Recognizing and solving for AI bias

One of our biggest learnings is that AI is best trained by diverse teams that help identify the right questions for AI algorithms to solve. For example, several teams used multi-terabytes of operational data in wealth management to train algorithms to drive higher trading income. The obvious approach was to focus on day traders, who are mostly single, 30-35 year old white males. One of the teams – with a set of diverse members beyond the usual data engineers and neural net experts – addressed that objective and also identified an even larger opportunity targeting single 50-55 year old women, which uncovered a high investible assets segment that previously had gone untapped. Diverse teams think of questions others may not even know to ask.