1. Implicit Bias in STEM American Association for the Advancement of Science December 12, 2016
Jo Handelsman
Associate Director For Science
White House Office of Science and Technology Policy

2. Presidential Goal
Produce 1 million more STEM college graduates who reflect the demographics of the college population by 2022

3. Diversity — It’s Our Strength1
Take advantage of our greatest resource in science
Enhance the intellectual vigor of science through human diversity
President Obama, Speech at 2016 Science Fair

4. Diverse groups produce….
more feasible and effective solutions to problems (Cox, 1993; McLeod, 1996)
better, more defensible decisions (Nemeth, 1985; 1995)
more innovation in teams (Kanter, 1983)
NSF ADVANCE

5. Diversity — It’s Our Strength
Take advantage of our greatest resource in science
Enhance the intellectual vigor of science through human diversity
Practice our American belief in equity
It’s the law.

6. Bias — It’s Our Weakness
A substantial body of research shows that virtually all people carry unconscious biases
Biases shape attitudes and behavior
Behaviors include hiring, mentoring, and promotion
These behaviors affect inclusion of women and minorities in the STEM workforce

7. Example of Bias Research RCT Job Applicant and Tenure
CVs of a real professor were assigned a male or female name, randomly, and sent to 238 academic psychologists
CV at time of job application
CV at time of early tenure decision
Respondents more likely to hire if male name on job application
Gender of applicant had no effect on respondents’ likelihood of granting tenure
Steinpreis et al., 1999

8. However…… CV’s were returned to researchers
There were “cautionary comments” in margins of tenure package four times more often on those with woman’s name:
“We would have to see her job talk.”
“It is impossible to make such a judgment without teaching evaluations.”
“I would need to see evidence that she had gotten those grants and publications on her own.”
Steinpreis et al., 1999

9. Example of Bias Research Yale Study of Scientists
127 biologists, chemists, and physicists
Six top research universities
Sent participants a student description
Randomly assigned name “Jennifer”or “John”
Questions about student
Hire as lab manager?
Competent?
Provide mentoring?
Salary?

10. John was more likely than Jennifer
to be thought competent
to be hired
to be mentored
Jennifer was more likely than John
to be liked

11. How much would Jennifer or John be paid?
t(125) = 2.94, p < .01, d = .51

12. Did the faculty gender matter in their evaluation of Jennifer or John?

13. What can we do to mitigate the impact of bias in the STEM workforce?

14. Bias Mitigation Interagency Policy Group (IPC)
Holdren-Cobert Memorandum on Increasing Diversity in the STEM Workforce by Reducing the Impact of Bias (October 16, 2015)
Establish interagency policy process
Inventory best/promising evidence-based practices in Federal STEM agencies
Report recommending policy options (15 participating Federal agencies and EOPs)
“Reducing the Impact of Bias in the STEM Workforce: Strengthening Excellence and Innovation,” Nov 2016

15. Best, Promising, and Emerging Practices
Best Practices
Analyses of mandated workforce data sets
Implicit bias training
Conflict resolution
Work flexibility

16. Best, Promising, and Emerging Practices
Promising Practices
Diversity change agents
Diversity tool kits
Technical qualifications board
Grant proposal review experiments

17. Best, Promising, and Emerging Practices
Unconscious bias training targeted at search committees
Bias training for the entire workforce
Hiring and promotions safeguard pilots
New inclusive workforce tools

18. Top Strategies at the Federal-Academic Interface
Proactive use of diversity, equity, or inclusion grants
Family-friendly policies and programs
Compliance reviews
Institutional access to bias mitigation resources

19. Recommendations Federal STEM Workforce
Exercise leadership at all levels, including senior officials, STEM program and administrative managers, human capital officials, and diversity and inclusion officials (or their equivalent), to reduce the impact of bias in their internal operations

20. Recommendations Federally funded institutions of higher education
Federal agencies can incorporate bias mitigation strategies into the proposal-review process and offer technical assistance to grantee institutions to implement bias-mitigation strategies

21. Recommendations
Cross-cutting government leadership—STEM workforce and Federally funded institutions of higher education
OSTP, OPM, and the Department of Justice (DOJ), as appropriate, should exercise leadership to reduce the impact of bias in the Federal STEM workforce and Federally funded institutions of higher education

22. Implementation and Next Steps
Interagency body to coordinate and review Government-wide implementation, scaling, gap identification, tool development, living inventory development
Public engagement campaign
Institutionalization plans
Accountability measurement

23. @jo44