Summary Series Chapter 1: Unconscious Bias is Everywhere
In this post, we explore how Iris Bohnet, Harvard Behavioural Economist, explores the challenges of unconscious bias plaguing our lives, especially in the workplace.
As part of our Summary Series for Behavioural Design & Gender Equality, Bohnet introduces the topic of gender inequality with an experiment that perfectly encapsulates the nefarious role of unconscious bias.
Competence v. Likeability
In a social experiment, university students were split into two groups and given an identical case study. It described the actual life of an entrepreneur turned successful venture capitalist who possessed strong networking skills and a sociable personality.
The difference? The entrepreneur’s name was called Howard in one text and Heidi in the other.
Both groups were subsequently questioned about what they thought about the entrepreneur’s personality.
The results? Both groups saw Heidi and Howard as equally competent. but Howard was seen as the more likeable colleague. In fact, Heidi was seen as selfish and not “the type of person you would want to hire or work for.”
So what does this say? As Facebook’s COO Sheryl Sandberg explains it,
“success and likability are positively correlated for men and negatively correlated for women. When a man is successful, he is liked by both men and women. When a woman is successful, people of both genders like her less”.
It should be noted while gender inequality typically refers to women suffering penalties in the workplace, it actually refers to social penalties incurred when someone is working a counter-stereotypical job.
How Biased Are You?
One of the things often overlooked when it comes to bias is its unconscious nature. That is to say, a lot of us do not intentionally show favouritism to certain groups of people. These inclinations are a product of our cognitive faculties and the environment.
Still think you’re immune to most biases and can be counted on to make impartial decisions? I invite you to try the Implicit Association Test created by Harvard. It seems like a boring test, looking at word associations and how quickly we make them. But this is the most fundamental of evidences for implicit bias.
Sad as it may seem, it is difficult to unravel implicit bias and its causes. Take statistical discrimination. In knowing that on average, about one third of all surgeons in the US are female, we tend to first think of “man” when we see the word “surgeon”. People therefore base their assessment of an individual person on group averages.
This is not to say these mental shortcuts do not serve us well. Categorising people helps us to get much of the initial hassle of finding out more about a person. We are said to be economising our cognitive effort. But in situations of incomplete information, we can misjudge individuals.
But at times, statistical discrimination can be the engine behind the exacerbation of inequality. Take the effect of having a child on salaries. It is a premium for men and penalty for women. Some of this is because employers expect mothers to reduce their working hours more so than fathers. While there may be empirical evidence for this, such a policy slant would only serve to encourage more women to leave the workforce.
So Are We Doomed?
So biases are omnipresent. In our natural selves, it is clear to see that we may be disadvantaging women, even if we don’t want to. Well then, bias has an antonym right? Why can’t we just de-bias people then? Well we can certainly try… And that’s what we’ll explore in the next chapter. Seeya!
