1. Dr. Catherine Ashcraft, NCWIT Senior Research Scientist
Unconscious Biases: Addressing Stealth Barriers to Innovation & Productivity
Dr. Catherine Ashcraft, NCWIT Senior Research Scientist 1

2. Women in Tech: The Facts
Given this research, the tech industry is in trouble. Full pipeline challenge
Girls take 46% of AP Calculus exams but just 19% of AP CS exams
Women earn 57% of undergraduate degrees but just 12% of CS degrees
Women hold 57% of all professional occupations but only 25% of all computing-related occupations
56% of women leave their tech jobs by mid-career - twice the quite rate of men

3. Women In Tech: The Facts
Drill down on Technical Women - mention that many technical women complain about being side tracked in technical “empathy” jobs and are not in the creative roles
Mention that in startup companies, women hold 7% of executive leadership positions (not really the same as technical leadership positions however) - This number is still woefully low: successful startups have 7% of their executive positions filled by women, vs. 3.5% for unsuccessful startups.

4. We’re Losing The Women Who Are Already There: An Unnecessary Corporate Brain Drain
74% love work
56% leave
75% stay in workforce
Sources: Capturing Turnover Costs, Joins, 2000; TalentKeepers, 2010; Athena Factor, 2008

5. Why Women Matter
1) WOMEN REFLECT CUSTOMER BASE 2) WOMEN IMPROVE COLLECTIVE INTELLIGENCE 3) WOMEN CAN FILL GROWING # OF JOBS 4) WOMEN IMPROVE COMPANY PERFORMANCE
1) If 50% of your user base isn’t represented in your design team, how can you expect to know what women want, or how they will use your product?
2) The presence of women in a group is more likely to increase the collective intelligence (problem-solving ability, creativity) of the group than the presence of individuals with higher intelligence. (“Evidence for a Collective Intelligence Factor in the Performance of Human Groups,” Science October 2010, Woolley, Chabris, Pentland, Hashmi and Malone.) Groups with greater diversity solve complex problems better and faster than homogenous groups. (Scott Page, The difference: How the power of diversity creates better groups, firms, schools, and societies, Princeton University Press, 2009.)
3) Women are 50% of the workforce. There will be an estimated 1.4 million computing-related jobs in the workforce by 2020, yet at current graduation rates we’ll produce only enough candidates to fill 30% of those jobs. Meanwhile, women are earning more than half of all undergraduate degrees, more than 60% of biology degrees, 42% of math degrees. They are a untapped workforce.
4) Analysis of more than 20,000 venture-backed companies showed that successful startups have twice as many women in senior positions as unsuccessful companies. (Dow Jones VentureSource, 2011.) Tech companies with women have been shown to use 40 percent less capital and be more likely to survive the transition from startup to established company. (Cindy Padnos, Illuminate Ventures: "High Performance Entrepreneurs: Women in High-Tech," 2010.) Tech companies with the highest representation of women in their management teams have a 34% higher return on investment than those with few or no women. (Catalyst, The Bottom Line, 2004.)

6. Diversity Enhances Teams
Groups with greater diversity solve complex problems better and faster than homogenous groups.
Let’s consider this diversity thing with a non-gender-related problem. Any left-handers here? A couple of years ago a major company released a very popular phone, and people quickly began to complain about dropped calls when the phone was held a certain way. Turns out that because of where the company positioned the antenna in this phone, this problem particularly affected left-handed people, who happened to hold the phone in the “wrong” way more often. WE ALL EXPERIENCE THE WORLD IN A DIFFERENT WAY and it’s important to bring as many of those experiences as possible into the development and design of technology.
(The company’s charismatic founder was ambidextrous, BTW.)
Scott Page, The difference: How the power of diversity creates better groups, firms, schools, and societies, Princeton University Press, 2009.

7. Women Improve Innovation
A group’s collective intelligence is not predicted by the IQs of its individual members. But if a group includes more women, its collective intelligence rises.
Several researchers set out to measure the collective intelligence of a group; they wanted to know if it could be explained by the intelligence levels of group members or not. They were surprised to find that one of the key predictors of a group’s intelligence level was the number of women on the team; the more women on the team, the more the team’s collective intelligence rose, up to a certain point. Individual intelligence of group members was not a predictor of collective intelligence.
This is an interesting finding because it absolutely counters the “rock star” approach to hiring. We all love the stories of a brilliant loner or a couple of guys dreaming up a tech company in somebody’s garage, but the fact remains that the vast majority of technology is developed by multiple people as part of a team. So whether you’re hoping to be acquired or doing the acquiring, it’s smarter to build good teams than look for the one brilliant standout.
“Evidence for a Collective Intelligence Factor in the Performance of Human Groups,” Science October 2010, Woolley, Chabris, Pentland, Hashmi and Malone.

8. Women Correlate with Success
Analysis of more than 20,000 venture-backed companies showed that successful startups have twice as many women in senior positions as unsuccessful companies.
Analysis of more than 20,000 venture-backed companies showed that successful startups have twice as many women in senior positions as unsuccessful companies.
Successful startups have a median of 7% of their executive positions filled by women, vs. 3.5% for unsuccessful startups. Still a pretty low number overall but twice as high as unsuccessful startups.
Correlation doesn’t equal causation, as we all know. But let’s pick this apart for a second: either women in leadership positions at startups cause those startups to become more successful, OR successful startups decide to hire more women into leadership positions. Either way, you want to be one of these startups. Because by the time you become a BIG company, this matters in different ways, too: among companies with a market cap of $10B or more, those with women on their board of directors outperformed those with no women in revenue growth, debt-to-equity ratio, and stock price. (
Dow Jones VentureSource, 2011.

9. Women Help Companies Grow
Tech companies led by women delivered higher revenues using less capital and were more likely to survive the transition from startup to established company
Tech companies led by women launch with 30-50% less capital but are at the same time more likely to survive the transition from startup to established company. It has also been found that women led companies deliver higher revenues using less capital.
This, along with similar research, suggests that women in leadership positions can make your company more efficient and stronger during a growth
Cindy Padnos, Illuminate Ventures: "High Performance Entrepreneurs: Women in High-Tech," 2010.

10. Why the Problem Persists: Understanding and addressing unconscious biases
We are going to roll through a ton of social science research in 10 minutes – we won’t do it justice

11. What the Research Says
We are going to roll through a ton of social science research in 10 minutes – we won’t do it justice

12. Let’s Cut to the Chase
Technical Women Aren’t Broken Technical Men Aren’t The Enemy Culprit = Societal Biases We All Share We Can Take Action Together

13. And EARLY ON is a particularly good time to start!
Clean state – easier to do it right from the start than to try to undo it and start anew
Individuals can make a bigger difference
Culture By Design or By Default

14. Society is Biased About Gender and Technology
So if it’s left to default….one of the things that happens is….BIAS
Project Implicit – measures automatic associated between gender and science.

15. What Causes Societal Bias?
We all have shortcuts, “schemas” that help us make sense of the world. But our shortcuts sometimes make us misinterpret or miss things.
That’s unconscious bias.
Unconscious bias results from “schemas.” Schemas are necessary to live; everyone has them. We need them to make sense of information and to function, they let us pay attention to only select information. But they can also cause us to miss or misinterpret certain things, leading to unconscious bias.

16. What do you see?
This and the next slide are the two short interactive pieces to illustrate unconscious biases

17. Count How Many Passes

18. Notice anything odd about this lung scan?
Photo:

19. More on Societal Bias – Howard vs. Heidi READ THIS
“Before class, we had one section of students read the original case and the other section read a version of the case called "Howard Roizen." Nothing was changed in the Howard version except for all the relevant pronouns. The students then went online and rated Heidi/Howard on several dimensions. The results were disturbing, as you might imagine. Students were incredibly harsh when they thought "Roizen" was a woman, but not when they thought Roizen was a man. I've attached the results in slide format so that you can see for yourself (most of these differences are highly significant).”
Frank Flynn, Associate Professor, Columbia Business School

20. Howard vs. Heidi
Statistically significant differences

21. Howard vs. Heidi

22. Howard vs. Heidi
Emphasize again – both women and men

23. Organizational Culture
Unconscious Bias Is More Salient in Homogenous Organizations
Society
Organizational Culture
Subtle Dynamics
Institutional
Barriers
Schemas/
Unconscious
Biases
Employees
Drew a little architectural diagram to put the social science in context.
Like Technology organizations for example.
Also true for male nurses or male elementary school teachers

24. Subtle Dynamics Example: Stereotype Threat
Example: White male engineering students score lower when told in advance that Asians typically score higher on math tests
Plenty of other examples. Math SAT, older people with memory tests.
Source: Aronson, et al., 1999; Steele & Aronson, 1998

25. How Stereotype Threat Shows Up in Technical Environments
Not speak up in meetings
Be reluctant to take leadership positions
Be overly harsh about their own work
Discount their performance

26. Subtle Dynamics Example: Micro-inequities
Slights: “Actually, Susan has a good idea.”
Exclusion: “Oops, I
forgot to cc her on the
about the
architecture review.”
Recognition: “No, I’m
pretty sure Jane would
not have had the
idea to use a link algorithm.”
Isolation: “Dude, let’s talk about it over a beer!”
All of these examples are subtle, tiny jabs that erode a woman’s sense of belonging, confidence, her sense that she fits in. For the men involved, it’s also subtle, right? It’s not like this is discrimination, here. Again, it’s the fact that these things are said unconsciously, that they speak to the status quo, that make them insidious.
Can make women feel as if they don’t really belong and can undermine the meritocracy of your organizations.
Class room example

27. Institutional Barriers
Hiring
Selecting people “like me”
Task Assignment
Women find themselves in “low status” jobs
Performance Appraisal
Men appraised for effort, skill; women for collaboration, luck
Promotion
Criteria modeled implicitly on existing senior male leaders

28. Institutional Barriers Example: Bias in Hiring
“Blind” orchestra auditions, with musicians behind a curtain, increased the number of female musicians hired by 25% to 46% percent.
In these auditions, musicians are not allowed to cue their gender at all – no talking, no coughing, and they remove their shoes so that there isn’t the tell-tale sound of stilettos or men’s wingtips against the floor.
**This fact really challenges the ideal of a meritocracy: if we so value performance and skills, could we review them blind and hire on them alone? Of what remains – personal characteristics that create good “fit” within a company culture, how many of you think we might, just might, evaluate fit with some bias?
Goldin & Rouse (2000) The American Economic Review, 90(4),

29. Turn to the action piece of this.

30. Invite Diversity & Actively Recruit
1 Broadcast that you’re actively looking for underrepresented people. You’re not waiting for diversity to come to you.
This is not the same as saying lower your standards to find it – it means recruiting where the women are, where the people of color are. Use THEIR networks, not your status quo networks, to advertise open jobs. Experiment with screening applications while “blind” to gender. (If you can build an HTML form, you can collect and evaluate applicants’ criteria without asking for their sex.) To “invite” diversity also means actively and repeatedly inviting women and people of color to the party. Think back to those examples of bias that we went over, and remember that women don’t take that invitation for granted. Just because you leave the door unlocked doesn’t mean your tech company is a meritocracy. What’s the harm in going out and telling the ladies that you value their contributions?

31. Evaluate Interview Questions and Include a Woman in the Interview
Anyone ever gone through a technical interview with those “gotcha” logic questions? These can often disproportionately disqualify women because 1) they play on existing stereotype threat and impostor syndrome, and 2) they are sprints where women are often endurance runners. So ask yourself, are those gotcha logic puzzles an accurate reflection of the engineering work being done in your office? Or is there another way you can test someone’s problem-solving ability?
Diversity comes in many forms. For example, “functional diversity” means identifying that people use different methods and creative solutions when tackling work assignments or solving problems. A pile sort is when you provide a random set of objects or in this case terminology and ask the person to sort them according to categories that make sense to them. A pile sort is a great exercise to screen for functional diversity. It helps identify people who may be good problem-solvers but don’t use status quo methods to arrive at a solution.
Also, try to interview at least one woman for every position you advertise, and try to include a woman on the interviewing committee. Remember that you’re not doing this to fulfill a quota but to include at least one woman’s perspective in the process. Google has been experimenting with making sure it has at least one woman on every hiring committee.

32. Audit Your Physical Space for Gendered Vibes
Physical environment counts a lot. Research has shown that women are less likely to be attracted to computing majors and anticipate less success in these fields when asked about their interests while sitting in a room with Star Wars posters, stacked soda cans, action figures, and other stereotypical “geek” objects.
4 Make sure you’re communicating that your office welcomes all different kinds of people, not just those who enjoy beer pong between all-night coding marathons.
(Cheryan, S., Plaut, V., Davies, P., & Steele, C. (2009). Ambient belonging: How stereotypical cues impact gender participation in computer science. Journal of Personality and Social Psychology, 97(6), )
(Cheryan, S., Plaut, V., Davies, P., & Steele, C. (2009). Ambient belonging: How stereotypical cues impact gender participation in computer science. Journal of Personality and Social Psychology, 97(6), ;
Photo:

33. Assure inclusive team meetings and social events.

34. Provide Recognition, Credit, Encouragement

35. Audit Performance Review & Advancement Processes
Examine performance reviews for unconscious biases
Build accountability metrics into managers’ performance reviews
Clarify paths to promotion

36. Consciously Develop Talent
Watch for biases in task assignment/leadership opportunities
Watch for biases in career path advice

37. Be a Male Advocate; Inspire More Male Advocates
Men have the power to make things awesome for women. Remember that by making things awesome for women, you’re also making things awesome for yourself – because your company is more likely to be correlated with success measures, and because working on teams with women is awesome – but there’s another reason to get involved on behalf of women, too. The status quo was created with men in mind and that means men are more likely to be in positions to change it.

38. Enable & Empathize
“Every person that becomes an advocate had to go through that door where they take the first risk and realize, ‘Oh, that wasn’t so bad.’ So I would talk about the risk-taking that you take the first or second time and how, all of a sudden, it is no longer risk-taking.”
The men who were activist in their orientation talked about standing out as an advocate and what that felt like.
Here’s a quote from a man telling us how he broached this topic with other men. QUOTE
This is an important thing to have discussions about. …
Share this quote, for instance, and it makes it okay for men to talk about similar fears, risks, challenges they’ve experienced.

39. Listening to Women’s Stories
“When it finally started to hit me about gender diversity…We were in a big meeting and…she made a comment about how difficult it was for her to be a leader in the organization as a woman. And so, here is someone who I literally was putting on a pedestal saying this…And I…was like, “Wow!” So I asked her after the meeting… “Hey I want to go to lunch with you, I want to understand this!”

40. ASSUME BEST INTENTIONS
Talk to Other Men
“It’s like if I work on me, I can call people in my immediate peer group when they do something… call them on it and make sure they’re aware of what they’re doing.…I guess my strategy is increasing awareness.” xx
ASSUME BEST INTENTIONS

41. Correct Biases & Microinequities
“A lot of times, the women’s voice kind of gets drowned; it’s left out in a sense. I tend to play that role of connector in group settings. So, I…say, “Wait a minute — [woman’s name] has something to say....Or, you know, “[woman’s name] looks like she wants to get in here, but [man’s name], you just keep talking and we can’t hear over you.”

42. Don’t give up: this is a long distance race and not a sprint

43. Keep Going with Research-Backed Resources
Supervisory Program-in-a-Box Series
Women & IT – The Facts
Top Ten Ways to Be a Male Advocate for Technical Women
Top 10 Ways Managers Can Increase the Visibility of Technical Women
Data driven, research driven, so when you step out to create change, you do so utilizing the best possible evidence.

44. Questions?

45. Small Group Questions
How do we surface unspoken gender issues in the workplace? How is our organization laid out – in what ways might it subtly disadvantage women or other groups? What do men most worry about when it comes to getting involved or being a male advocate?