5 unexpected sources of bias in artificial intelligence

Kristian Hammond Crunch Network Contributor As chief scientist and co-founder, Kris focuses on R&D at Narrative Science. Kris is also a professor of computer science at Northwestern University. How to join the networkWe tend to think of machines, in particular smart machines, as somehow cold, calculating and unbiased. We believe that self-driving cars will have no preference during life or death decisions between the driver and a random pedestrian. We trust that smart systems performing credit assessments will ignore everything except the genuinely impactful metrics, such as income and FICO scores. And we understand that learning systems will always converge on ground truth because unbiased algorithms drive them. For some of us, this is a bug: Machines should not be empathetic outside of their rigid point of view. For others,…


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