AAAS 2017 Annual Meeting AMA Series: All of us make decisions based on unconscious shortcuts that result in bias or other mistakes. We are scientists who use big data and structured interventions to compensate for errors in human decision-making. Ask us anything!

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Hi reddit!

Research and educational institutions and industries in the United States have encountered difficulty attracting and retaining individuals from underrepresented groups, particularly in STEM disciplines, despite decades of well-meaning efforts by government, universities, and employers. Why is this?

We’re Lydia Villa-Komaroff, an independent scientist, Sherilynn Black of Duke University, Timothy Renick of Georgia State University, and David Asai and we approached the problem from a variety of perspectives.

Psychologists and other social scientists have long recognized that humans make systematic errors in judgment. Hard-wired, simple, efficient rules that all humans use to make decisions (i.e., “thinking fast”) may lead to misjudgments about the capacity and potential of individuals from underrepresented groups.

In this AMA, we’d like to discuss real-world examples, and share how academic institutions can make remarkable progress recruiting underrepresented groups as students and faculty when they recognize and compensate for the realities of how the human mind works. Real-time use of big data at Georgia State has, for example, eliminated all achievement gaps based on race, ethnicity or students’ socioeconomic status. Recognition of established barriers to diversity, coupled with a thoughtful strategy to engage students, alums, faculty, staff, and administrators has resulted in profound organizational change at Duke.

We'll be back at 1 pm EST; we look forward to reading and answering questions about our research and findings!

">AAAS 2017 Annual Meeting AMA Series: All of us make decisions based on unconscious shortcuts that result in bias or other mistakes. We are scientists who use big data and structured interventions to compensate for errors in human decision-making. Ask us anything!