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59% complete! salt marsh has read 31 of 52 books.
I keep being frustrated that Pariser seems to take for granted that various recommendation algorithms, machine learning models, etc all work well as intended. The ways in which they extremely do not work are really important!
Nearly all geek cultures are structured as an empire of clever wherein ingenuity, not charisma, is king. The intrinsic efficiency of a creation is more important than how it looks. Geek cultures are data driven and reality based, valuing substance over style.
next you're going to tell me a cis white guy wrote this
I guess this is a normal thing in this type of nonfiction but I find it very irksome
This book keeps starting chapters with long anecdotes about things like a Soviet spy defecting, or how adderall works, which do not explain anything about how computers work, and then basing broad statements about how computers effect the brain on them
Jeff Bezos, the CEO of Amazon.com, was one of the first people to realize that you could harness the power of relevance to make a few billion dollars.
I would argue that recommendation algorithms pale in comparison to monopolistic business practices, labor exploitation, and corporate tax evasion in the role it plays in making Bezos a billionaire.
I guess I also wish, more generally, that we were more explicit when talking about the efficacy of recommendation algorithms, that they inherently can only recommend to you within their own content, and contextualized what a successful the recommendation means, specifically.
...at this point, Netflix can predict how much you'll like a given movie within about half a star.
I'm curious where this conclusion comes from? The wording makes the claim a little nonsensical, but it sounds like it's based on actually metrics about how people (in 2011) responded to netflix's recs? But there must be an unstated assumption here about how much prior use the user has on which the recommendation is made.
I also wonder how well this holds up today, when streaming video is so fragmented. Netflix has basically none of the movies I like on it, so it does a very poor job if recommending them to me.