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Today, we are featuring a discussion with Mike Selmi, an employment law professor and expert in algorithmic decision-making as it applies to hiring practices.
An algorithm is only as good as the people who program it and the data it analyzes. With the rise of algorithmic decision making in the hiring process has come concern in the legal community that those algorithms may be biased.
In reviewing what has been written on this topic, Selmi found plenty of concern to that effect. But then he analyzed what was actually happening, and that’s not what he found. “I haven’t seen anything that would suggest that algorithms have been more biased than humans. I suppose it could happen,” he says.
In fact, he says, “Between a computer and humans, trying to figure out which is going to be less biased, I would go with the computer.”
In this interview, Selmi walks us through the challenges of deciding which data to use, how something as simple as a name can throw off equity and how he didn’t choose employment law but is grateful it was chosen for him.
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