It’s ML, not magic: machine learning can be prejudiced

July 30, 2016 Of the many misconceptions about machine learning, the idea that they can’t be prejudiced is likely the most harmful. As stated by Moritz Hardt in How big data is unfair, machine learning is not, by default, fair or just in any meaningful way. Even though many researchers and practitioners have noted this repeatedly in the past, the message is still lost. It’s not uncommon to hear variations of “algorithms don’t have in-built bias” even when there is an entire field of research dedicated to fighting that very issue. To make this clearer, prejudice in machine learning will haunt us for years to come. Prejudice in machine learning is like security in programming. No-one will notice the underlying issues until it’s obvious something is horribly wrong. By the…


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