Gender Diversity, Empathy and Technology

What’s the value of gender diversity in technology-based disciplines?  Is gender diversity an asset for technology-based companies?  Are men inherently better than women at technology-based jobs?

These are questions that have long been discussed.  Lots of progress has been made in addressing them.  But they recently resurfaced following an internal memo by Google engineer James Damore that criticized the company’s diversity initiatives, for which he was subsequently fired by Google.

Let me attempt to explore these questions based on relatively recent academic research in three key areas: gender-based behavioral differences; how to create smarter working groups; and the changing skills requirements in the digital economy.

Are there essential differences between the male and female brain?

The best work I’ve come across in understanding gender-based behavioral differences has been done by Simon Baron-Cohen, Professor of Developmental Psychopathology and Director of the Autism Research Center at the University of Cambridge in the UK.  As part of his research into the causes and treatment of autism, Professor Baron-Cohen has been investigating why autism spectrum disorders occur four to five times more often in males than in females.

To understand what might account for such large gender disparities in the incidence of autism, Baron-Cohen formulated the Empathizing-Systemizing theory, which classifies people on the basis of their scores along two key dimensions: empathy (E) and systems (S).  His overriding conclusion was that “the female brain is predominantly hard-wired for empathy, and that the male brain is predominantly hard-wired for understanding and building systems…”

“Empathising is the drive to identify another person’s emotions and thoughts, and to respond to these with an appropriate emotion.  The empathiser intuitively figures out how people are feeling, and how to treat people with care and sensitivity.  Systemising is the drive to analyse and explore a system, to extract underlying rules that govern the behaviour of a system; and the drive to construct systems.  The systemiser intuitively figures out how things work, or what the underlying rules are controlling a system.”

 “[P]eople with autism,” he agued, “may have an extreme of the male brain - good at systemising, very bad at empathising - and that studying autism with E-S theory in mind, can help increase our understanding of the condition.”

According to E-S theory, a person, whether male or female, has a particular brain type.  “A key feature of this theory is that your sex cannot tell you which type of brain you have.  Not all men have the [predominantly] male brain, and not all women have the [predominantly] female brain.  The central claim of this new theory is only that on average, more males than females have a brain of type S, and more females than males have a brain of type E…”

“Should a theory like this be a cause of concern?  Some people may worry that this is suggesting one sex is better than the other, but a moment's reflection should allay this fear.  The theory is saying that, on average, males and females differ in what they are drawn to and what they find easy, but that both sexes have their strengths and their weaknesses.  Neither sex is superior overall.”

How to create smarter working groups

The human brain may well be one of the most complex structures in the universe.  It will be many years, if not decades, before we better understand the brain’s impact on our behaviors as well as the causes of brain disorders like autism.  But, while much research remains to be done, let’s accept the conclusions of the E-S theory, and consider a different question:  Are empathy and related soft capabilities important, - for males as well as females, - even in the hard world of technology?

The answer is a definite yes.  To help us address increasingly complex problems, the bulk of modern work, - in technology as well as most other fields, - is more and more team-based.  As this recent NY Times Magazine article - What Google Learned in its Quest to Build the Perfect Team - noted: “In Silicon Valley, software engineers are encouraged to work together, in part because studies show that groups tend to innovate faster, see mistakes more quickly and find better solutions to problems.  Studies also show that people working in teams tend to achieve better results and report higher job satisfaction… If a company wants to outstrip its competitors, it needs to influence not only how people work but also how they work together.”

Over the past decade, MIT professor Tom Malone, CMU professor Anita Woolley and their various collaborators have been conducting pioneering research on group performance.  Their work addresses a very intriguing set of questions: Do groups exhibit characteristic levels of intelligence which can be measured and used to predict the group’s performance across a wide variety of cognitive tasks?  If so, can you devise tests to measure the group’s intelligence using methodologies and statistical techniques similar to those that have been applied to measure the IQs of individuals over the past hundred years?

To see if there was an equivalent collective IQ, Malone, Woolley et al conducted a number of studies, - nicely summarized in their 2015 article, - Why Some Teams Are Smarter Than Others.

In their initial set of studies, they randomly assigned nearly 700 volunteers into groups of two to five members.  Each group worked together on a diverse set of short tasks selected to represent the kinds of problems that groups work on in the real world.  They also measured the individual IQs of each of the participants.

They did indeed find a statistically significant collective intelligence factor that predicted how well each group would do on a wide range of tasks.  But, neither the average intelligence of the individual group members nor the highest individual intelligence were strong predictors of the group’s overall performance.  They also looked at group cohesion, motivation and satisfaction, but none of them worked either.

Instead, the best performing groups exhibited three key characteristics:

  • More equal contributions.  Group members contributed more equally, instead of letting one or two dominate the conversation.
  • More women.  Groups with more women outperformed groups with more men.  This is likely because as previous research has shown, women generally score higher than men in the Reading-the-Mind social sensitivity tests.

A later study looked at whether groups that worked online instead of face-to-face also exhibited collective intelligence.  They found that whether online or off, some teams consistently outperformed the others.  And, just like in the earlier studies, the best performing teams were better at communicating with each other, participating equally in the process and exhibiting higher emotion-reading skills.

How important are empathy and related social skills in the digital economy?

Finally, let’s look at a few recent studies on the changing nature of jobs and skill requirements in the 21st century digital economy.

Last year, the Pew Research Center, - in association with the Markle Foundation, - conducted a survey to shed light on the skills and training needed to get ahead in the digital economy.  Their analysis and conclusions were published last October in The State of American Jobs.

A key finding was that between 1980 and 2015, jobs in occupations requiring high social and analytical skills had the highest growth.  Jobs in occupations requiring stronger social skills, - e.g., interpersonal, communications, - increased by 83%.  Employment in occupations requiring higher levels of analytical skills, - e.g., quantitative, computer usage, - increased by 77%.  And jobs in occupations requiring both high social and analytical skills, - e.g., managerial, teaching, - grew the fastest at 94%.  By comparison, employment in occupations requiring manual or physical skills, - e.g., physical labor and machinery operation, - increased by only 18% during the same time period.

In an earlier study, USC’s Annenberg School of Communications and Journalism embarked on the Third Space, a research project led by then Dean Ernest Wilson to better understand whether their talent requirements were being adequately addressed by engineering and business schools.  Their research discovered that, beyond the traditional skills typically provided by engineering and business schools, companies needed a new kind of talent that’s currently undersupplied in the workforce.

Future leaders must be strong in quantitative, technical and business skills.  But these must be complemented with a unique set of attitudes, perspectives, experiences and other so called softer skills.  Good leaders need to be good strategic thinkers and must have strong social and communications skills.  Finding and retaining talented individuals with these capabilities is a challenge regardless of geography or industry.

The study identified five specific leadership competencies: adaptability, cultural competence, 360-degree thinking, intellectual curiosity, and empathy.   Empathy turned to be the most important of the five attributes.  “Frankly, when empathy kept coming up in our research, I was surprised,” wrote Wilson in a 2015 HBR article.  “All of the people we interviewed were serious business executives.  Empathy was not the first virtue I associated with the rough and tumble of today’s highly competitive business world.  I expected to hear about boldness, perseverance, and toughness.”

Finally, let me briefly mention another related paper, The Growing Importance of Social Skills in the Labor Market, by Harvard professor David Deming.  Deming’s paper showed that over the past several decades, labor markets have been increasingly rewarding social skills, that is, interpersonal skills that facilitate interactions and communications with others.  A major part of the reason is that jobs requiring high social skills are the most difficult to automate.

He presented evidence that since 1980, social-skill intensive occupations have enjoyed most of the employment growth across the whole wage spectrum, and that employment and wage growth have been particularly strong in jobs that require both high cognitive and high social skills.  On the other hand, employment has fallen in occupations with high math but low social skill requirements, suggesting that cognitive skills are increasingly a necessary but not sufficient condition for obtaining a high-paying job.

Biodiversity is often used as a measure of the health of biological ecosystems.  Similarly, diversity in people and skills should be viewed as a measure of the health of an organization, especially in our increasingly complex, fast changing world.

External URL: http://blog.irvingwb.com/blog/2017/10/gender-diversity-and-technology.html

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