99.9% of what our brains
process is unconscious.
And without a doubt,
somewhere in there are biases.
Biases about women in the workplace.
Biases about people of different races.
And all these biases are things
companies like Google,
Starbucks, and even Insider
have been trying to train out
of their workforce for years.
But is it working?
Calvin Lai: We don't know.
We really don't know.
Narrator: And a lot of that uncertainty
has to do with our understanding
of implicit bias in general.
So, what do we know?
Implicit biases are stereotypes
that we form about
certain groups of people.
Every day, your amygdala processes
and categorizes billions of stimuli.
And because of this, almost all of it
is happening automatically.
Every experience you have,
every bit of socialization,
every piece of media
is processed and stored
by a stereotyping neural network,
creating a database of shortcuts
that your brain can pull from.
And while it's helpful to see
a big metal box with wheels
and immediately know it's a car,
categorizing people in
the same way is harmful.
And that's where the implicit
association test comes in.
The IAT is part of many
implicit bias trainings.
It's supposed to establish a baseline
for each participant's unconscious
biases by measuring them.
The problem is, we don't
actually know if it does that.
Lai: I think that the
implicit association test
is an imperfect measure.
It's been incredibly
useful for researchers
to understand how the mind works
in ways that are not self-reported.
But if you want to use it
as a diagnostic measure
of how racist or sexist you
are or something like that,
it's not gonna tell you that.
Narrator: A psychological
test is usually measured
in two ways: reliability and validity.
Test-retest reliability means
that people should be able
to take the test over and over again
and get nearly the same results each time.
A perfect reliability score is a one,
but a test is solid if
it scores at least 0.7.
But studies have put the race
IAT's reliability at 0.44
and the IAT overall at 0.5,
well below acceptable standards.
This means when a person
takes the test multiple times,
they get notably different results.
And experts can't say for sure
whether that's because
the test is a bad tool
or if the concept of implicit
bias actually fluctuates.
Lai: So, one of the theoretical
ambiguities right now
about the nature of implicit bias
is the extent to which it
reflects something deep
about a personality or
an enduring attitude
versus something that is more fickle,
something more like an
emotional state or a mood.
Narrator: Either way, this discrepancy
makes it difficult to rely
on the results of the test.
Which leads us to validity:
Does the test actually
predict what it says it does?
The IAT was intended to and
is currently used in a way
that is supposed to link
implicit bias to behaviors.
At least four different meta-analyses
between 2007 and 2015
looked at this exact thing.
And all of them suggest that the IAT
doesn't really predict
behaviors that well.
Lai: It turns out that
predicting discrimination
is just difficult, full stop.
Narrator: But even if the
IAT was conclusively valid
and reliable, implicit bias
trainings still have a problem:
Acknowledging your bias does not mean
you're gonna act less racist.
At least one study found
that recognizing a bias
is a necessary step to getting rid of it,
but it won't solve the problem on its own.
Lai: You want to make people
feel enough motivation,
maybe something like enough guilt or shame
to be actually motivated to do something
about the problem of
bias or discrimination.
Narrator: And some studies
suggest that the trainings
can even make the problem worse.
They have the potential
to dredge up stereotypes
and make a person act on them more.
So, how do we make sure that
implicit bias trainings are effective?
Standardizing the programs is a start.
Lai: I've seen ones where
the IAT is never mentioned,
let alone used in any way.
I've seen ones where they
put a measurement of bias
in the middle of the thing,
and they do it as a group activity.
Some of them are just
purely just a collection
of PowerPoint slides with
nothing else attached.
Narrator: One 2016 meta-analysis
of over 40 years of
diversity-training data
found that the programs were successful
if they focused on skill development
and were conducted over
a long period of time.
Many trainings end up being reactionary,
half-day or shorter events that end up
being more performative than impactful.
It's like using a Band-Aid
to treat a broken bone
instead of a comprehensive treatment plan.
Lai: Exactly!
You might not be so certain
that any individual initiative works,
but we know that, generally,
when firms or companies have more of them,
their diversity and inclusion
outcomes tend to be better.
Narrator: Harvard Business Review
found that a combination of things
like college recruitment,
mentoring programs,
self-managed teams, and task forces
have increased diversity.
Diversity task forces alone
boosted Black women in management by 23%.
Instead of focusing on the
thoughts of individual employees,
these tactics address the
bigger, systemic issues
that make bias a problem
in the first place.
So, just because we don't know for sure
if implicit bias trainings
work doesn't mean they can't.
We should be asking ourselves
what we do know we can do differently
in order to ensure lasting change.
I just want to be very
clear that the information
we're presenting here has to
do with implicit bias trainings
and their effect on diversity
and inclusion within companies.
Bias is very much real, and it's something
that we as individuals need to continue
being aware of, checking, and unlearning.
So, please, continue the
conversation in the comments below
and in real life, and subscribe
for more "Deep Science."
