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Parable of the Polygons - a playable post on the shape of society
This is a story of how harmless choices can make a harmful world.

These little cuties are 50% Triangles, 50% Squares, and 100% slightly shapist. But only slightly! In fact, every polygon prefers being in a diverse crowd:
games  society  visualization  racism  diversity  bias  game  segregation  simulation  ghetto  ghettoisation 
17 hours ago by kybernetikos
Keep Your Identity Small
More generally, you can have a fruitful discussion about a topic only if it doesn't engage the identities of any of the participants. What makes politics and religion such minefields is that they engage so many people's identities. But you could in principle have a useful conversation about them with some people. And there are other topics that might seem harmless, like the relative merits of Ford and Chevy pickup trucks, that you couldn't safely talk about with others.

The most intriguing thing about this theory, if it's right, is that it explains not merely which kinds of discussions to avoid, but how to have better ideas. If people can't think clearly about anything that has become part of their identity, then all other things being equal, the best plan is to let as few things into your identity as possible. [2]

Most people reading this will already be fairly tolerant. But there is a step beyond thinking of yourself as x but tolerating y: not even to consider yourself an x. The more labels you have for yourself, the dumber they make you.
identity  culture  philosophy  politics  religion  *****  bias 
yesterday by gpe
Simpson's paradox - Wikipedia
Simpson's paradox, or the Yule–Simpson effect, is a phenomenon in probability and statistics, in which a trend appears in different groups of data but disappears or reverses when these groups are combined. It is sometimes given the descriptive title reversal paradox or amalgamation paradox.[1]

statistics  paradox  probability  average  bias 
yesterday by hellsten
Machine learning is racist because the internet is racist | The Outline
Deep learning algorithms are often trained on data from the web, and their biases are getting hard to ignore
bigdata  ethics  racism  bias  algorithms  artificialintelligence 
7 days ago by jorgebarba

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