Being perfectly rational is not an evolutionarily viable form of reasoning. It’s slow and requires a lot of information that may not always be available.
What helps is reasoning through bias: a cognitive shortcut that is quick, doesn’t require perfect information, gets the job done, and reduces the kind of errors that have existential consequences.
Algorithms have biases too. But over time, biases have started reinforcing themselves, further disenfranchising the disenfranchised. So, what do we do about it?
We talk to Osoba Osonde, a senior information scientist, co-director of the Center for Scalable Computing and Analysis, and professor at the Pardee RAND Graduate School, to discuss how we can make algorithms fairer. We also talk to Benjamin Boudreaux, a professor at the Pardee RAND Graduate School, about what it means to make algorithms fairer.
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