Unconscious bias

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EqualBITE 74 Unconscious bias
Unconscious
bias
Derek Jones
What is bias?
We are not aware of most of our cognition and
thinking (Mlodinow, 2012; Norman, 2005). Each and
every day we respond subliminally to a huge range
of events and conditions. Most of the time we do not
question or challenge these cognitive processes since
the whole point of them being subliminal is for them
to process things efficiently in the background.
We use a number of different techniques to enable this
effectiveness and many of these lead to biases in our
enacted thinking. Bias is essentially pre-existing or primed
knowledge and beliefs brought to bear on immediate
situations and contexts. Without such shortcuts, we
would be far less able to operate effectively in the world.
But there are times when these shortcuts can have
negative effects – the snap judgements we make for
unknown reasons; the immediate reactions we have
that result in other consequences; or simply the benefits
we take for granted as we go about what we think of
as a normal life (seen from our own perspective).
When these individual decisions add up we start to then
see larger scale biases. The gender pay gap is still there
(https://www.gov.uk/government/consultations/closing-
the-gender-pay-gap), even in academia. But the gap itself is
a symptom of deeper structural, social and political issues.
In Moss-Racusin et al. (2012), both male and female science
professors rated female applicants as less competent than
male applicants and they offered female students a lower
starting salary. And students of both genders tend to rate
female academics lower than male (MacNell et al., 2014).
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75 EqualBITE Unconscious bias
There tends to be no ‘consciously’ executed
rationale to bias, although when bias is
identified, we are more than able to create
such rationales (Ariely, 2012). On top of
that, the bias against bias is difficult to
research and address (Moss-Racusin et al.,
2015). We don’t like to believe that we are
not entirely in control of our own thinking.
Being reminded that our decisions, ideas,
attitudes, or actions may have resulted
from some other source than ‘me’ can
be a difficult situation to accept.
But accepting and using it can be a very
valuable, albeit challenging, process.
It works both ways
Gender bias can work positively and
negatively for and against both genders
mainly because stereotyping is one of the
primary underlying mechanisms (Mlodinow,
2012). For example, we readily (and
subliminally) make use of appearance when
we ascribe, accentuate or confirm attributes
to people, such as lower reporting
of shoplifting if a person has a tidy
appearance (Steffensmeier & Terry, 2016).
This simple social appearance stereotyping
is a reasonably trivial and obvious example.
For example, in Brescoll et al. (2010),
women working in roles associated as
male were judged far more harshly when
compared to men working in those roles.
When they made mistakes, people
in gender-incongruent jobs – female
police chiefs and male women’s college
presidents – were ascribed a lower
status and seen as less competent
than their gender-congruent
counterparts. (Brescoll et al., 2010)
A similar result is reported in Brescoll
et al. (2012), where a negative impact
on male subordinates was observed.
The lesson here is perhaps that tackling bias
wherever it is found or can arise is simply
a healthy thing to do for any community.
The unfair unevenness and asymmetries
observed in social groupings have to be
continually appraised and challenged. But
it is perhaps also true that, as with the
title of the study by Brescoll et al. “Hard
won and easily lost: the fragile status of
leaders in gender-stereotype-incongruent
occupations” (Brescoll et al., 2010), it can
be so easy to assume that a problem has
been sorted and forget that the problem
is far deeper than the symptoms.
The other lesson is that when working to
resolve an existing imbalance, the really
hard work perhaps only starts when
a new balance is being tried. Implicit
biases do not stop operating and can
arise in particular ways when a shift
in normative positions is realised.
For example, women being perceived as
‘coldly ambitious’ instead of ‘assertive’
(Okimoto & Brescoll, 2010). Moving
to a more even gender balance may
bring to the surface a number of
other symptoms of deeper issues.
The effort required to identify, challenge
and then keep working on implicit
biases can be significant. But there are
practical things that can be done to
affect bias, and we review them below.
Balance your work
When creating anything (when creating
materials for a general audience) get into
the habit of balancing it wherever possible.
• Imagine a wider audience than just
yourself. There is strong evidence
to suggest that gender gaps in
educational attainment, especially in
STEM subjects (science, technology,
engineering and mathematics),
are socially constructed (Good
et al., 2010). We tend to write for
ourselves and that’s OK but once
you have that first draft, imagine
reading it to a varied audience. This
is healthy for your own ideas and
thinking as well as your readers’.
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EqualBITE 76 Unconscious bias
• Use gender-neutral language; use all
the tricks in the writing book to avoid
any gender preferences. Studies show
that gender neutral language alienates
far less than gender-specific (‘he’ or
‘she’ only) or gender-balanced (‘he and
she’) text (Stout & Dasgupta, 2011).
• Use examples of a range of different
people and role models: using relevant
examples of people that students can
identify with (in terms of in-group) is
a well-known effect in maintaining
educational attainment. In terms of
gender, the study by Good et al. (2010)
shows that mixed examples of gender
in images in science textbooks lead
to comparable attainment results in
students (when compared to single
gender or counter-stereotypical
images). Similarly, simply having
female role models in maths can
improve female student attainment
(Marx & Roman, 2002), although
the wider effects are not as simple
as a single result (see below).
Increase positive exposure to imbalances
This is perhaps one of the simplest and
most obvious changes that can be made
– if you have staff that are representative
of students, attainment will be affected
positively. We all identify with a certain
amount of self-similarity and this
personal bias is very often projected.
Having female lecturers and professors
can reduce the attainment gap observed
between female and male students
in STEM subjects by improving female
attainment (Carrel et al., 2010). Importantly,
this research also showed that as the
level of study increased, so too did the
importance of gender representation on
attainment – that gender representation
at all levels of study is essential to
achieve equipotential achievement.
Having said that, recent findings show that
students perceive female professors to be
generally less capable than male professors.
Prior bias in terms of role assignment or
gender capability assessment is something
that can take time to change when it
is acculturated socially. Similarly, the
counter-intuitive result shown in Hoyt
& Simon (2011) suggests that simply
having role models is not enough to
engender an immediately positive effect.
But there is evidence to show that
exposure can work on short and long-
term bias structures and that such
longer-term benefits are the real reward.
For example, Beaman et al. (2008) show
that existing and prior biases remain
in terms of preferring male leaders
in local politics but that stereotypes
of gender roles are weakened with
repeated exposure to female leaders or
politicians. Most significantly, this seems
to have a cumulative effect over time and
exposure, leading to longer-term changes
in gender balance as demonstrated
through local election results.
Reduce the opportunities for bias
to be expressed or realised
In studies on employment
and pay negotiation:
Reducing the degree of
situational ambiguity constrains
the influence of gender on
negotiation. (Bowles et al., 2005)
It seems that, with ambiguity, comes
the opportunity to allow implicit bias to
emerge. In certain economic negotiations,
this emerging bias affects women
negatively in terms of outcomes – lower
salaries or increased payments.
But this also allows a fantastic opportunity
for simple, good practice: being explicit and
very clear about standards and conditions
of employment can reduce gender pay gaps:
In job negotiations with clear industry
standards, there were no differences
in salaries negotiated by men and
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77 EqualBITE Unconscious bias
women. When industry standards
were unclear, female MBAs accepted
wages that were, on average, $10,000
lower than those accepted by
male MBAs. (Bowles et al., 2005)
Similarly, having rigorous, transparent and
accessible processes for decision-making
can also help reduce the ambiguous
‘spaces’ within which bias can emerge.
For example, removing gender bias
through anonymising hiring processes was
demonstrated in the famous blind audition
research in Golding & Rouse (2000).
Another technique reported in Bohnet et
al. (2012) demonstrates reduced bias when
joint evaluations were carried out when
compared to single evaluations. Again, the
behavioural ‘nudge’ that Bohnet et al. refer
to may result in reducing the opportunities
for unchecked biases to fully emerge.
Beware of priming
Being told you are good at something
can have different effects on different
individuals and different groups of
individuals. A specific gender grouping
study is provided by Shih et al. (1999),
where Asian-American women were
primed to consider themselves as either
Asian or women and then immediately
tested in maths. In the former group, they
performed better than in the latter.
The hypothesis here is that being
reminded that you are in one group
affects your own view of yourself and
even your ability to do certain things. Of
course, this also relies on the prior bias
that ‘Asians have superior quantitative
skills’. More disappointingly it also relies
on the corollary too – that women have
lower quantitative skills and self-identify
with that group and group stereotype.
When adjusted, neither of these
stereotypes is true in and of itself –
but the threat or promise of it is more
than enough to have an effect.
So this priming effect took a prior bias
and seemed to leverage it positively to
enhance student attainment. But great
care has to be taken when priming
of any kind is utilised – not least in
terms of the ethical issues involved in
deliberately (and secretively) affecting
other people’s cognitive states.
In addition to the ethics, the actual
responses will vary depending on the
individuals being primed. For example,
reinforcing positive reactions in some
might lead to stereotype threat in
others (see Stereotype threat).
In fact, research shows that all
you need to trigger an in-group
perception is simply to be told that
you are in that group (Mlodinow,
2012). So, think before you prime…
Don’t rely on meritocracy
One of the basic arguments against
positive discrimination is that of pure
meritocracy – that it should only be talent,
skills or ability that ensures an individual’s
success. Unfortunately there aren’t too
many absolutely neutral methods to
measure such merit that do not also call
into question other basic skills and abilities.
We rarely employ or make decisions based
on single metrics and very rarely are we
sufficiently objective to do this properly.
For example, Castilla & Benard
(2010) found that explicitly applying
meritocratic methods tended to increase
gender imbalance in favour of men.
Participants in the meritocratic
condition showed greater preference
for the male employee over an equally
qualified female employee.
Interestingly, when participants were
instructed to apply a values-based
method and use ‘managerial discretion’,
the imbalance moved significantly in the
opposite direction (towards women).
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EqualBITE 78 Unconscious bias
This was thought to be due to priming
that suggested an imbalance did need
to be addressed in favour of women.
But perhaps most significantly, when
participants were instructed to take a
values-based approach without using
discretion, then the imbalances largely
disappeared! This may tie in with findings
in Bowles et al. (2005) that by removing
space for bias, gaps can be reduced.
To put it simply – if we are left to not
only measure but to create the method
of measurement, we might be getting
it very wrong (see Defining excellence).
But if we are given good methods by
which we can measure (even using
subjective criteria) and clear space
within which such measurement
should take pace, then most people
are actually pretty good at being fair.
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