Is This the Face of a CEO? It Should Be.

toothless
Toothless.  Photo courtesy of Chris Penny.

In order to become a CEO you need to “look like” a CEO.  And it’s not about wearing the right suit, climbing mountains, or having a cruel handshake.  No, the main indicator of whether you “seem like” the CEO type is that you have a complete absence of baby-face.

The research paper is entitled “A Corporate Beauty Contest” published in July 2016 in Management Science.  The research was entirely about men because status-quo data is already sexist to begin with.  The authors are John Graham, Campbell Harvey, and Manju Puri, all from Duke University.  There’s a good news article about it in the Wall Street Journal, but I’ll summarize it more briefly:

  • Survey participants can easily identify if two people with identical demographics are a CEO and a non-CEO.
  • People judge the CEOs of larger organizations as being “more CEO-ish” than the CEOs of smaller organizations based on the same facial features.
  • Those executive with more “mature” facial features were paid more than those with less-mature facial features. To clarify, even within the arbitrary demographic category of tall straight white able-bodied males with a bit of grey hair, there is an additional category of pay discrimination based on genetics: mature-face.
  • The authors found the findings surprising because it is assumed that CEOs are selected by corporate boards based on metrics and expertise.   The main driver of a successful executive search is metrics about the shape of the executive’s face.
  • Just in case you’re about to ask if super-effective people tend to develop a mature face over the years, hold your horses. “The look of competence isn’t correlated with superior [business] performance,” says co-author John Graham.  That is, discrimination based on looks can forgive corporate performance altogether.

We just throw certain types of people into high-level jobs regardless of how good they are at running our economy.

What to do?  First, thou shalt laugh.

Second, you should actively recruit people who don’t look the part but who have good formal indicators of competence.  In the book Moneyball, Billy Beane relied exclusively on metrics to decide which baseball players to recruit into the Oakland A’s.  He ended up with an team of weird-looking people.  One guy pitched under-hand, some people had a lot of moles and birthmarks, and there was a legend about that once you look at the numbers, overweight catchers tend to be selected because of their great batting performance.  We’re not selling blue-jeans.

If you could identify the most baby-faced darlings who had exceptional corporate performance, those might be your best candidates for CEO.  And their salaries would be a total bargain, too.

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.

I Like Your Style, You’re Just Like Me

Apostrophe Absent. By Michael Derr
Apostrophe Absent. Photo courtesy of Michael Derr.

Are you compatible with your organizational culture?  I sure hope not.  You need the freedom to break from the pack in order to pass along new information and adapt to disruptive change.

In the 2011 book Connected by Nicholas Christakis and James Fowler, the authors describe the way opinions and behaviors spread through social networks.  They describe a Three Degrees of Influence rule: we influence and are influenced by people three degrees removed from us, most of whom we do not even know.

You might know one hundred people, but those people may know another one hundred people (each), and so on.  This could result in a million people crowd-sourcing shared opinions.  You would pick up many opinions from this extended network.  The reverse is true as well.  You could spontaneously assert that we should have all better table manners, and a million people might change their behaviors.  Or maybe they’ll just talk about having better manners.

The implication is that you do not entirely experience independent thought.  You might control what time you arrive at work, what garments to wear to the office, and how you respond emotionally to what  your manager just said.  But the allocation of housework in your household, the social norms in appropriate dress, and the organizational culture of two-way conversation could all be things that have significant third-party influence.  You’re not exactly an autonomous hero in the workplace; you are a team-player in an environment where culture runs deep.

This critique has been revisited in a recent book review in which Yuval Harari summarizes The Knowledge Illusion by Steven Sloman and Philip Fernbach.  Sloman and Ferbach posit that individual thinking is a myth, and that we actually think in groups.  With modern civilization we have come to rely increasingly on the expertise of others.  This crowd-think has mostly been good for us, but it also has a downside.  People “…lock themselves inside an echo chamber of like-minded friends and self-confirming newsfeeds, where their beliefs are constantly reinforced and seldom challenged.”

Group loyalty and pride in our presumed intelligence causes us to stick to the normal way of doing things.  This is a challenge to those of us who produce or consume new information.  New information and new ideas disrupt stable group environments.  If we are trying to change the workplace so that things are done differently, we must exchange discomforting opinions.  We must propose ideas that will be rejected.  We must try things out that won’t work.

Are You Blinded By Your Own Smarts?

Then he laughed into my eyes. By Josh Pesavento
Then he laughed into my eyes.  Photo courtesy of Jose Pesavento.

Too much knowledge can turn you into an idiot.  The curse of knowledge is that problem where experts in a field are unable to explain their great knowledge to a lay audience, because they can’t bring it down to earth.  The speaker might have good information about the base knowledge of their audience, but they just don’t “get” that their audience hasn’t taken the introductory course in their subject area.  It’s odd that someone can be highly esteemed for their knowledge, yet get short-tempered with the very people who hold them in high regard.  I think this is why it’s so hard for experts in two different fields to communicate with one another.  There is a special skill set in talking to intelligent people who don’t understand what it is that you do.

You’re Smarter Than You Were an Hour Ago

Rear-view mirror of Zion Mountains, by daveynin
Rear-view mirror of Zion Mountains, by daveynin.

One of the greatest adventures in uncovering new information is the clash between our new ways of thinking and the opinions we had moments prior.  Our brains play tricks on us, through cognitive fallacies, when dealing with disruptive evidence.

One such fallacy is called “hindsight bias,” a kind of knew-it-all-along effect.  I have given complex and novel findings to clients who quickly proclaim that the information is basic and obvious in some way.  Sometimes it is basic and obvious, but quite often they had opposite views minutes earlier.  Learning and research can be thankless because it is so common for smart people to quickly absorb new information.  They don’t recall being ignorant.  If they do remember being ignorant, they’re not tempted to draw attention to it.

Those who neglect to pursue new knowledge and feed their curiosity become less savvy over time.  The times change, people change, and evidence shifts.  People who figured out the ways of the world many years ago start to lose their grip.  They have dubious clothing, haircuts, and social views.  They overlook emerging evidence.

Real smarts are not really about having a vault of information; it is the act of striving to explore.  I watch new data make its way through the organization, with little or no attribution to me or the original source.  Things quickly become known.  The culture becomes smarter.  It is quietly satisfying.