Template:M intro technology rumours of our demise: Difference between revisions

It isn’t hard to imagine how this might work. A rudimentary version exists in {{Plainlink|https://www.librarything.com/|LibraryThing}}’s recommendation engine. It isn’t even wildly clever '''—''' {{Plainlink|https://www.librarything.com/|LibraryThing}} has been around for nearly twenty years and doesn’t even use AI: each user lists, by ASIN, the books in her personal library. She can rate them, review them, and the LibraryThing algorithm will compare each users’s virtual “library” with all the other user libraries on the site and returns to you the users with the most similar libraries to yours.  

The effect is really quite uncanny. The non-matched books from libraries of similar users are often a revelation. My closest match is a user called eggnog2085 I share 62 books in common with her, out of 4,000 of hers, and 843 of mine. I can browse her books by cover, as if I am in a library, and see I find pretty much every book is interesting. The ones we have in common are among my absolute favourites. Her interests extend in different directions '''—''' more political history, But this is scratching the surface.  

This role — seeking out delightful new human endeavours — would be a valuable role ''that is quite beyond the capability of any group of humans'' and which would not devalue, much less usurp the value of human intellectual capacity. Rather, it would ''empower'' it.

''This'' is a suitable application for artificial intelligence. This would respect the division of labour between human and machine.

Note also the [[system effect]] it would have: it would encourage people to create unique and idiosyncratic things. It would distribute wealth and information — that is, [[strength]], not [[Power structure|power]] — ''along'' the curve of human diversity, rather than concentrating it at the top.

About that “[[division of labour]]”. When it comes to mechanical tasks, machines — especially [[Turing machine]]<nowiki/>s — scale very well, while humans scale very badly. “Scaling” when we are talking about computational tasks means doing them over and over again, in series or parallel, quickly and accurately. Each operation can be identical; their combined effect astronomical. Of course machines are good at this: this is why we build them. They are digital: they preserve information indefinitely, however many processors we use, with almost no loss of fidelity.

But when it comes to imaginative uses of information we associate with the mind, humans scale magnificently. Here what we look for in “scaling” is very different. We don’t want identical, digital, high-fidelity duplication. Ten thousand copies of ''Finnegans Wake'' contribute no more to the human canon than does one.<ref>Or possibly, even ''none'': wikipedia tells us that, “due to its linguistic experiments, stream of consciousness writing style, literary allusions, free dream associations, and abandonment of narrative conventions, ''Finnegans Wake'' has been agreed to be a work largely unread by the general public.”</ref> Multiple humans contribute precisely that difference in perspective: a complex community of readers can, independently parse, analyse, explain, narratise, extend, criticise, extrapolate, filter, amend, correct, and improvise the information and each others’ reactions to it. This community of expertise is what Sam Bankman-Fried overlooks in his dismissal of Shakespeare’s “[[Bayesian prior|Bayesian priors]]” creates its own intellectual energy and momentum. No matter how fast it pattern-matches in parallel processes, artificial intelligence can’t do this.