similar to themselves, and who have
faced the same barriers.
30, 41 Know the
history of minority contributors to the
field, and make sure these achievements are known.
Adopt an expandable view of intelligence: demonstrate you believe that
skills can be learned.
Know your own biases. Read some
of the literature about unconscious
bias and about the IAT, and then take
the Implicit Attitude test5 at https://
Embrace differences: recall the women in the management study,
9 and as a
manager, pay attention to differences
in needs by individuals.
Foster intergroup conversations as
Remember the subject of a bias is
not always aware of the effects on him
For organizations, it is important for
individuals in key positions to sponsor
promising women and minorities.
An organization that says “we value
diversity” is more trusted than one that
says “we are color blind.”
Values affirmation has been shown
to have long enduring positive effects
on classroom performance.
Before important decisions, make
sure you are well fed: in one study, subjects were tested for their bias against
homosexuals. Half of the subjects
drank lemonade with sugar before the
test; the other half drank lemonade
with a sugar substitute. The subjects
who had sugar showed less bias than
those who had a sugar substitute.
I have conducted this research personally because of my interest in the
subject, and any omissions are inadvertent. I would like to thank the
many people who have sent me relevant literature, but most especially
Caroline Simard, who has studied
this area extensively (Note that the
body of relevant research is larger
than what is cited here.) My particular thanks to Robin Jeffries and Brian
Welle for their critical reading of and
comments on this article, to Bryant
York for the reference to the computer scientists of the Black Diaspora,
and to Alan Eustace for his instrumental role in making diversity a
priority at Google.
For a full reference list, please refer to Supplemental
Materials in the ACM Digital Library or to my blog
1. The Ada Project. Pioneering Women in Computing
Technology. Carnegie Mellon University; http://www.
2. Ambady, N., Shih, M., Kim, A., Pittinsky, T.L. Stereotype
susceptibility in children: Effects of identity activation
on quantitative performance. Psychological Science
12, 5 (Sept. 2001), 385–390.
3. Aronson, J., Lustina, M. J., Good, C., Keough, K., Steele,
C. M. and Brown, J. When white men can’t do math:
Necessary and sufficient factors in stereotype threat.
J. Experimental Social Psychology 35 (1999), 29–46.
4. Ashcraft, C. and Breitzman, A. Who Invents IT? An
Analysis of Women’s Participation in Information
Technology Patenting. NCWI T Report, Dec. 2006.
5. Banaji, M.R. and Greenwald, A.G. Blindspot: The Hidden
Biases of Good People. Delacorte Press, 2013.
6. Barres, B. Commentary: Does gender matter? Nature
442 (Aug. 2006), 133–136.
7. Bateson, M., Nettle, D. and Roberts, G. Cues of being
watched enhance cooperation in a real-world setting.
Biology Letters 2 (June 27, 2006), 412–414.
8. Buse, K.R. Why They Stay: Individual Career Factors
Predicting Career Commitment for Women Engineers.
Social Science Research Network, May 2011.
9. Carter, N. M. and Silva, C. Pipeline’s Broken Promise.
Catalyst Report, 2010.
10. Carter, N.M. and Silva, C. Myth of the Ideal Worker.
Catalyst Study, Oct. 2011.
11. Center for Work Life Policy. Off-Ramped Women May
be the Answer to Japan’s Demographic Crisis Finds
New Study from the Center for Work-Life Policy,
12. Cohen, G. L., Garcia, J., Apfel, N. and Master, A.
Reducing the racial achievement gap: A social-psychological intervention. Science 313, 5791 (Sept.
13. Cohen, G. L., Steele, C. M. and Ross, L.D. The mentor’s
dilemma: Providing critical feedback across the racial
divide. Personality and Social Psychology Bulletin 25
14. Croizet, J.C., Deprés, G., Gauzins, M.E., Huguet, P.,
Leyens, J.P., Méot, A. Stereotype threat undermines
intellectual performance by triggering a disruptive
mental load. J. Personal and Social Psychology 30, 6
(June 2004), 721–731.
15. Desvaux, G., Devillard-Hoellinger, S. and Sancier Sultan,
S. Women Matter: Women at the top of corporations:
Making it happen. McKinsey Report, 2010.
16. Gailliot, M. T., Peruche, B.M., Plant, E.A., and
Baumeister, R.F. Stereotypes and prejudice in
the blood: Sucrose drinks reduce prejudice and
stereotyping. J. Experimental Psychology, Jan. 2009.
17. Gladwell, M. Blink. Little Brown, 2005.
18. Goff, P.A., Steele, C.M. and Davies, P.G. The space
between us: Stereotype threat and distance in
interracial contexts. J. Personality and Social
Psychology 94, 1 (2008), 91–107.
19. Haffner, K. Giving women the access code. New
York Times (Apr. 2, 2012); http://www.nytimes.
20. Harrenstien, K. Finally, Caption Playback. Google
Video Blog (Sept. 2006); http://googlevideo.blogspot.
21. Heilman, M.E. and Chen, J.J. Same behavior, different
consequences: Reactions to men’s and women’s
altruistic citizenship behavior. J. Applied Psychology
90, 3 (2005), 431–441.
22. Heilman, M.E., Chen, J.J. No credit where credit Is
due: Attributional rationalization of women’s success
in male-female teams. J. Applied Psychology 90, 5
23. Herring, C. Does diversity pay? Race, gender, and the
business case for diversity. American Sociological
Review, Apr. 2009.
24. Hewlett, S. A. Leader-Chivée, L., Sumberg, K., Fredman,
C. and Ho, C. Sponsor Effect. Center for Talent
Innovation, U.K., 2012.
25. Inzlicht, M. and Ben-Zeev, T. A threatening
intellectual environment: Why females are
susceptible to experiencing problem-solving deficits
in the presence of males. Psychological Science 11
26. Joy, L., Carter, N. M., Wagner, H. M., and Narayanan,
S. The Bottom Line: Corporate Performance and
Women’s Representation on Boards. Catalyst Report,
27. Judge, T. A. and Cable, D.M. When it comes to pay, do
the thin win? The effect of weight on pay for men and
women. Journal of Applied Psychology 96, 1 (Jan.
28. Kleiman, K. Eniac Programmers Project; http://
29. Martell, R.F., Lane, D.M., Emrich, C. Male-female
differences: A computer simulation. American
Psychologist 51, 2 (Feb. 1996), 157–158.
30. McIntyre, R.B., Paulson, R.M. and Lord, C.G. Alleviating
women’s mathematics stereotype threat through
salience of group achievements. J. Experimental
Social Psychology 39 (2003), 83–90.
31. MIT Faculty Newsletter: A study on the status of
women faculty in science at MIT, March 1999; http://
32. Moss-Racusin, C.A., Dovidio, J.F., Brescoll, V.L., Graham,
M. J. and Handelsman, J. Science faculty’s subtle
gender biases favor male students. In Proceedings of
the National Academy of Science (Aug 2012).
33. NASSCOM-Mercer. Gender Inclusivity in India:
Building Empowered Organisations, 2009.
34. Mitchell, R.L. Women computer science grads:
The bump before the decline, Computerworld Blogs,
(April 2013); http://blogs.computerworld.com/
35. Pieper, J. Leisure, the Basis of Culture. Ignatius
36. Pittinsky, T. L., Shih, M., Ambady, N. Identity
adaptiveness: Affect across multiple identities.
J. Social Issues 55 (1999), 503–518.
37. Purdie-Vaughns, V., Steele, C.M., Davies, P.G., Ditlmann,
R. and Crosby, J.R. Social identity contingencies:
How diversity cues signal threat or safety for African
Americans in mainstream institutions. J. Personality
and Social Psychology 94, 4 (2008), 615–630.
38. Schilt, K. and Wiswall, M. Before and after: Gender
transitions, human capital, and workplace experiences.
The B.E. J. Economic Analysis and Policy 8, 1 (2008), 1–28.
39. Spencer, S.J., Steele, C.M., Quin, D.M. Stereotype
threat and women’s math performance. J.
Experimental Social Psychology 35 (1999), 4–28.
40. Steele, C.M. and Aronson, J. Stereotype threat and the
intellectual test performance of African Americans.
J. Personality and Psychology 69, 5 (Nov. 1995),
41. Steele, C. Whistling Vivaldi. W. W. Norton, 2011.
42. Stone, J., Lynch, C. I., Sjomeling, M., Darley, J. M.
Stereotype threat effects on black and white athletic
performance. J. Personality and Social Psychology 77,
6 (1999), 1213–1227.
43. Tannen, D. The power of talk: Who gets heard and why.
Harvard Business Review, Sept. 1995.
44. Totenberg, N. Sandra Day O’Connor’s Supreme
Legacy: First Female High Court Justice Reflects on
22 Years on Bench. All Things Considered (May 14,
45. Treisman, U. Studying students studying calculus:
A look at the lives of minority mathematics
students in college. The College Mathematics
Journal 23 (1992), 362–372.
46. Vedantam, S. The Hidden Brain. Random House
Publishing Group, 2010.
47. Williams, S. Computer Scientists of the African
Diaspora. SUNY Buffalo; http://www.math.buffalo.edu/
48. Woolley, A. W. Chabris, C. F., Pentland, A., Hashmi, N.
and Malone, T. W. Evidence for a collective intelligence
factor in the performance of human groups. Science
Magazine, 330 (Oct. 29, 2010), 686–688; DOI:
49. Woolley, A. and Malone, T. Defend your research:
What makes a team smarter? More women. Harvard
Business Review Report, June 2011.
50. Zweben, S. and Bizot, B. 2012 Taulbee Survey:
Strong increases in undergraduate CS enrollment
and degree production; record degree production at
doctoral level. Computing Research News 25, 5
Beryl Nelson ( firstname.lastname@example.org) is a software
engineering manager at Google, Mountain View, CA.
Copyright held by author.