MIT Sloan Management Review Article on When You Reject People, Tell Them Why

Humans are meaning-making machines, continually searching for patterns and creating stories to make sense of them. This intense desire to understand the world goes hand in hand with the rise of artificial intelligence in organizations. We expect AI to advance our quest for meaning — not just to predict that X leads to Y in the workplace but to shed light on the reason. In short, we expect it to be explainable.

Definitions vary, but in a recent academic paper, my colleagues and I described explainable AI as “the quality of a system to provide decisions or suggestions that can be understood by their users and developers.” That’s important for applications designed to evaluate people.

About the Author

Tomas Chamorro-Premuzic (@drtcp) is the chief talent scientist at ManpowerGroup and a professor of business psychology at University College London and Columbia University. He is the author of Why Do So Many Incompetent Men Become Leaders? (and How to Fix It) (Harvard Business Review Press, 2019).

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