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Artificial Intelligence: The Difficult Task of Taking the Bias out of Algorithms
Algorithms are increasingly being used score, rank and screen just about everything. Algorithms scan resumes, credit applications, housing applications and more. They have a say in which school your child may attend and which product advertisements and even product pricing that you’ll be offered.
The charge is that algorithms often filter out or discriminate against applicants because of factors like gender and race. Algorithms follow the directives of how they were programmed and are not inherently bad or biased in themselves. They simply do what they’re programmed to do.
The ACLU argues that “even when we know an algorithm is racist, it’s not so easy to understand why. That’s in part because algorithms are usually kept secret. In some cases, they are deemed proprietary by the companies that created them, who often fight tooth and nail to prevent the public from accessing the source code behind them. That secrecy makes it impossible to fix broken algorithms.”
Martine Bertrand, AI Research Scientist, said that “we as humans are striving to set boundaries for machine-learning models but it is going to be very difficult because AI will still reflect the biases and prejudices fed to it because it’s impossible for human beings to not have unconscious biases.”
Jann Spiess, an assistant professor of operations, information, and technology at Stanford Graduate School of Business, said that “it’s not just a matter of mathematics. There are clearly tradeoffs that we as a society have to resolve by coming together and saying what we expect of an algorithm. Existing regulations just don’t include those answers yet.”
