Video: Implicit Bias and Stereotypes in Science
Biases start early. In one famous study, when children are asked to draw a scientist, about half of kindergarteners will draw a male scientist and half will draw a female scientist. By third grade, about 75 percent will draw a male scientist. And just about everyone is prone to biases, whether you’re male or female, white or non-white, scientist or not.
Hear more about how these biases manifest in the workplace and what you might be able to do about them. In this video from 2016, Dr. Caroline Simard, Managing Director at Stanford’s VMWare Women's Leadership Innovation Lab, discusses implicit bias and stereotypes in science.
What is implicit bias?*
Bias is a prejudice in favor of or against one thing, person, or group compared with another usually in a way that’s considered to be unfair. Biases may be held by an individual, group, or institution and can have negative or positive consequences.
There are types of biases
Conscious bias (also known as explicit bias) and
Unconscious bias (also known as implicit bias)
It is important to note that biases, conscious or unconscious, are not limited to ethnicity and race. Though racial bias and discrimination are well documented, biases may exist toward any social group. One’s age, gender, gender identity physical abilities, religion, sexual orientation, weight, and many other characteristics are subject to bias.
Implicit biases are social stereotypes about certain groups of people that individuals form outside their own conscious awareness. Everyone holds unconscious beliefs about various social and identity groups, and these biases stem from one’s tendency to organize social worlds by categorizing.
Implicit bias is far more prevalent than conscious prejudice and often incompatible with one’s conscious values. Certain scenarios can activate unconscious attitudes and beliefs. For example, biases may be more prevalent when multi-tasking or working under time pressure.
What is the science on implicit bias?
Over the last three decades, our understanding of implicit bias has evolved. The nature of implicit bias is well understood, and an instrument (Implicit Association Test or IAT) to assess implicit bias has been developed and rigorously tested.
Here’s what we know:
Implicit biases develop at an early age: biases emerge during middle childhood and appear to develop across childhood (Dore, 2014).
Implicit biases have real world effects on behavior (Dasgupta, 2004).
Implicit biases are malleable-one can take steps to minimize the impact of Implicit bias (Dasgupta, 2013; Dasgupta & Greenwald, 2013).
A substantial amount of research has been published demonstrating impact of implicit bias in various domains including the criminal justice system, education, and health/health care (Kirwan Institute, 2014). Bias may have an impact on: hiring, and mentoring and may contribute to healthcare disparities.
Fictitious resumes with white-sounding names received 50% more callbacks for interviews compared to resumes with African-American sounding names. (Bertrand & Mullainathan, 2004).
Science faculty rated male applicants for a laboratory manager position as significantly more competent and hireable than female applicants. Faculty also selected a higher starting salary and offered more career mentoring to the male applicant (Moss-Racusin et al, 2012).
Among mentored career K08 or K23 recipients – mean salary of female researchers was about $31,000 less than males (Jagsi et al., 2013).
Implicit bias among health care professionals can influence their behaviors and judgments (Stone & Moskowitz, 2011).
Since 1997, more than 30 studies have been published relevant to unconscious bias and clinical decision-making. Racial bias is prevalent among healthcare providers and it appears that race influences medical decision making (Paradies, 2013).
How can I assess implicit bias?
For many years, scientists have been working on instruments to assess unconscious bias (also know as implicit associations). Of the various tools that are available, the Implicit Association Test (IAT) is one of the most popular and well-studied. The IAT was developed as part of a project to detect unconscious bias based on several factors including race, gender, sexual orientation and national origin. It was developed as part of Project Implicit, which blends basic research and educational outreach in a virtual laboratory that allows users to exam one’s own hidden biases and understand stereotypes that exist below one’s conscious awareness. Project Implicit comprises a network of laboratories, technicians, and research scientists at Harvard University, the University of Washington and the University of Virginia.
How does the IAT work?
The IAT measures the relative strength of associations between pairs of concepts. It is designed as a sorting task in which individuals are asked to sort images or words that appear on a computer screen into one of two categories. The basic premise is that when two concepts are highly correlated, people are able to pair those concepts more quickly than two concepts that are no well associated. The IAT is relatively resistant to social desirability concern, and the reliability and validity have been rigorously tested.
How is the IAT used?
The IAT is powerful instrument, which has been used to explore the impact of implicit bias on behavior. Here are some examples highlighting the use of the IAT in healthcare.
A greater pro-White bias (measured using the IAT) among physicians resulted in an increased likelihood of prescribing thrombolytics for White patients compared to Blacks presenting with acute coronary syndrome (Green, 2007).
A greater pro-White bias (measured using the IAT) was associated with a greater inclination to prescribe pain medications for White versus Black children (Sabin, 2012).
Greater pro-White bias (measured using the IAT) was associated with poorer ratings of interpersonal care among Black patients (Cooper, 2012).
How can I address implicit bias?
Implicit biases are not permanent. In fact, they are malleable and steps can be taken to limit their impact on our thoughts and behaviors (Dasgupta, 2013).
Individual strategies to address implicit bias include:
Promoting self-awareness: recognizing one’s biases using the Implicit Association Test (or other instruments to assess bias) is the first step.
Understanding the nature of bias is also essential. The strategy of categorization that gives rise to unconscious bias is a normal aspect of human cognition. Understanding this important concept can help individuals approach their own biases in a more informed and open way (Burgess, 2007).
Opportunities to have discussions, with others (especially those from socially dissimilar groups) can also be helpful. Sharing your biases can help others feel more secure about exploring their own biases. It’s important to have these conversations in a safe space-individuals must be open to alternative perspectives and viewpoints.
Facilitated discussions and training sessions promoting bias literacy utilizing the concepts and techniques listed about have been proven effective in minimizing bias. Evidence suggests that providing unconscious bias training reduces the impact of bias in the workplace (Carnes, 2012).
The UC Managing Implicit Bias Series is a six-course online training series designed to increase awareness of implicit bias and reduce its impact in the workplace. The series reinforces our IDEA values that enable the Lab and UC to attract and retain a top talent workforce, and it further supports our commitment to developing effective leaders and managers of people.
Employees may complete individual courses, or the entire series. Those who complete all six online courses will receive the UC Systemwide Managing Implicit Bias Certificate. The series contains six self-paced, online interactive courses. Each course is 15-20 minutes in length.
The series is also a core requirement to the UC Systemwide People Management Series and Certificate. As a People Manager, it is especially important to be aware of implicit bias and how it impacts the way we work and interact with others.
50 Ways to Fight Bias (Videos on 6 Types of Gender Bias)
4 Kinds of Gender Bias Women Experience at Work - Overview (trainings and discussion guides below)
Click HERE to view additional trainings on implicit bias
Why don't more women win science Nobels? – Chicago Tribune, 2019
How Implicit Bias and Lack of Diversity Undermine Science – Scientific American, 2018
The False Promise of Meritocracy – The Atlantic, 2015
Orchestrating Impartiality: The Impact of “Blind” Auditions on Female Musicians – The American Economic Review, 2000
Click HERE to view additional Good Reads on implicit bias
Diversity Is Pointless Without Balanced Conversations – Chief Executive, 2020
Did you really just say that? – American Psychological Association, 2017
Students See Many Slights as Racial ‘Microaggressions’ – The New York Times, 2014
How to Respond to Microaggressions - the New York Times, 2020
NPR: Code Switch - How Startups Are Using Tech To Try And Fight Workplace Bias
NPR: TED Radio Hour - Bias and Perception, a Four Part Series
NPR: Invisibilia - The Culture Inside
NPR: Freakonomics - What Are Gender Barriers Made Of?
NPR: Hidden Brain - The Double Bind For Women In Leadership
Quick Reference Guides from UC Implicit Bias Series:
Toolkits for Implicit Bias:
Six Types of Gender Bias: Performance, Attribution, Likeability, Maternal, Affinity, Double Discrimination