Why Algorithmic Fairness is Elusive

Written by ambercazzell | Published 2019/12/06
Tech Story Tags: algorithmic-fairness | machine-learning | artificial-intelligence | ethics | tech-ethics | statistics | algorithms | hackernoon-top-story

TLDR In 2016, Google photos classified a picture of two African-Americans as ‘gorillas” Two years later, Google had yet to remove the word “gorilla” from its database of classifications. In Florida, algorithms used to recommend detention and parole decisions on the basis of risk of recidivism were shown to have a higher error rate among African-American. Protected categories often can make a meaningful impact on the behaviors that the algorithms are designed to predict. The trouble is that it’s not at all clear how to make algorithms fair.via the TL;DR App

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Written by ambercazzell | Social psychologist interested in ethical technology :)
Published by HackerNoon on 2019/12/06