Diversity and inclusion makes tech work better. But that's not what we're seeing.
The business case for diversity and inclusion is clear. A recent McKinsey&Company report found a strong correlation between diversity and inclusion and financial performance. For example, in 2017, companies in the top quartile in executive gender diversity were 21% more likely than their lower-ranked counterparts to exceed the national median for financial performance within their industries. Similarly, companies in the top quartile for racial and ethnic diversity were 33% more profitable.
Nevertheless, the tech sector remains among the least diverse in the economy. These trends are well-documented. From deficiencies in the educational system that track women and people of color for non-tech careers, to unconscious biases in hiring decisions, numerous factors create these disparities.
We all have biases. But when one set of biases it disproportionately reflected in our technology and algorithms, they can reinforce existing inequality. We see these biases played out repeatedly in future crime prediction algorithms that disproportionately rank black people as more likely to commit crime, gender stereotypes in translation algorithms, and in targeted, "psychometric" based advertising.