Women in Tech
The Surprising Neuroscience of Gender Inequality

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The Surprising Neuroscience of Gender Inequality

Janet Crawford • March 11, 2016 • Bath, UK

The video titled "The Surprising Neuroscience of Gender Inequality" features Janet Crawford speaking at BathRuby 2016, addressing the pervasive issue of gender inequality in the tech industry, often attributed to unconscious bias rather than overt sexism. The talk delves into the following key points:

  • Personal Experience: Crawford shares her journey in science, detailing early influences of gender bias within her family and educational environments that shaped her aspirations.
  • Statistical Overview: Despite an increase in female college graduates, gender representation in tech and leadership roles remains deeply troubling, with only about 20% of tech roles occupied by women, and even fewer in leadership positions.
  • Impact of Unconscious Bias: The talk highlights how unconscious biases affect hiring, promotions, and perceptions of competence, often leading to women being underestimated or overlooked in professional settings.
  • Consequences of Representation: The video discusses the negative impact of low female representation on innovation and business success, citing studies that show varying company performances based on gender diversity in leadership.
  • Call to Action: Crawford emphasizes the importance of individual and collective responsibility to recognize and address these biases. She advocates for increased male participation in fostering inclusive environments, suggesting practical steps that can be implemented immediately.

The conclusion of the talk underlines the necessity of tackling unconscious biases to drive genuine change, encouraging audiences to be vigilant in recognizing their biases and fostering diverse environments for future generations. Crawford expresses hope that the audience will take proactive steps in their workplaces, reinforcing that addressing gender bias benefits everyone in society.

The Surprising Neuroscience of Gender Inequality
Janet Crawford • March 11, 2016 • Bath, UK

The Surprising Neuroscience of Gender Inequality by Janet Crawford

When it comes to the tech industry and gender, intolerance and under-representation are daily news items. Yet despite the glaring ugliness of scandals like Gamergate, the prime culprit in gender inequity is likely not overt sexism. Implicit bias, a normal byproduct of our neural design, leads well-intentioned men and women to reinforce the status quo, while constricting creativity and limiting strategic vision. This talk explores the biological basis of bias and the responsibility we all hold in changing the story.

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BathRuby 2016

00:00:00.000 Good afternoon! It is a delight to be here in this absolutely gorgeous city. I've actually never been here before, and as a huge Jane Austen fan, I am having a great time. I’ve managed to get about six hours of sleep in the last 72 hours, so arriving here at 6 AM for me feels a bit challenging.
00:00:20.789 Today, I’m here to talk to you about gender equality in technology. I’ve been listening to this fabulous slate of speakers with their impressive coding credentials. I am not one of them, but I am a scientist, and I aim to sprinkle in some scientific insights regarding the lack of representation we observe in the industry.
00:00:53.309 I don't know much about the situation in the UK, but I suspect it parallels the United States. Gender equity has suddenly become headline news. You can't pick up a newspaper in the States without encountering scandals like Gamergate or high-profile gender discrimination lawsuits. Tech companies seem to fall like dominoes when forced to release their diversity stats, which are not looking good—around twenty percent of those in technology are women, a figure that plummets as you move up through the leadership ranks.
00:01:14.210 I live and work in the San Francisco Bay Area, and as I mentioned, I am a scientist. I have experienced many of the issues that women face in technology firsthand. However, my story with women in tech stretches back long before the current media frenzy. My dad was a rocket scientist who worked in a laboratory filled with male physicists and engineers, along with their female secretaries—except for one lone female engineer. My dad held her in the highest regard.
00:01:57.479 From this, I received the message early on that being a scientist or an engineer was a cool thing for a woman to aspire to. I believed I could be anything I wanted to be, and if that turned out to be a scientist or engineer, my dad would be incredibly proud. Nonetheless, I also absorbed a more subtle yet profound message. Each Christmas or birthday, my brother received gifts from a catalogue, while I received toys deemed more appropriate for girls. After he opened his gadgets, he would happily disappear with my dad into his workshop to solder circuit boards, while I was left with clothing and crafting supplies. To be fair to my dad, I never asked him for a Heathkit; I just intuitively sensed it was not something made for girls.
00:02:50.090 This experience lays the groundwork for today's discussion. Fast forward a few years, and I became a scientist, attending UC Berkeley, where I was largely unprepared for the onslaught of sexism that awaited me. At Berkeley, we had three levels of physics courses—physics for physicists, physics for biology majors, and physics for liberal arts majors, which was often dismissed as 'physics for girls' because it didn’t require math. I excelled at math and thus aimed straight for the physics for physicists course, only to find myself in a lecture hall surrounded solely by men. At age 18, being a heterosexual female in that environment was not a problem for me, and I did well on the theoretical portions of the class.
00:03:54.800 However, things changed one day when I entered the laboratory. I saw a pile of equipment that resembled a daunting challenge and instructions that might as well have been written in Swahili. I was forced to ask for help, observing all the other men in the room soldering away with ease because, unlike me, they had experience with Heathkits. From that moment, I became a poster child for why girls didn’t belong in real physics.
00:05:01.840 Let’s pause here for a moment and consider a few questions: Why would my dad, a vocal advocate of women in science and technology, fail to give me a Heathkit? Why did I, an intellectually curious young girl, not ask for one? And why was there this gigantic logical leap made by my male peers from 'doesn't know how to use a soldering iron' to 'doesn't belong in physics'? The unifying factor in all these questions is what we are here to explore: unconscious bias.
00:05:35.020 I graduated in 1985, and despite the overt sexism prevalent at that time, it was also a period of optimism for women in the United States. For the first time in history, female college graduates outnumbered men, and we flooded into the marketplace. We naively believed our generation would eliminate gender inequality, yet here we are, 30 years later, and the conversation remains largely unchanged.
00:06:19.210 If you work in tech, just look around the room for evidence. The statistics are disappointing. This image from last year's Apple Developers Conference captures the story well—it’s often the only place with quick access to a bathroom during a conference. However, what you may not know is that the numbers in technology are moving backward, not forward. The year I graduated was also the year when female graduates in computer science peaked at around 38%. Since then, that figure has steadily declined.
00:06:56.690 Moreover, the numbers of women are strikingly low in key roles across various sectors. For instance, only 4.7% of Fortune 500 CEOs are women. In the FTSE, there are 17 male CEOs named David but only five female CEOs in total. Globally, only five countries have women representing more than 20% of board seats in publicly held companies, and sadly, the United States is not among them. In venture capital, a mere 6% of partners are female, while women receive only 2.7% of venture funding—0.1% if they are black females. Across the globe, just 6% of countries have ever had an elected female head of state.
00:07:57.190 Interestingly, while arguments may be made for the under-representation of women in these categories, women constitute 50% of the population; hence, they should logically hold 50% of roles in films. Yet, last year, women accounted for merely 12% of lead roles in major motion pictures. These figures are dismal, but many do not perceive this as a problem. They argue that in the industrialized world, women have equal access to education and that we’ve outlawed overt forms of discrimination. Therefore, if they aren’t appearing in these roles, it must be due to a lack of interest.
00:08:41.370 If you find yourself aligned with that viewpoint, I hope to broaden your perspective by the end of this talk. Beyond social justice and fairness, there are pragmatic reasons to address this gap. First, there is abundant evidence that empowering and uplifting the voices of women worldwide is one of the quickest ways to alleviate poverty. Numerous studies from Catalyst, Deloitte & Touche, McKinsey, Credit Suisse, the World Bank, and the United Nations show the effects of women on business performance, indicating that companies with a higher representation of women in leadership significantly outperform their competitors across all critical measures.
00:09:38.290 For example, Catalyst found that companies with the highest representation of women on boards outperformed those with the lowest by 42% in sales and by 66% in return on investment. Studies on group intelligence also show a strong correlation between the number of women in a group and the inclusivity of the conversation. Innovation is tied to diversity in voices, and from a design perspective, it makes sense to include a constituency that represents half the population.
00:10:05.790 Given the solid reasons for improving gender representation, why aren’t there more women in leadership roles? Some point to motherhood, claiming it’s a factor. While it's undeniable that this influences many women, our thinking hasn’t matched the demographic reality: in the United States, 50% of the labor pool is female and 40% of primary wage earners are women. Therefore, we can't simply accept that the low percentage of female CEOs in the Fortune 500 is because they are absent from the labor pool.
00:10:45.380 Another common explanation is the pipeline argument, suggesting women haven’t been in professional roles long enough to ascend through ranks to leadership. However, in fields like medicine and law, where the numbers of women have been nearly equal over the years, we still see a significant drop-off in top leadership roles. These explanations overlook a powerful and invisible factor: unconscious gender bias which all of us, male and female, possess to some degree. This bias causes well-meaning individuals to act inconsistently with their values, reinforcing the status quo without even realizing it.
00:11:21.760 Until we acknowledge and address this phenomenon, we unwittingly become accomplices in perpetuating inequities and discrimination. Let's explore how unconscious bias operates in our brain and, more importantly, what we can do to combat it. A central feature of brain design underpins this entire discussion: most of what we do is not the result of conscious deliberation. We cannot process the sheer volume of environmental information with only our conscious mind—it requires assistance from a wealth of unconsciously stored associations.
00:12:04.650 As we navigate our day, our brain is continuously scanning for patterns. When it recognizes them, it stores those patterns as 'the way things are.' The challenge with this process, which often works well, is that the brain does not distinguish between fairness, utility, or accuracy. If we perceive something, it gets encoded in our minds regardless of its truth. These associations are what our brains draw upon to make sense of the world and formulate responses.
00:12:45.210 The moment I walked onto this stage, you already had an unconscious narrative of who I am: my age, race, height, appearance, and topic of discussion. All of these aspects fed into an unconscious algorithm we develop to make split-second judgments based on superficial data. This process is often beneficial since biases serve as cognitive shortcuts; without them, we would struggle to function. However, they can lead to incorrect conclusions and assumptions, especially when not revisited for accuracy.
00:13:23.960 You can think of your brain as operating on two pathways: one is like a superhighway during off-peak hours with minimal traffic; the other is an overgrown path through the woods that requires constant attention. Naturally, the brain defaults to the superhighway for ease and efficiency. To illustrate how limited our conscious processing is, let’s consider quick math: What’s two plus five? Can anyone answer that? Now, what about 12 plus 10? Or 96 plus 57? As you can see, these complex calculations can easily overwhelm the conscious mind, highlighting its limited capacity.
00:14:13.750 In addition to gathering and storing associations, our brains classify these associations for quick retrieval. For instance, when discussing dogs, we utilize information relevant to that category. However, if we were to encounter terms like went to Stanford or Oxford, we might inappropriately associate those institutions with elitism or exceptional intelligence, despite the reality that not every graduate embodies those traits. To grasp how these associations affect us, let’s engage in a brief exercise. I will show you lists of words, and your task will be to name the color of each item as quickly as possible.
00:15:21.840 Let’s practice with a simple list. On the count of three, name the color of each item as quickly and accurately as possible: one, two, three! Great job! Now we’ll try it with a second list: one, two, three! Excellent. However, when we move to a third list, you might notice it becomes more challenging. This stems from the incongruity between the word and its color, forcing your brain to analyze each separately, resulting in slower responses or errors. Understanding this foundational process helps to clarify unconscious or implicit bias.
00:16:54.545 In the mid-1990s, professors Mazarin Banaji and Anthony Greenwald proposed that our biases might not solely reflect our explicit attitudes but could also encapsulate these unconscious associations. In 1997, Greenwald collaborated with Brian Nosek to create the Implicit Association Test (IAT), which you can take at implicit.harvard.edu. This test measures your ability to associate certain words with male or female faces. When your requested association matches your internal associations, you complete the task more quickly and with fewer errors.
00:17:27.560 For example, you would tap the 'e' key on your keyboard if you saw a female face or words like supportive, gender, emotional, or fragile. Conversely, you would tap the 'i' key when presented with male faces or words such as leader, provider, strong, or driven. Most people can perform this task well; however, when the associations do not align, people tend to slow down and make more mistakes. The degree of slowness or error rates provides insight into your unconscious associations.
00:18:01.080 As of a few years ago, approximately 16 million individuals had taken the IAT, one of the largest datasets in social science. The results reveal high levels of unconscious gender bias across the globe. Unsurprisingly, technology and leadership remain closely tied to male identity. Studies consistently show that technology is associated with being male, and in turn, so is power.
00:18:38.160 If our biases stem from societal influences, we can examine our environment for evidence. I conducted image searches on the internet for various professions, and the results were telling. Images depicting CEOs, politicians, founders, computer scientists, software developers, and mathematicians overwhelmingly featured men, while women were often relegated to roles as assistants or caregivers. This illustrates where societal messages about gender competency are formed.
00:19:21.560 Just for fun, I even looked up 'computer code' and 'Ruby.' The images that appeared were shocking. The internet can serve many idiosyncratic results; however, real-world examples confirm persistent biases in gender representation. For instance, this email from LinkedIn showcased the top minds I should follow, showing only a 23% representation of women.
00:20:15.140 In examining gender ratios at professional conferences, I turned to events like the Wall Street Journal Digital Conference and the Global Leadership Summit, both exhibiting stark disparities. Even Oracle hosted an enlightening session on unconscious bias, yet the attendance was overwhelmingly male. Such industry events often reinforce the perception that technology and leadership roles belong to men.
00:20:53.860 Representation issues persist even in promotional content. For example, Fortune Magazine felt compelled to reassure readers of Marissa Meyer's credibility as a leader due to her appearance. Girls are often influenced from a young age by toys designed to promote gender representation. In 2014, Barbie came with a booklet that suggested girls needed help from boys named Steven and Brian to become successful engineers.
00:21:45.470 This imagery used in media is consequential as it factors into our unconscious calculations of who belongs where and what competence looks like. As we explore these associations, one might question whether they affect our behavior. Copious academic research affirms they absolutely do. The most adversely affected area is assessments of competence, which starts early in life.
00:22:28.570 A New York University study revealed that mothers underestimated their daughters' crawling capabilities while overestimating their sons’. Similarly, a Tel Aviv University study showed that middle school teachers credited boys with more merit for equivalent answers on math exams. Various studies involving resumes indicate stark disparities in hiring based on gender, demonstrating that 'John' is often favored over 'Jennifer.'
00:23:32.380 Another significant finding explored GitHub acceptance rates. An analysis encompassing 1.4 million GitHub users indicated that women’s code was accepted at a rate of approximately 78.6%, as opposed to 74.6% for men's code. However, when reviewers could identify a coder's gender, acceptance rates for identifiable women dropped to 62.5%. Research also suggests women experience a disproportionate number of interruptions in professional settings, leading to their good ideas often being misattributed to others.
00:24:23.740 This situation reflects a twisted logic; if we carry unconscious biases and associate identity with competence, we're less likely to give airtime to those we perceive as less qualified. This impacts the way women perceive their achievements as well. Women are more prone to attribute their success to luck or help from others, whereas men attribute their success to hard work and expertise. This diminishes their likelihood to pursue advancement opportunities.
00:25:39.320 There exists a troubling double bind: competence and likability are positively correlated for men but negatively correlated for women. Recruitment predominantly considers both attributes, complicating the landscape for women aspiring to leadership roles. This issue is evident in the United States, influencing our political landscape as well. Gender biases infiltrate not just hiring processes but also life choices. A fascinating study conducted by the University of Washington crafted two computer science classrooms with different designs.
00:26:52.470 One was filled with neutral decor, such as art posters, plants, and coffee cups, while the other featured stereotypically nerdy items like Star Trek posters and video games. Interestingly, female freshmen exposed to the neutral environment displayed equal interest in pursuing careers in computer science, whereas those in the traditionally nerdy environment registered significantly less interest. Male students, in contrast, showed no difference based on their classroom environments.
00:27:53.240 Everywhere we look, biases affect outcomes. Simply believing in gender equity is insufficient; we are both the creators and consumers of environments that fuel these biases. Thus, it is crucial for each of us to engage in transforming these conditions. So, what can we do? First and foremost, increased male participation is critical; we cannot rely solely on women to resolve these issues. This is not intended as an admonition to the men present, but rather a practical point of view.
00:28:44.830 The leadership must drive this change, and if leadership is predominantly male, then the responsibility falls on them. Moreover, it can be incredibly isolating for women in technology, who face biases and stereotypes that accumulate over time. Alongside overt challenges, minor yet persistent issues lead to a significant exodus of women around the ten-year mark in their careers—not by coincidence, as they begin to prioritize belonging in a supportive environment.
00:29:29.940 It becomes imperative for all of us to shift this paradigm. As for actionable steps, my company specializes in consulting on such issues, helping organizations untangle this complex dilemma. The initial step remains the same: we must pay attention to gender representation. This observation doesn’t need to be politically correct or overly formal—it can even be a source of camaraderie among colleagues as you share observations.
00:30:14.890 Where should we look? Examine talks, websites, and articles—the content you consume and produce. Assess stock images: not only who is in these images, but also what activities they are engaged in. Pay close attention to the speakers and participants at events, especially those that are by invitation only. One woman or person of color on the executive committee can significantly influence representation at conferences. Look at your workplace’s hiring practices too, and question whether cultural fit is being used to justify exclusion.
00:31:11.130 What does your organization’s social culture communicate? Are gatherings skewed toward the preferences of an exclusive group, or do they foster inclusivity? You cannot dismantle what you cannot detect. Legislative changes or mandatory training alone will not alter unconscious biases; real change emerges from individual actions.
00:32:17.670 While this process demands effort and conscious awareness, it is crucial to engage with these issues. Changing representation calls for consistent attention, which may require stepping outside your comfort zone and straying from what feels familiar. Initiating this endeavor is not easy—it can be set aside when life gets hectic. Yet this work is essential; until we collaborate to illuminate the invisible biases operating around us, these damaging patterns will persist.
00:33:30.860 I trust that everyone in this room is intelligent, well-meaning, and driven by values. For those gathered here, it’s not about blame but responsibility. The stakes are high, and so too are the potential benefits—not just for businesses and our economies, but for families and future generations.
00:34:37.210 Changing our societal narrative around gender is an immense challenge. Yet during conferences like this one, I find inspiration in the men who approach me, sharing their commitment to driving change at their companies—even if they feel uncertain about how to proceed. These men become my heroes for being willing to tackle this issue, which, while inherently complex, is indeed worth engaging with.
00:35:05.120 Addressing these biases benefits not only women but everyone, and working together to dismantle them is a crucial step toward transforming the world.
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