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 ===AI overreach===
-The magic of sufficiently advanced technologies like artificial intelligence induces us to look too far ahead. We see an AI art generator and immediately conclude that the highest order of human intellectual achievement is at stake. Not only does reducing art to “[[Bayesian prior]]s” stunningly miss the point about art — in a strangely artificially intelligent way, ironically — but it is to skip over all the easier, drearier, more machine-like tasks with which the human intellect is still burdened, got which there is apparently no technological resolution in sight. Machines that can fold washing, remember where you put the car keys, weed out fake news, and wipe down the kitchen table. Imagine a machine that could search through all the billions of books and recordings and surface the undiscovered genius, to give the Bayesian priors a chance?
+The magic of sufficiently advanced technologies, like [[artificial intelligence]], induces us to look too far ahead.
-''This is not just the Spotify algorithm'', as occasionally delightful as that is. That has its own revenue maximisation as it's primary goal, and reader enlightenment is an occasional by product. That will serve up the reader’s personal “[[cheesecake for the brain]]”. Per Anita elberse’s {{br|The Blockbuster Effect}} commercial algorithms have had the counter-intuitive effect of ''truncating'' the [[long tail]] as envisioned by Wired’s Chris Anderson. A sensible use for this technology would ''extend'' it.
+We see an AI art generator and immediately conclude that the highest order of human intellectual achievement is at stake. Not only does reducing art to “[[Bayesian prior]]s” stunningly [[Symbol processing|miss the point]] about art — in an artificially intelligent way, ironically — but it skips over all the easier, drearier, more machine-like applications to which machines might profitably put, but with which the poor inconstant human is still burdened. For these mundane but potentially life-changing tasks there is, apparently, no technological resolution in sight: machines that can fold washing, remember where you put the car keys, weed out fake news, and wipe down the kitchen table,wipe a baby’s arse.
+Okay, these require motor control and interaction with the irreducibly messy [[off-world|real world]], so there are practical barriers to progression. But other such facilities would not: imagine a machine that could search through all the billions of books, recordings and artworks that humanity has created, and surface the undiscovered genius, to give its [[Bayesian prior]]s a fighting chance?
+''This is not just the Spotify algorithm'', as occasionally delightful as it is. That has its own agenda: revenue maximisation for Spotify is its primary goal, and reader enlightenment is an occasional by-product, where the two intersect. That will tend to serve up populist mush: the reader’s personal “[[cheesecake for the brain]]”. Per {{author|Anita Elberse}}’s {{br|The Blockbuster Effect}}, commercial algorithms, targeted primarily at revenue optimisation, have had the counter-intuitive effect of ''truncating'' the “[[long tail]]” of consumer choice Wired’s Chris Anderson famously envisioned it. A sensible use for this technology would ''extend'' it.
 This would be a personal LLM, private to the user, free, therefore, of data privacy concerns, that would pattern-match purely by reference to the user’s actual reading habits, instructions and the recommendations of like-minded readers. This algorithm would be tasked with ''diversifying'' — finding undiscovered works — rather than ''converging'' — gravitating towards common, popular, commercially promoted ones.