Welcome to the show.
Thank you for having me.
I have seen some of your interviews.
I have read the book,
and this is one of the most fascinating conversations
that is being had in a completely new way.
Let's talk about bias.
What's interesting is many people think of bias
-as a way to say somebody's racist. -Right.
But, off the bat, we've got to clear that off the table.
Someone being biased
is not someone necessarily being racist.
That's right.
And, I mean, all of us,
uh, have a vulnerability to-to bias.
And, um-- and the book really looks at the science behind it.
-Right. -And, um, um, I think--
But implicit bias can be defined as, uh,
the, um, beliefs and the feelings that we have
about social groups that, um,
can affect our, you know--
our decision-making and our behavior,
even when we're unaware of it, so...
It's interesting, because, you know, most of us hear
-the term "bias" or "implicit bias," oftentimes, -Mm-hmm.
-when we're talking about police. -Right.
You know, we'll hear that police have implicit bias,
as they will stop African-American people
or-or m-minorities at a higher rate
-than the general population. -Right.
And-and that plays into the why.
But-but how does bias affect somebody's ability
to do their job as a police officer?
Well, it-it could affect, um--
So-so, in this country, there's an association
-between blackness and crime. -Right.
And that association could, um, influence, um,
you know, the decisions that officers make
and the actions they take,
again, even without, you know, knowing,
-that it's affecting them. -Right.
You-you actually worked with, uh, Kamala Harris
-in-in implementing bias training -Yes.
with police forces.
How-how do you begin that?
Like, what do you say to somebody?
-Be like, "Now, when you see the black person, no. -(laughing)
Whatever you're thinking, no"?
Like, how do you-- how do you teach someone to not be biased?
(continues laughing)
-(laughter) -Sorry.
(applause)
So, um... so, the idea is to, uh...
(laughs, chuckles)
-I'm sorry. (laughing) -No, please, I mean...
So, um... (chuckles) So, what you do is,
I mean, you-you go in and you teach them what bias is,
what implicit bias is and-- but you also, uh, teach them
the conditions under which it's likely to be triggered.
And so you want them to be mindful of those conditions
in order to try to protect themselves from having,
uh, that bias affect, um, what they do.
Right. That-that was-- that was another amazing thing
that I learned from the book
and that is bias may not be on the surface.
-It may be triggered by an event-- by stress, -Yes.
-by-by panic, by... -Right, right.
So what you're saying is there may be an officer
who's fine all the time.
He doesn't see black people as a threat, he doesn't...
-But then, when-when a situation becomes stressful... -Right.
-...all of a sudden, his bias kicks in? -It could. right.
-It's like an allergy. -Right.
-(laughter) -Yeah.
I... I hadn't thought about it that way before, but... yeah.
Well, you're-you're a genius, I'm a comedian, so, I mean...
(laughter)
So-so, yeah. I mean, so, some situations
where you're stressed, where you're, um, threatened, uh...
-Right. -...where you have to think quickly,
make decisions really fast...
Um, so all of those, um, situations could trigger bias.
It could make it more likely
that you're going to act on that bias in some way.
-Right. -And so, you know, we as individuals,
we could try to protect ourselves from bias
by slowing it down, you know, right?
Um, by, uh, relaxing,
by, um, you know, you know, towards, um,
you know, combatting, uh, the conditions that we know,
-uh, are gonna produce it. -Interesting.
Um, and you can do that, also, um, at the organizational level,
so, a police department could, um, develop strategies
and-and policies that, uh, don't put their officers
-in situations where they have to think fast... -Right.
...um, and, you know, um, you know,
where they're under threat and so forth, and so the...
Right. Try and find ways to slow it down
so that you are less, I guess, you know,
-less at risk of your bias kicking in. -Right.
If-if we... if we talk about bias as a police issue,
-it seems easy for everybody to understand. -Okay.
But one of the most powerful stories you-you write about is
the story of bias in your family
-as it affected your son. -Yes.
-And you-you tell the story of your five-year-old son. -Yes.
And you're in a plane together, and he looks over,
and he sees a black man with dreadlocks,
and he says, "That man looks like Daddy."
-Right? -Yes. Yeah.
And you go, "Oh, yeah, well, he doesn't look like Daddy,
but why do you think that? And he's like, "I don't know.
He just reminds me of Daddy."
And then your kid says, "I hope he doesn't rob the plane."
-Yup, that's right. Yes. -Right.
And you ask him-- which is really fascinating--
you say to him, "Well, why would you say that?
Would Daddy rob the plane?" And he's like,
"No, I-I don't even know why I thought that.
I just... I just..." That moment, I mean, as a mother
and as somebody who studies this,
must have been fascinating for you.
What do you think that displayed,
I mean, of a five-year-old child who is black?
Right, right. I mean, it-it... it really, um, underscores
how, um, sort of, you know, all of us are living
in this world, uh, where we are absorbing,
um, you know, you know, what's out there.
-Right. -We're absorbing, uh, what we see,
and we're absorbing these associations
that are getting made.
And-and so, my child, um, he, you know, picked that up,
right, from living in the world,
from, you know, from, uh, being exposed
-to-to everything out there. -Right.
It-it affects, um, what's in here.
And it affects, you know, how you then come to associate,
you know, a particular group
with a particular behavior or trait.
Uh, but then you don't know exactly when you learn that.
So you don't have to...
Like, I think people think that, oh, well,
you know, children, um, learn to be, um, racists, say,
-because they have racist parents... -Mm-hmm.
...who will tell them, you know, that, um,
-you know, these people are like this. -Right.
You stay away from them.
But you can live in the world and just absorb that
by just watching how people behave and, just, you know...
-Wow. -Yeah, it-it...
You don't have to be explicitly told, um,
about a group-- um, you can... you can learn that for yourself.
And that's... that's what a child's job is,
is to pick up what goes with what,
you know, what correlates with what...
-Right, pick up what is not said, effectively. -Yes. Yeah.
Do you think that it helps to have...
narratives and images and ideas that counteract that?
You know, I... I remember a really beautiful conversation
that I... that I watched.
It was, um, Muslim actors who were speaking
about how the portrayal of Muslims in Hollywood
has affected how many people in America and around the world see
-Yeah. -a brown person who is Muslim.
They go, "This person is bound to be a terrorist,"
because that's all they see, and they said:
We need more roles where Muslim people
are just Dan in Accounting.
You know? So you go, like: This person could be anything.
-Yeah. -But does it help to see images that counter it,
or is it... is it more powerful than that?
Well, I mean, I think it does help to see those images,
-but that's not, you know, the cure, right? -Right.
Um, so there are studies that are-are...
that have been done by researchers
showing that even when, say, African Americans are placed
in positive roles, in powerful roles on television,
um, they... the actors surrounding them
can give them sort of negative treatment,
-or negative non-verbals that then people pick up -Wow.
just watching the show, and so you can become,
you know, more biased
by watching someone treat a black person in a negative way.
So if Michael Kosta gives me the stank eye,
then people out there could become biased.
-I'm watching you, Michael. I'm watching you. -Where is he?
Um... let's talk about companies as well.
-Okay. -You do work with corporations as well
to try and help them combat bias.
-Mm-hmm. -Um, Airbnb is one of those,
and we know that there are many stories where Airbnb
was struggling with people who didn't want
to-to have black people stay in their houses
-Yes. -and how they rented affected it.
How do you begin implementing this on a corporate level
and then expanding it into the public?
Yeah, so, I mean, I work with them, just informally.
-Yes. -They sought me out as a social scientist
who does work in this area, and, right,
they were having issues, uh, with racial profiling,
-Right. -basically, on the platform.
And so, um, yeah, so they, um, tried to combat it
in multiple ways, and so, um,
one was by hiring someone to come in
and to, um, you know, to, um, you know,
to kind of talk to people about what their experiences were,
-Mm-hmm. -uh, by looking at the law
to see, you know, what could be done there.
They settled on actually having people sign a community pact
saying that, uh, basically, that they wouldn't be biased
-Right. -and that they understood
what the norms of the platform were, you know,
to not disqualify someone from staying in your home
-Yes, yes, yes, right. -because of your race, and so forth.
So they did all that, and then they also put together
a team of people, it was an antidiscrimination team,
um, that meets on an ongoing basis,
and sometimes I meet with them as well
to try to think about ways that, uh, will...
will, um, you know, you know, shut it down,
or at least, um, you know, combat it in some way. Yeah.
Before I let you go, one issue that has been discu...
uh, discussed, um... quite intensely
has been the issue around artificial intelligence
-and bias. -Yeah.
You know, we've seen so many stories
of, like, artificial intelligence
used in court cases
or artificial intelligence used
to determine people's threat levels
or, you know, and so on and so forth.
But what's been interesting is the realization
that computers and A.I. aren't biased.
They are just exposing the bias
-in the people who program the computers. -Right. Right.
Do you think that that's something that we can fix?
-And if so, how? -You know, when...
We need to deal with bias, right?
So when we don't deal with it,
um, it can just migrate to-to some other place.
-Right. -And, so, I think, um, we sort of think about A.I.
as doing all these good things
and, um, sort of, you know, doing a service to us.
-But in that way, they don't always. -Mm-hmm.
Um, so, I think...
You know, I'm actually using A.I.
-with the policing work now... -Right.
...to look at body-worn camera footage,
and-and there it's really helpful
because you can look not just at an isolated case
where there's a sort of, um, high-profile case
-and try to adjudicate right and wrong. -Yes, yes, yes.
You can actually look across thousands of traffic stops,
is what we're doing,
and look at how those interactions are unfolding
-and to try to pick up patterns in those interactions. -Right.
Um, and to see the extent to which, you know,
drivers who are black versus white
are treated differently and so forth.
So I feel like there's huge promise there to...
The-the A.I., um...
Using A.I. to actually analyze this footage
can give us a window into what is really happening
on the ground, the blow-by-blow
-as it's unfolding in real time. -Right.
Before I let you go, um, I really had a fun time
reading about one particular incident
or-or a series, rather.
You know, it's interesting. So many people will say,
"Oh, bias is not real" or "We don't see it."
Companies, businesses, et cetera.
But there are a group of criminals in Oakland
-who are very aware of bias. -Oh. (chuckles)
And what they did was really interesting.
Could you tell the audience what exactly these criminals did
and how they used bias in their favor?
So, yeah. So, um, this was when I got to Oakland, California,
and I was working... just starting work
with the police department there.
And, um, their... The crime rate was going down,
but there were a series of strong-arm robberies
that always seemed to happen in Chinatown in Oakland.
-Mm-hmm. -And they would involve middle-aged Chinese women.
-So, they were snatching their purses from their arms. -Right.
Um, and, you know, so, this has real...
this really stymied, you know, the police officers.
They couldn't figure out,
-um, how to, you know, catch the robbers... -Right.
...because when they would round people up
and say, "Is this the person?"
-the middle-aged Chinese women couldn't tell you. -Right.
And when they asked the-the robbers,
"Well, why are you going there? Why are you going to Chinatown?"
And they said, "Because, you know, uh,
they can't tell the brothers apart."
(laughter)
That's...
That is one of the most horrible,
fantastic stories ever.
And the book is full of them.
-Thank you so much for joining us on the show. -Thank you.
Wonderful having you.
Biased is available now.
Dr. Jennifer Eberhardt, everybody.