> When do you start with biased data? In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. "What are you

> When do you start with biased data? In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. "What are you doing?", asked Minsky. "I am training a randomly wired neural net to play Tic-Tac-Toe" Sussman replied. "Why is the net wired randomly?", asked Minsky. "I do not want it to have any preconceptions of how to play", Sussman said. Minsky then shut his eyes. "Why do you close your eyes?", Sussman asked his teacher. "So that the room will be empty." At that moment, Sussman was enlightened. (from: http://catb.org/jargon/html/koans.html#id3141241 http://catb.org/jargon/html/koans.html#id3141241 ) There is always bias (and other types of error) in data. There is even bias in the choice of which data to use and the type of analysis to perform. If you think that this isn't a problem, you should really read about practices like "redlining"[1]. For many decades segregation was (and still is) enforced by opaque "loan approval" methods that just happened to always deny loans to blacks. [1] http://www.theatlantic.com/magazine/archive/2014/06/the-case-for-reparations/361631/ http://www.theatlantic.com/magazine/archive/2014/06/the-case...