In 2018, as part of developing a shared foundation on unconscious bias, our community welcomed Dr. Mahzarin Banaji, the Richard Clarke Cabot Professor of Social Ethics in the Psychology Department at Harvard and one of the founders of the Implicit Association Test. Dr. Banaji is an experimentalist psychologist who focuses on understanding how human minds work in social contexts. During her visit, she led a session with 200 members of the Bridgewater community about the science underlying hidden biases and what it practically means.
Anchored in decades of her research, Dr. Banaji demonstrated how brains help people make sense of and navigate the overwhelming complexity of reality. However, she explained that while the brain enables human comprehension, it also creates blind spots and biases outside our awareness. Dr. Banaji and her team used their research to develop a test to help people become aware of the biases they carry. The Implicit Association Test seeks to measure the strength of associations between concepts to reveal intrinsic unconscious beliefs.
Dr. Banaji led our community through her exam to demonstrate how bias can be a part of our everyday experience. As she took the test, she commented on how typical results show that people are slower to respond when they associate “female” with “career” than they are when they associate “female” with “home” or “male” with “career.” She attributed this occurrence to “the thumbprint of the culture” in which people live, meaning that experiences within certain environments can be deeply internalized by people. Dr. Banaji explained that only when people discover their implicit biases can they then consciously disrupt the negative influences they may have on a person’s behavior.
She encouraged any organization seeking change to begin by discovering biases in its own internal processes and then begin a systematic process for addressing them. Simultaneously, individuals within the company should commit to doing their piece of the work every day. Dr. Banaji said that ultimately, biases are ubiquitous and our goal cannot be to eliminate them, but when necessary, to mitigate their effects in systems and decision making.