Hacker Cinema
A Class Divided
1985 · Film · documentary · 53 min
Directed by William Peters
William Peters follows up on the 1970 TV documentary Eye of the Storm about Jane Elliott's experiment of dividing an otherwise homogenous group of school kids by their eye color. The episode intercuts footage from Eye of the Storm with new footage of the students, who are now adults. The film takes us through the journey of a young class learning the unfairness of racism. Elliot teaches the lesson through eye color and different treatment. All of the students admit that this is wrong. In footage of the students as adults, we are able to see how this shaped the experiment changed their lives.
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I've often heard fans of AI[1] claim that a benefit of machine-based evaluations is the removal of human bias. The machine applies the rules consistently, while humans allow race, sex, religion, politics, eye-color[2], etc to bias their decisions, often without knowing the bias even exists.
This sounds great at first, but it's really just moving the problem around. Instead of many individuals making their own biased decisions, we get a uniform application of the biases of whoever designed the AI. They still may not realize how their biases influence the design process, so it's easy to think that the AI is somehow "neutral".
This is particularly bad because it removes locality from the decision process. While the fallible humans sometime inject their own racism/sexism/etc, the freedom to make those mistakes also gave them the power to fix problems that were never included in the "official policy".
Decision by remote algorithm is really just another type of central planning, and I expect it to have the same inability to respond to local conditions that cause a lot of the problems in the traditional communist states.
[1] usually combined with a new type of data collection (surveillance-as-a-business-model)
[2] biases that are often taught socially: http://www.pbs.org/wgbh/frontline/film/class-divided/