The Unceasing Significance of Colorism: From the Social to the Sociotechnical

Tue, February 17, 2026 12:00 PM at Zoom

Bio: 
Ellis Monk is a Professor of Sociology at Harvard University and former Visiting Faculty Researcher at Google. His award-winning research focuses on the comparative examination of social inequality, especially with respect to race/ethnicity, in global perspective. This research uses both quantitative and qualitative methods, while drawing heavily upon contemporary theories of social cognition and categories. By deeply engaging with issues of measurement and methodology, it examines the complex relationships between social categories and social inequality; and extends into topics such as social demography, health, aging, race/ethnicity & technology (e.g., artificial intelligence, machine learning, and computer vision), social psychology, sociology of the body, and comparative & historical sociology. His recent projects include continued work on the Monk Skin Tone Scale project with Google and other industry leaders; and NIH funded research on characterizing and solving algorithmic biases related to skin tone in pulse oximetry.


Title: The Unceasing Significance of Colorism: From the Social to the Sociotechnical
 
For many decades, scholars have documented immense ethnoracial inequalities in the United States and beyond. From health to wealth to nearly every measure of well-being, success, and thriving one can find, there is overwhelming evidence that race/ethnicity is significantly associated with it. Nevertheless, the well-warranted focus on ethnoracial inequalities tends to obscure long-standing skin tone stratification within and across ethnoracial categories. Making matters more complicated is the common folk tendency of conflating race/ethnicity with skin color, thus further obscuring the importance of colorism - discrimination on the basis of skin color - for inequality and stratification. In this talk, I will explain the enduring significance of color and colorism across many domains, including, but not limited to algorithmic bias in artificial intelligence & machine learning and medicine. I will also discuss my work with the Monk Skin Tone Scale (MST) to address some of these pressing issues.

https://msu.zoom.us/j/99966271040

Passcode: soclecture