AI News, Women in Artificial Intelligence – A Visual Study of Leadership Across Industries

Women in Artificial Intelligence – A Visual Study of Leadership Across Industries

Women in artificial intelligence (AI) and machine learning (ML), or the lack thereof, is not a new topic in media, just as gender equity and disparity in the workplace is not a new subject of research for academics and think tanks.

While we address the potential reasons and implications of these issues toward the end of this article, our initial interest in this subject came from our desire to know the following: We looked at top-level female presence (see definition below), and more specifically C-level roles, across 287 companies (average size between one and 100 employees) in seven core industries that leverage AI and ML technologies as part of their main product and service delivery.

While the industries and size of companies may differ, it’s interesting to note the almost on-par percentage of females in C-level roles in comparing our findings to those from McKinsey, a number that is winnowed significantly in the S&P 500.  Based on our analysis of the data, the following key questions arose: To help us begin to address these questions, we again sought out reputable sources, including research groups and thought leaders who have addressed the topic, as well as female C-level executives themselves.

In a survey based on 1,000 male/female respondents, Author Tara Mohr for the Harvard Business Review found that 78% of women’s reasons for not applying for a position have to do with “believing that the job qualifications are real requirements and seeing the hiring process as more by-the-book and true to the on paper guidelines than it really is.” Towards the close of her analysis, Mohr gives a memorable reflection of her own experience as a woman striving to find a place of leadership in enterprise: “When I went into the work world as a young twenty-something, I was constantly surprised by how often, it seemed, the emperor had no clothes.

It took me a while to understand that the habits of diligent preparation and doing quality work that I’d learned in school were not the only—or even primary—ingredients I needed to become visible and successful within my organization.”   Mohr’s realization of the importance of network and relationships is an essential point, and one that is illuminated by McKinsey’s “Women in the Workplace” findings—that 90% of new CEOs for the S&P 500 were promoted or hired from similar line roles.

In a 2012 report that explored the “talent pipeline and gender-diversity practices” amongst Fortune 200 companies (selected based on outlined evidence of their promoting gender diversity), McKinsey found that while more women are making it to mid-level management, less move on to executive roles and C-level positions.

some have found ways to attract, keep, and promote more women than others, and it was based on interviews with senior executives from these companies that McKinsey identified best practices for ensuring closure of the gender gap in leadership, which they outline: senior leaders being consciously aware and committed to achieving gender-diversity;

McKinsey emphasizes that different companies in different industries will understandably have varying contexts and starting places in how they seek to achieve gender equality, but that the “…magic begins when leaders achieve real diversity of thought.” According to a 2013 study by Pew Research, men and women want mostly the same things when it comes to a job: a job they enjoy, job security (slightly more important to women, 37% vs 33%), ability to take time off for family needs, and good benefits.

Without the experience of working at a big tech corporation as I did at the time, it would’ve been much harder for me to internalize the drivers and dynamics of doing business with large enterprise as we do today.” In this respect, a changing landscape at present may not yet be fully realized, assuming that—the startup phenomenon aside—there is any correlation between more experience and older adults (female and male) eventually moving into C-level roles.

It seems safe to say that these vary on a wide spectrum across individuals, with a more limited number of people interested in holding C-level positions; however, the core question is whether there are socio-cultural barriers and inherent structures that discourage or prevent, either consciously or subconsciously, females rather than males from progressing and moving into senior leadership positions across industries.

The 2013 Pew study also showed that the percentage of women (and men) aspiring to top management jobs drops once individuals reach their 30s and 40s—from 61% of women in their 20s and early 30s to 41% in their 30s and 40s, compared to 70% and 58% for men respectively.

A perhaps not-so-surprising statistic stands out as one causal strand: 51% of women (versus 16% of men) have said that becoming a parent makes it harder to advance their career, and women in general are much more likely to experience work interruption due to family in the role as the dominant “caretaker.” In the more recent 2016 report by McKinsey (and referenced earlier), an exploration of staff versus line roles shows the number of roles filled by men and women are fairly even, up until about mid-management levels.

In light of the evidence, one thing does seem clear—if women are to have the same opportunity and choice to realize their full potential in any given field, certain sociocultural structures (including expectations and resources available for having children and childcare) will need to be addressed and new ways of thinking promoted across gender and industry lines.

He recalled a couple of main insights that address both the potential quantitative and qualitative ramifications of industries and companies that hire females for management positions: While the latter point is Palmer’s opinion, it’s one worth noting and of particular relevance to implications for companies solving tough problems—something at which many would argue AI and ML companies are at the forefront.

For example—AI is automating a lot of jobs—so (we have to think) how does that impact the person sitting across the room or whose job is manual now, and what would be the right way of positioning the message for your technology?” In an oft-referenced 2005 meta-analysis of gender differences, Dr. Janet Hyde largely “debunks” the claim that there are noticeable psychological differences between males and females, a “myth” that she believes can do more harm than good in stigmatizing gender in the workplace.

A more recent 2011 study published in Frontiers in Psychology, however, concluded that in many cases, gender does affect accuracy in reading body language, with females more apt to pick up on hostile reactions and “lack of emotional content” in body actions and males better at identifying positive or upbeat body gestures.

In looking specifically at females in roles that require strong math and engineering skills, we likely won’t see the results of today’s educational and other efforts for another five or 10 years.  Is there anything to the argument that women tend to be more interested in social and humanitarian type fields?

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