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Machines don’t necessarily fix our biases, they mirror them.

"Alexandria Ocasio-Cortez recently began sounding the alarm about the potential pitfalls of using algorithms to automate human decisionmaking. In an interview, the newly elected representative pointed out a fundamental problem with AI: 'Algorithms are still made by human beings... if you don’t fix the bias, then you are just automating the bias.'

"In a joint study at the Center for Research on Equitable and Open Scholarship at MIT Libraries and the Berkman Klein Center for Internet & Society at Harvard University, we analyzed a number of common approaches to making algorithms less biased. We found that many of the most widespread approaches do little to address inequality.

"Given these legitimate concerns," write Alexandra Wood and Micah Altman, "we should expect the creators of algorithms to explain their design choices, share data on the consequences of these choices, and continually monitor how their algorithms affect different groups of people, particularly vulnerable groups. We should not trust an algorithm unless it can be reviewed and audited in meaningful ways."

Read more in The Hill...

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Aug 3, 2018

A Harm-Reduction Framework for Algorithmic Fairness

Any evaluation of algorithmic fairness must consider a counterfactual analysis of the effects that algorithmic design, implementation, and use have on the well-being of… More