Reducing discrimination in AI with new methodology

I finally had a chance to watch Hidden Figures on my long journey to Sydney, where I co-organized the second annual ICML Workshop on Human Interpretability (WHI). The film poignantly illustrates how discriminating by race and gender to limit access to employment and education is suboptimal for a society that wants to achieve greatness. Some of my work published earlier this year (co-authored with L. R. Varshney) explains such discrimination by human decision makers as a consequence of bounded rationality and segregated environments; today, however, the bias, discrimination, and unfairness present in algorithmic decision making in the field of AI is arguably of even greater concern than discrimination by people.