Introduction to Unconscious Bias, Innovation & Computing 1

DIVERSITY BENEFITS CREATIVITY Groups with greater diversity solve complex problems better and faster than homogenous groups. So first it’s important to clarify WHY we are doing this. There are important reasons for increasing representation. Perhaps most notably, the fact that diversity improves team problem solving, creativity and innovation. A great deal of research has demonstrated this. For example, one study by the London Business School found that teams comprising equal numbers of women and men outperformed teams of any other composition in terms of problem-solving and productivity. Other studies have shown that companies with higher levels of racial and gender diversity have higher profits. In fact, one study found that racial diversity was a key predictor of a company’s competitive standing in it’s industry. Many studies in different contexts have revealed similar findings. Scott Page, The difference: How the power of diversity creates better groups, firms, schools, and societies, Princeton University Press, 2009.

AND, YET… DIVERSITY IN TECH IS LOW Considering the importance of diversity to innovation, this spells a bit of trouble or concern for technical innovation and industry. Consider some of these statistics: Girls take 46% of AP Calculus exams but just 19% of AP CS exams Women earn 57% of undergraduate degrees but just 18% of CS degrees Women earn 42% of all math and statistics degrees and 40% of all physical science degrees 56% of women leave their tech jobs by mid-career - twice the quite rate of men – and 75% of these stay full time in the workforce – so for the most part, they aren’t leaving to start families as is often thought to be the case

AND, YET… DIVERSITY IN TECH IS LOW Women Comprise 57% of U.S. Professional Occupations Women Hold 25% of U.S. Computing Jobs Women Make Up 19% of U.S. Software Developers Women comprise 57% of all U.S. professional occupations – these are defined as occupations requiring a 4-yr degree But they hold only 25% of Computing jobs – and this number has been declining since 1990s when it reached a high of 37% And as you see here, the numbers are even fewer for certain tech jobs – such as software developers. Finally, women hold approximately 5% of technology leadership positions Women Make Up 15% of U.S. Computer Hardware Engineers Source: U.S. Dept of Labor Statistics, 2012 Current Population Survey

AND, YET… DIVERSITY IN TECH IS LOW Black & Hispanic Professionals Comprise 16% of U.S. Professional Occupations, but 30% of U.S. Population Black & Hispanic Men Hold 9% of U.S. Computing Jobs --The specific breakdown for professional occupations is 9% black and 7% Hispanic for Professional --Breakdown for men in computing jobs:4% black men computing and 5% Hispanic men computing --Breakdown for women in computing jobs: 3% and 1% Hispanic women Black & Hispanic Women Hold 4% of U.S. Computing Jobs Source: U.S. Dept of Labor Statistics, 2012 Current Population Survey

WHY Does the Problem Persist?

WHAT’S GOING ON? LET’S CUT TO THE CHASE Minority groups aren’t broken. Majority groups aren’t the enemy. The culprit is societal bias (shared by both women and men) that manifests itself in technical cultures. We know what to do and should take action together. It’s important to clarify up front a few things about our approach because a lot of times when these issues are talked about there’s a lot of blame hurled around – a lot of non productive discussion, so we like to say upfront that we don’t believe underrepresented groups are broken. This is not about fixing them. Majority groups are not the enemy – this is not about pitting groups against each other. It IS about societal biases that we ALL share. The good news then is that we can take action together.

QUICK REVIEW: WHAT THE RESEARCH SAYS So just a quick review of some of the research on bias and how it works.

SOCIETY IS BIASED ABOUT GENDER AND TECHNOLOGY So what do we mean when we say society has biases about science, tech, and gender. Sometimes a picture is worth a 1000 words! Ask if they remember this incident from 2013. And then recap: This comes from the Computer Engineer Barbie book – throughout the book there are pages like this one where she is constantly breaking things, messing things up and needing the boys to help out. And this is in the book that’s supposed to be encouraging girls to go into tech! Mattel eventually pulled the book. Also on a more positive note - a “Hacker Barbie” twitter feed and webpage responded where they took pages from the book and rewrote the captions to say what they should have said. Some are pretty humorous and some are not so G-rated. https://computer-engineer-barbie.herokuapp.com/ https://computer-engineer-barbie.herokuapp.com/

WE ARE BIASED AND MOST LIKELY, YOU ARE TOO Implicit Association Test – This test has been taken by thousands over the past two decades consistently demonstrates that a majority of the population has slight to strong automatic associations of science with male/masculinity. We at NCWIT have taken the test and also come out with these biases. Not about intent or blame – we all share these biases. Project Implicit Science and Gender Test – Harvard University

WHAT CAUSES SOCIETAL BIAS? We all have shortcuts, or “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. And this is important to remember because it also helps remove this idea of blame. We need these schemas to make sense of information and to function, they let us pay attention to only select information. We have schemas for very simple concepts. But they can also cause us to miss or misinterpret certain things, leading to unconscious bias. NOW IS A GOOD TIME TO PLAY THE NCWIT VIDEO Video link

WE ALL BRING UNCONSCIOUS BIAS TO WORK ORGANIZATIONAL CULTURE SOCIETY ORGANIZATIONAL CULTURE SUBTLE DYNAMICS INSTITUTIONAL BARRIERS SCHEMAS/ UNCONSCIOUS BIASES This diagram helps illustrate how these biases are already circulating in society as large and individuals encounter them in a variety of contexts even before they enter organizations. We then bring these biases into our organizational cultures. They subtly shape the culture in 2 ways: Subtle dynamics – small interactions that happen every day and add up over time and Institutional Barriers – which are larger processes or systems that become embedded in the organization’s way of doing things. Examples of Institutional Barriers: performance management, promotion, out-of-work bonding, etc. Institutional barriers are more systemic and coded/embedded into organizational processes. Subtle dynamics can eventually become institutional barriers when they become systemic and encoded in this way. So you might have subtle biases in task assignment here and there but if more pervasive it leads to an institutional barrier – EMPLOYEES

Here are some examples of subtle (sometimes not so subtle) dynamics Here are some examples of subtle (sometimes not so subtle) dynamics. – taken from real life statements NCWIT Aspirations Winners (our award program for young women with aspirations in computing). One of the young women posted the question at the top of the slide to the Aspirations Facebook page. She wanted to know what kinds of advice they would tell people about things they should not say to technical women….. and within minutes these answers started poring in – you can see the time stamp. Hundreds of responses within a short period of time – this is just what we can fit on the slide. And these are high school young women – by this time they have already heard these sorts of statements repeatedly. It doesn’t start in college or when they come into your company. Imagine what it is like to go through your computing education with this experience……you don’t enter that college classroom or that industry interview with the same experience as most men have (see Silent Technical Privilege article in your reading packet)

INTERRUPTING BIAS IN SUBTLE DYNAMICS: WHAT WOULD YOU DO OR SAY? In the hall, a colleague mentions Sarah has potential, if only she could learn to tone it down a bit and not be so abrasive. You notice that someone is repeatedly interrupted in a meeting. You hear someone coach a colleague on how to get ahead, encouraging her to take it “low and slow,” meaning to lower her voice and speak more slowly. You’re sponsoring an employee who is unsure whether or not they should take on a risky assignment. You see someone getting credit for something another colleague said earlier in the meeting. You hear a team lead scold a new employee for mistakes on a project, and that they need to stop making errors as they are not tolerated — especially in these high-visibility projects. You recommend an employee you’re sponsoring for an opportunity, but get the response, “we’re not sure she’s the right fit; she’s not a natural leader.” Work meetings typically include spirited discussion and argument, but Samantha consistently avoids engaging in that manner; instead, she prefers to respond via email later on. A colleague complains to that someone only got that promotion or position because she’s a woman. So for the rest of this session we want to get to work! Goal is to discuss and “practice” practical things we can do -- ways we might intervene when we see bias occur. It’s important to practice confronting bias. Bystanders are more likely to say or do something to confront bias when they have had at least one training. Most people do not have experience or training on confronting bias. Going to have you get into small groups and pick a scenario to discuss.

ACTIVITY INSTRUCTIONS Pick a scenario to work on or, create your own. Generate two ideas for dealing with or intervening in this scenario. Jot down questions you had while dealing with this scenario. Here’s what you need to do in your small group and then we will come back together to discuss in a large group.