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Alyosha - A counter recommendation engine for news feeds

There is an increasingly vibrant discussion about how the filtering algorithms behind news feeds reinforce existing biases and prejudices. As a recent comment on mathbabe.org put it:

There was a time when there were only three major news sources available to people on a daily basis and the news they provided was governed by a fairness doctrine. The segmentation that began with cable TV has increased with the internet... This segmentation leads to a situation where one’s world view is constantly reinforced making it harder for open-mindedness to prevail.

The idea behind Alyosha is - on any given subject - to provide you with a recommendation to a news article or editorial piece that you normally wouldn't see or look at, but that's at least substantial and relevant enough to have a debate about. Kind of "If you like this you'll probably won't like this but it's still worth reading".

The idea was partially inspired by Philip Tetlock's 2005 study on the accuracy of experts' predictions, distinguishing between foxes and hedgehogs (the following quote taken from The Long Now):

The ancient Greek warrior poet Archilochus coined the phrase: “The fox knows many things; the hedgehog one great thing.” The idea was later expanded by essayist Isaiah Berlin. In Tetlock’s interpretation, Hedgehogs have one grand theory (Marxist, Libertarian, whatever) which they are happy to extend into many domains, relishing its parsimony, and expressing their views with great confidence. Foxes, on the other hand are skeptical about grand theories, diffident in their forecasts, and ready to adjust their ideas based on actual events. ... Hedgehogs annoy only their political opposition, while Foxes annoy across the political spectrum, in part because the smartest Foxes cherry-pick idea fragments from the whole array of Hedgehogs.

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A counter recommendation engine for new feeds

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