According to a recent Women’s World Banking study, it found gender bias in AI algorithms used to determine creditworthiness.
To find out more on this discovery, we invited Women’s World Banking Director of Research and Advocacy Sonja Kelly on the show. Sonja shared key findings from this study and one of the big ones was sexist AI contributes to the $17 billion gender credit gap.
The study also found:
Algorithms themselves are often biased because the individuals creating them have unconscious biases that they code into the algorithms.
Biases also emerge because of incomplete, faulty, or prejudicial data sets that companies use to “train” the algorithm.
The majority of data sources are vulnerable to gender-based bias.
Data scientists and algorithm developers on the whole (U.S.-based, male, and high income) are not representative of the end customers being scored.
Sonja also discusses how this issue can be remedied, as well as their interactive tool that allows researchers and practitioners to explore various bias scenarios.
Check it out and let us know your thoughts.
Mike Lawson, Host
Married to a beautiful and wonderful wife, raising 5 kiddos (including twins!), enjoy helping others tell their stories, and love surfing SoCal waves. Keep it simple.