From the Editor's Desk

Ask HBR: Building a More Diverse Data Science Team

We’ve seen no shortage of scandals in artificial intelligence. Several AI projects have been plagued by bias. ProPublica reported that an algorithm built by one private contractor was more likely to rate Black parole candidates as higher-risk than other candidates. A landmark U.S. government study reported that more than 200 facial recognition algorithms had a harder time identifying non-white faces than white faces. Is it surprising that these applications were built by teams lacking diversity? Technology has a remarkably non-diverse workforce. And data science is a special standout, underrepresenting women, Latinx, and Black professionals more than any role in tech.

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