New research shows that people recognize more of their biases in algorithms' decisions than they do in their own -- even when those decisions are the same.
New research shows that people recognize more of their biases in algorithms' decisions than they do in their own -- even when those decisions are the same.
But that same year, just 39 percent of Amazon's workforce were women. If the algorithm had been trained on Amazon's existing hiring data, it's no wonder it prioritized male applicants -- Amazon already was. If its algorithm had a gender bias,"it's because Amazon's managers were biased in their hiring decisions," Morewedge says.structural biases in our society," he says."Many biases cannot be observed at an individual level.
In the second half of the experiment, participants were told about a research finding that explained how the host's race might bias the ratings. Then, the researchers showed participants a set of ratings and asked them to assess how likely it was that bias had influenced the ratings. Morewedge attributes this to the different evidence we use to assess bias in others and bias in ourselves. Since we have insight into our own thought process, he says, we're more likely to trace back through our thinking and decide that it wasn't biased, perhaps driven by some other factor that went into our decisions. When analyzing the decisions of other people, however, all we have to judge is the outcome.
This is the crucial step for Morewedge and his colleagues, he says. For anyone motivated to reduce bias, being able to see it is the first step. Their research presents evidence that algorithms can be used as mirrors -- a way to identify bias even when people can't see it in themselves. Although most decisions in life are made by individuals themselves, many are influenced by others such as principals, managers, parents or colleagues. New research finds that women take part in ...
Consumer Behavior Gender Difference Perception Computer Programming Software Neural Interfaces Computers And Internet
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