Sexism is a By-product of Incompetence

Trump Tower (Stuart)
Trump Tower.  Photo by author.
In the game of life, are you nice to those who out-perform you?  Maybe, if it’s not a big deal if you lose.  But if you lose games all the time, you might not be nice to those who are strong.

There was an interesting study from 2015 making the rounds anew in November 2017.  The study showed that low-performing males in the online game Halo 3 were hostile towards high-performing females.  The study found:

“…lower-skilled players were more hostile towards a female-voiced teammate, especially when [the male was] performing poorly. In contrast, lower-skilled players behaved submissively towards a male-voiced player in the identical scenario. This difference in gender-directed behaviour became more extreme with poorer focal-player performance…. Higher-skilled [male] players, in contrast, were more positive towards a female relative to a male teammate.”

The general idea is that in a contest of skills in a male-dominated environment, there is a hierarchy amongst the men in which junior men are politely submissive towards the men who are at the top of their game.  However, if a woman enters the arena, the lower-ranking men perceive that they can be pushed even lower in the hierarchy and respond with hostility towards the female entrants.

By contrast, higher-performing males aren’t as worried about hierarchical reorganization, so they act like gentlemen, scoring points (figuratively) for being both high-performing and well-mannered.

This is relevant to workforce analytics because the data was good.  There was a clear performance measurement, verbal communications were recorded (including hostility), and it was possible to split the data between males and females.  It’s hard to get this kind of data, and sometimes it’s best to look at games and sports, where data is abundant, to make meaningful interpretations.

In terms of what interpretations to make, it’s a reminder that women can’t simply be given permission to enter a male-dominated area of work.  Verbal discouragement and unfair treatment can damage performance, so creating an inclusive environment is key to allowing women to perform at their pre-existing level of competence.  But that only takes care of women coming up to par.  It is also implied that women need support to grow upwards and onwards.  That is, encouragement and targeted supports directed towards women might be part-and-parcel of enabling women to become equals and superiors.  And some of this support might come from high-functioning men.

The paper entitled Insights into Sexism: Male Status and Performance Moderates Female-Directed Hostile and Amicable Behaviour, by Michael Kasumovic and Jeffrey H. Kuznekoff, is from July 15, 2016.  In my own network I picked this up as a result of the paper being tweeted by Dr. Jennifer Berdahl from UBC.  Dr. Berdahl is well-known and her tweet drove more than 5,400 retweets and 214 comments.

The comments responding to Dr. Berdahl’s tweet were lively and provocative.  For example, the original paper proposes an evolutionary rationale for the male behaviour, and several people thought this was not meaningful (i.e. maybe this has nothing to do with cavemen).  Some people thought that the context of the research (online gaming) is not representative of society overall, because of the number of teenage boys involved.  It’s well known that those aged 15-25 exhibit behaviours that cannot be extrapolated into the general population.

The most prevalent comment was that the study rings true.  This pattern of behaviour resembles typical behaviour in society, and it mirrors peoples’ experiences in many realms.

Don’t Hate Mayhem. Love Complexity Instead.

You Better Hold On. By Jane Rahman
You Better Hold On. Photo courtesy of Jane Rahman.

The strongest defense against a bewildering world is a love of complexity and ambiguity.

Elif Shafak, Turkey’s most popular female novelist, has provided a brilliant critique of our modern times.  In her TED Talk from September 2017, she expresses concerns about economic uncertainty, the impact this uncertainty has on our emotional bewilderment, and knock-on effect this has on the appeal of demagogues.

“Ours is the age of anxiety, anger, distrust, resentment, and I think lots of fear.  But here’s the thing:  Even though there’s plenty of research about economic factors, there’s relatively few studies about emotional factors.  …I think it’s a pity that mainstream political theory pays very little attention to emotions.  Oftentimes, analysts and experts are so busy with data and metrics that they seem to forget those things in life that are difficult to measure, and perhaps impossible to cluster under statistical models.”

Speaking as a workforce analyst, these are my sentiments exactly.  People like me often try to figure out what is happening inside the workplace while thinking of employees as livestock or machines.  But then the people talk, and their souls come through.  Their context and their lives prevail over objective definitions of effectiveness.  Workplace culture overpowers the declarations of those with authority.

Emotional Complexity Amidst Demographic Over-Simplification

Nowhere do I see this more than when I split a dataset into demographic categories.  The categories are usually either-or scenarios, such as age bracket, binary sex, or length of service.  And just as we find the definitive behaviors and opinions of a certain category of people, with a little more digging we find that there is a deeper human story that defies categories.  I see men taking parental leaves, older workers expressing career ambitions, and high-school dropouts with unmet educational needs.  Putting people into categories only helps find a demographic that best gives voice to the human story.  But that human story will usually speak for everyone.

Shafak, who understands human stories, notes that demagogues “…strongly, strongly dislike plurality.  They cannot deal with multiplicity.  Adorno used to say, ‘Intolerance of ambiguity is the sign of an authoritarian personality.’  …that same intolerance of ambiguity, what if it’s the mark of our times, of the age we are living in?  Because everywhere I look, I see nuances slipping withering away.  …So slowly and systematically we are being denied the right to be complex.”

To Shafak, it is the bewilderment imposed upon us by change that makes us susceptible to the simple ideas offered by demagogues.  “…In the face of high-speed change many people wish to slow down, and when there is too much unfamiliarity people long for the familiar, and when things get too confusing, many people crave simplicity.  This is a very dangerous crossroads, because it is exactly where the demagogue enters into the picture.”

Emotional Intelligence, Embracing Complexity, and Building Resilience to Organizational Change

Shafak suggests that “…we need to pay more attention to emotional and cognitive gaps worldwide.”  Those who struggle with complexity and ambiguity need our help.  We’re not at liberty to define non-complex people as the “other,” as people whose opinions we can reject in yet another polarizing simplification.

I felt this concern when I followed the James Damore incident at Google.  A programmer on the autism spectrum was fired for writing an anti-diversity manifesto, and his memo showed that he struggled with sensitivity training in a culture of diversity.  He attempted to attribute the onus of emotional intelligence to a liberal bias and the imposition of allegedly feminine social concerns.  The true lesson was not so much that bigotry sucks; it is that simplified emotions make us prey to extreme opinions.  I think we need to devote more time and energy to empathizing with the perplexed.

Shafak is insistent that we must cherish complexity.  We must value ambiguity.  We must allow ourselves to carry multiple identities and become the cosmopolitan people who can adapt to the world.  For me, I felt reassured that a deep curiosity for new information and enthusiasm for diverse views is the ultimate resistance against bad ideas.

With complexity we can have a meaningful society, meaningful work, and a resilient sense of self that allows us to move forward.  Only then can we get back to work and do our jobs well.

Can We Teach Robots to be Egalitarian?

Abstract robot head from different angles on black background. Artificial intelligence. 3D render.

Can we teach robots to be less biased than us?  Probably yes.  But only if we do this right.  Bias is mostly the product of mental shortcuts we make in our reasoning, and machines can only think clearly if we teach them to not make the same mental shortcuts.

There is an interesting article about employers’ best attempts at reducing bias in hiring algorithms.  Paul Burley, the CEO at Predictive Hire, describes his company’s efforts to identify and eliminate bias in the recruitment and selection of the best job applicants.  This work goes beyond eliminating applicant names from a conventional recruitment processes; this effort gets into predictive analytics to identify the best candidate.

Burley is particularly keen on identifying interview questions that drive bias (either direct or adverse-effect discrimination), and then eliminating those questions entirely.  While they do not use demographic information inside their algorithms, they do use demographic information outside of the algorithm, to test if any of their questions are causing a bias after-the-fact.

Using Workforce Analytics to Identify Invisible Bias

It sounds to me like his company is going about it the right way.  With bias, we don’t disproportionately “choose” white males to be the boss.  Rather, we assess what traits would normally indicate strong leadership, accidentally carry-forward historic stereotypes about strong leaders, and then inadvertently choose white males.  Plenty of people, including some women and visible minorities, accidentally advance this momentum.  That is because it’s the underlying thought patterns driving things, rather than deliberate and malevolent racism and sexism.  You can make one step forward by not being a jerk, but take two steps backward on something called cognitive bias.  And everyone does cognitive bias, not just the man.

Over at Better Humans, they have created a Cognitive Bias Cheat Sheet.  Personally, I have been trying to stay on top of cognitive bias since it was revealed to be a major driver of the 2008 sub-prime mortgage fiasco and the subsequent Great Recession.  Cognitive bias is overwhelming, and that’s illustrative of what the real problem is.  The world just gives us too much information to process, so we make shortcuts in our thinking to make sometimes-accurate judgments.  In the language of behavioral economics, prejudice is largely the advancing of skewed thinking based on cognitive bias shortcuts.

Information Overload – Are Machines Better Equipped Than Humans?

The big deal with big data is that machines are supposed to help us overcome the over-abundance of information.  Sure, we can find patterns and dig up nuggets that are buried in a mountain of data.  But if we are also making judgment calls using cognitive shortcuts because the human brain can’t handle the volume, there is the opportunity to use the machine to allow us to make judgments using all of the information.  We can create algorithms that are larger and more complex, bypassing the constraints of cognitive bias, and produce recommendations that are far less biased than those produced by humans.

We don’t entirely have the option of just turning the machine off.  Going off-grid just sends us back to biased decisions made by humans on gut instinct.  Think of who you know, and consider that not all luddites are champions of equality.  Right now, we are just getting past the first wave of machines imitating our own sexism and racism.  We now have the option of telling the machines to stop doing that, and then building new algorithms that meet our own purported standards of neutrality.

But this will happen if and only if we choose to name our biases, talk openly about them, measure them, make decisions to reverse them, and keep improving the algorithms such that everyone has a fair shot at the good jobs.  And even then, we still can’t trust robots to decide where to seat people on the bus.  We must forever be vigilant, and stay human.

Loving Math, Caring About Peers

Nerd. by David Nichols
Nerd. Photo courtesy of David Nichols

Some time has passed, so let’s calmly reflect on the anti-diversity manifesto that got a software engineer fired from Google in August of 2017.  James Damore, the author, has to be the unluckiest person on earth.  Not only did he lack the genetics and environmental upbringing to be compassionate about the emotions of others (he might be on the autism spectrum), but he also wrongly attributed his career difficulties to the ascent of workplace diversity initiatives.

He delivered his critique via the alt-right media one week prior to the deadly neo-Nazi rally in Charlottesville.  That incident provoked corporate executives, top-ranking generals, and mainstream Republicans to denounce the rally and distance themselves from Donald Trump’s muddled sympathies in the aftermath.  Damore and his fans have left no opening for a nuanced discussion about the effects of diversity initiatives on those with developmental disorders, a potentially meaningful topic of debate.

In this article in the New York Times, author Claire Cain Miller proffers a critique of the role of emotional intelligence in the modern world of information technology.  It turns out that technology has a massive overlap with social and emotional context.

Emotional Intelligence in Workforce Analytics and Computer Programming

For deep evidence, the article cites 2015 research from David Demming that finds job growth and wage growth are highest among roles that use both math skill and social skills.  The idea is that workers “trade tasks” with one another, to allow specialization of talents and improved efficiency when work duties are shuttled back and forth.  Those who trade tasks more effectively through the use of social skills are more productive; hence more jobs and higher pay.

This double-barreled skill set is abundantly obvious to those in workforce analytics.  We spend half our day figuring out cool formulas and novel discoveries.  But the other half of our day is spent interpreting client need, negotiating resource priorities, wordsmithing data definitions, developing interpretations that are suitable to context, and showing compassion while we advance disruption.  However, my field is new.

When computer programming was new it was originally considered highly social work.  There was an abundance of women working in the field.  Through some office-culture twists and turns, things changed.  Boys and men who weren’t as clever at the social skills self-selected into programming.  It worked out for a lot of people.  But there’s a problem; at some point in someone’s career their next chance for a promotion is contingent on social skills.  Those who are lacking in this area see their careers stalled.

Examples abound of coding projects with male-dominated teams who lacked context, who missed an important detail about women’s perspectives.  Apple’s original health app tracked everything except menstrual cycles, the most-tracked health data point amongst women.  Google Plus obliged users to specify their gender and provide a photo, exposing women to harassment.

The Times article also cites research from 2010 by Stanford sociologist Shelley Correll showing that gender stereotypes about skills and performance are a kind of self-fulfilling prophecy.  It’s not true that women are naturally bad at math, but it is abundantly true that women who are told they are bad at math will under-perform and rate themselves more harshly.  The struggle about this stereotype has played out in dramatic ways over the years.

How to Improve Workplace Culture to Ensure Equality for Women

In terms of what to do about this, Correll advises that we:  1) ensure there are no negative gendered beliefs operating in the organization, 2) ensure performance standards are unambiguous and communicated clearly so that sexism does not fill the vacuum, and 3) hold senior management accountable for gender disparities in hiring, retention, and promotion.  That third item is metrics-based accountability, which means that business performance, diversity, and workforce analytics are fundamentally entwined.

The times article notes that “one way to develop empathy at companies is by hiring diverse teams, because people bring different perspectives and life experiences.”  While we might perceive that equity and inclusion efforts come from an activist base, there is a corporate interest in fostering inclusion.  High-performance workplaces need an environment where tasks and diverse views are shuttled back and forth, with ease and good manners.

As for white white males who desperately struggle with emotional intelligence, their voice will have to wait another day.  And probably wait for another leader.

Bias Bad for Business

Hiding, by Wes Peck
Hiding.  Photo courtesy of Wes Peck

Bias is bad for productivity.  Here’s an overview of a study that came out in July 2017.  The findings are that perceptions of bias have a negative impact on idea-sharing and job commitment.  “Of employees who experienced bias, 34% reported withholding ideas or solutions in the last six months and 48% said they looked for a new job while at their current job during the same time period.”

Perceptions of implicit bias are reduced by an inclusive environment. “Employees were 64% less likely to perceive bias at companies with diverse leaders, 87% less likely when they had inclusive leaders, and 90% less likely when they had sponsors.”

The methodology was to compare self-assessments of employee potential to those employees’ estimates of how they would be rated by their manager.  Larger gaps were interpreted as an indicator of bias.  There’s room for debate about the methodology, but the findings ring true.  That is, that managers who favour people like themselves discourage the productivity of a diverse workforce.  Bias is simply malfunctioning thinking.  Leading an organization with malfunctioning thought would presumably be a hindrance to workplace effectiveness.

I’ll Show You My Salary if You Show Me Yours

Secrets. By Salvatore Barbera
Secrets.  By Salvatore Barbera

Human resources departments and those who handle their data are expected to guard the best secrets.  But one of the biggest secrets is ironically an anti-secret.  Did you know you’re allowed to talk openly about your own pay?  Don’t tell HR.  It’s embarrassing (for them).

This article in Atlantic.com by Jonathan Timm from July 2014 draws attention to the dubious practice of pay secrecy.  I’m not talking about the employer’s obligation to keep your pay information confidential.  Rather it’s an article about employees being obliged to keep their pay a secret from one another.  These obligations are referred to as “gag rules.”

For the uninitiated, there is no meaningful moral obligation for employees to refrain to talking about their salary with each other.  On the contrary, in the United States there are regulations that protect employees’ rights to discuss working conditions with one another.  It’s on the edges of the legislation that allows employees to collectively discuss their lot in life, bargain for improvements, and possibly unionize.

In that context the moral judgement should be obvious.  Those handling the file at human resources desks are not allowed to advance anti-union behavior, and as professionals they should always advise against such policies.

The article describes personal experiences of people struggling with these fake rules.  What is notable is how people presume these gag rules are legitimate, employers and employees alike.   Gag rules create a sense of guilt about whether we should put ourselves ahead of the employer.  They make us self-consciousness about whether we’re being greedy.  We’re embarrassed to talk about whether we’re losers for being the lowest paid person.  Raising the topic with colleagues is “akin to asking about their sex life.”

These emotions are powerful stuff.  But then, that’s how bullying is done, isn’t it?

Above and beyond beef-and-taters union issues, gag rules are also wrapped up in discriminatory pay practices.  That is, it is easier to under-pay women and visible minorities or play favorites if employees don’t talk about their pay.  A woman named Lilly Ledbetter complied with the gag rule at Goodyear for nearly three decades and ultimately found out she was under-paid.  Ms. Ledbetter sued and lost because she did not complain about being under-paid within the first 180 days of her first paycheck.

Ironically, employers share pay information with each other all the time.  They’re called compensation surveys.  They happen on an annual basis (if not monthly), and they are delivered through specialized consulting services.  The work is done under careful checks and balances that ensure data privacy and keep the whole process fair and legal.  Those who have worked on such surveys are proud of their work.  I used to do compensation surveys myself, and I was good at it.

One of the reasons why compensation professionals love doing this work is because it helps make pay fair and equitable.  Looking down from the ivory tower, human resources people know that perceived unfairness in pay creates discord.  So “good” employers put some work into getting it right, behind the scenes, in a kind of lab environment where social justice is organized by experts.  But really we’re just trying to stay one step ahead of the riff-raff.

Let’s face it, employees and the social justice movements they created are the rightful owner of this dialogue.  Gag rules and compensation surveys are just the cultural appropriation of working class politics.