

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Two links about AI

There are some articles that I read and think I ought to blog about that. Then I realize that I basically have. So this is basically a link dump kind of post.

Link #1: Geoffrey Hinton cautions that deep learning is not especially deep

I’ve written some posts¬†about the glitzy fad for “deep learning”. It has the same strengths and weaknesses it had when it traveled under the less-shiny banner of “back-propagation neural networks”.

Link #2: Efforts to understand the bias inherent in algorithms

Procedures that are superficially objective can encode bias. I don’t have anything deep to say here, but I’ve blogged about it before.