FB's algorithmic mind-steering has only one stable attractor: extreme radicalization.https://twitter.com/oneunderscore__/status/1451681699629260801 …
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"an attractor is a set of states toward which a system tends to evolve, for a wide variety of starting conditions of the system"
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The whataboutist reactions to this observation are... dumb. "This fast food chain's irresponsibly-managed operations have led to a worldwide salmonella outbreak" "Yeah but what about this restaurant you patronized once that gave someone diarrhea in 2016"
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The fast food chain: "our mission of Feeding People is good for the world"
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End of conversation
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Are these just really higher order versions of nonlinear attractors? So they've got a nonlinear system with regions of attraction that are grouping via the recommendation algo. Should they just force the algo to dip from all of the attractor groups to provide more perspective?
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Do any of these FB's algorithmic attractors use libraries and frameworks with which you have worked?
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