Spring 2024 Bulletin

Recent Dædalus Issue on Understanding Implicit Bias

Dædalus Editorial
A crowded subway platform shows several commuters turning to face the viewer. Their heads are surrounded by digital boxes that label each an arbitrary number, implying categorization by facial recognition software. The commuters appear to be of various races and ages.
Artificial intelligence. Facial recognition technology identifies human faces on a Bay Area Rapid Transit platform during evening rush hour in San Francisco, CA. Photo by Thomas Hawk. Image published under a Creative Commons Attribution-NonCommercial 2.0 Generic (CC BY-NC 2.0 DEED) license. Image modified. 

By Dædalus Editorial

How do we counter implicit bias in its individual and systemic manifestations? This question is explored in the Winter 2024 issue of Dædalus by leading scholars, scientists, and policy­makers who examine the science behind implicit bias—the residue of stereotyped associations and social patterns that exists outside our conscious awareness but reinforces inequality in the world. 

“Understanding Implicit Bias: Insights & Innovations,” edited by Goodwin Liu and Camara Phyllis Jones, features research and perspectives from a range of areas, including antidiscrimination law, early education, neuroscience, policing, social psychology, and workforce diversity. 

Stemming from a workshop convened by the National Academies of Sciences, Engineering, and Medicine, the volume highlights the work of those conducting research and leading interventions, as well as those with deep experience navigating issues of diversity, discrimination, and antiracism. Each provides models to help us understand the individual-level and structural causes of persistent inequalities. 

“Understanding Implicit Bias: Insights & Innovations” features the following essays:

Preface: Recognizing Implicit Bias in the Scientific & Legal Communities 
David Baltimore, David S. Tatel & Anne-Marie Mazza

Introduction: Implicit Bias in the Context of Structural Racism 
Goodwin Liu & Camara Phyllis Jones

Seeing the Unseen 
Eric H. Holder, Jr.

The Case for Data Visibility 
Marcella Nunez-Smith

The Science of Implicit Race Bias: Evidence from the Implicit Association Test 
Kirsten N. Morehouse & Mahzarin R. Banaji

The Implicit Association Test 
Kate A. Ratliff & Colin Tucker Smith

Young Children & Implicit Racial Biases 
Andrew N. Meltzoff & Walter S. Gilliam

Uncovering Implicit Racial Bias in the Brain: The Past, Present & Future 
Jennifer T. Kubota

Implicit Bias as a Cognitive Manifestation of Systemic Racism 
Manuel J. Galvan & B. Keith Payne

“When the Cruiser Lights Come On”: Using the Science of Bias & Culture to Combat Racial Disparities in Policing 
Rebecca C. Hetey, MarYam G. Hamedani, Hazel Rose Markus & Jennifer L. Eberhardt 

Disrupting the Effects of Implicit Bias: The Case of Discretion & Policing 
Jack Glaser

Roles for Implicit Bias Science in Antidiscrimination Law 
Anthony G. Greenwald & Thomas Newkirk 

Little Things Matter a Lot: The Significance of Implicit Bias, Practically & Legally 
Jerry Kang 

Retooling Career Systems to Fight Workplace Bias: Evidence from U.S. Corporations 
Alexandra Kalev & Frank Dobbin

Implicit Bias versus Intentional Belief: When Morally Elevated Leadership Drives Transformational Change 
Wanda A. Sigur & Nicholas M. Donofrio

Mirror, Mirror, on the Wall, Who’s the Fairest of Them All? 
Alice Xiang

Deprogramming Implicit Bias: The Case for Public Interest Technology 
Darren Walker 

Beyond Implicit Bias 
Thomas D. Albright, William A. Darity Jr., Diana Dunn, Rayid Ghani, Deena Hayes-Greene, Tanya Katerí Hernández & Sheryl Heron

“Understanding Implicit Bias: Insights & Innovations” is available on the Academy’s website. Dædalus is an open access publication.