Advancing Women’s Leadership: Blocking Bias at Work


[MUSIC] Hello and welcome everyone. Good to see you here. There’s plenty of room if you
want to come down closer. What I want to do with my colleague Lori
Mackenzie today is talk about how we might advance women’s leadership. And, I thought what I would do to get us
started on that, is give you a sense of where we are in terms of women’s
leadership in the United States today. So, the slide here,
when you take a quick glance at it, what you will notice is that
women are underrepresented, and continue to be underrepresented at the top
levels of all sectors of our society. So, the first two bullet points
show us the dearth of women in the corporate sector. If we drop down to the third bullet point, we see that women make up
only 18% of our Congress. And this was after a year which,
supposedly, was just a watershed of
women entering Congress. We’re still at only 18% women. University presidencies of our top
research universities, only 17% of women. And as low as these numbers are,
if we were to drill down and look at women of color,
they’re considerably lower. Now this is actually really quite
surprising in one way, and that is, it’s been over 30 years now since
women started outnumbering men and they’re earning a bachelor’s degree. So any of you who are here
from the class of 1980 or 1985, you were in college about the time
when that tipping point happened. And if you graduated in say 1990, you are
at a period of time here on the farm when people were very optimistic about what was
going to happen with women’s leadership. Matter of fact, if you read books
at the time about gender equality, the last chapter says,
now with women flooding into college and getting bachelor’s degrees,
it’s only a matter of time. But here we are 30 years
later with these numbers. And when I think about why
this is a problem, and maybe that seems obvious to people who
come to a talk on women’s leadership. But I want to point out that in addition
to this being a problem for women, there’s a societal cost to this. We have to ask ourselves,
what important questions and problems aren’t being solved by our
companies, our governments, and our universities if women’s voices
aren’t being more fully included? Or to flip that around to be positive
about it, think about what we could be doing in our governments, in our
universities, and in our companies if we were more fully drawing on all the talent
that women bring to our society. So that’s what I want to
talk about with you today. Clearly these numbers are low for
all kinds of reasons. I teach a class, one of the freshmen
Thinking Matters class, on this topic and we spend the entire quarter talking
about all these reasons and how to get beyond this. Today I want to highlight just one barrier
to you that I think is really important. And that is, I want to draw out the way
that stereotypes about gender and work lead to a bias in terms of how
women are evaluated in the workplace. And so what I’m going to do is spend some
time describing that problem to you and showing you that it’s more consequential
than perhaps we might think. And then I’m going to turn it over to
Lori Mackenzie, who’s going to talk about some of the tools that we’ve been
developing to move beyond that bias. And to create workplaces that more fully
embrace the talent of women and men. So, I want to just start off with a
research study that you may have heard of, that got a lot attention
when it came out and really illustrates the kind of things
that I want to share with you today. And as this picture shows here, the
context of this study is orchestras and the hiring of musicians into orchestras. So in the 70s and
80s in the United States, women made up only 5% of
all orchestra musicians. So this was a really male type space. And we do a lot of work at the Clayman
Institute in tech, and I think about this. And this was more male type
than tech is today, okay. And so the major orchestras around the
country became concerned that perhaps one of the reasons they were so few women is that there was a bias
against women in the audition process. And I think about that in the 70s and
80s, somebody making that suggestion, I’m sure they were lots of people that
thought that that seemed ridiculous and doubted that that was the right answer. But to these orchestras’ credit, what they
did, rather than just debating whether or not this was the case, they decided
to do an experiment and find out. We’re always trying to urge the companies
we work with to do an experiment. Let’s see, so what they did is they
introduced a screen between the musician auditioning and
the panel of judges, okay, so that the panel of judges could no longer
tell if the musician was a male or female. Now to make it a really good experiment,
they found out they also needed to put carpet down on the floors because
heel clicks were giving it away. So you want to to make it a really
nice experiment you couldn’t tell who this person was. And what they found was rather dramatic. That is the introduction of the screen
increased the odds that a woman would make it past this first round
of auditions by a full 50%. So it made a really big difference. If you fast forward to today, women make up 25% of orchestra
musicians in our top orchestras. 40% overall,
still not at parity in orchestras, but the screen really did make a difference. I lead off with this example because it
illustrates the two things I want to talk about with you today. One is that stereotypes about gender
affect how women are evaluated. Without this screen, women were not being
seen as competently as they actually were. And secondly the screen, there are going to be tools that we can
develop that are going to allow us to block the negative effects of
stereotypes on how women are evaluated. Now, we’re not going to be talking
about screens later today, we’re going to have to be more
creative than that, right? But since most of us couldn’t live our
work lives behind a screen and wouldn’t want to, but we do have some tools I
think that can help us get beyond bias. So that’s where we want to get to today. So I’m going to end up with this
as my conclusion, okay, and then we’ll work on getting there. I want to first show you how stereotypes
limit women’s leadership, okay. But all the way through,
I want to draw up one more thread, and it’s not only that these stereotypes
are limiting women’s leadership, they’re actually interfering with the goal
of having meritocratic workplaces. Meritocratic workplaces that are essential
to innovation and discovery. What I mean by that is this. If we want to be as
innovative as we can be. And if we want to discover the best
scientific findings we can find on our universities and in our companies. It’s essential that the best ideas and
the best talents rise to the top. And if that’s not happening then
we’re interfering with the goal of meritocracy in addition to
limiting womens’ leadership. So, let’s talk a little
bit about how this works. My job is to sort of review
some of the social science and share some really cool studies with you. But, before doing that, I want to talk
a little bit about the word bias itself. Bias is a word that
often people don’t like. It has kind of this ugly connotation to
it, as if you’re calling someone sexist or racist or something. But that’s not how I’m going to
be using the term here today. When I talk about bias, it’s simply
going to be an error in decision making. So if we think about the orchestras again,
I think we can safely assume that most, if not all of those judges wanted
to hire the best musician possible. They didn’t get out of bed in the morning
to discriminate against women, that wasn’t their goal. They wanted to hire the best
musician posssible. But for reasons I’m going to explain,
once they saw the gender of the musician, that affected how they saw that
person’s ability and skills, okay. What we’re going to see here today, is all
of us are prone to these sorts of biases. They’re unconscious biases if you will,
okay, which is the bad news. But the good news is going to be
that there are procedures in place, that we can put in place,
that keep us from acting on these biases. So I always describe this as kind of
a no blame, high responsibility message. So that’s bias, what does that tell
us about how stereotypes work? So the key idea about stereotypes that
we want to talk about today is that stereotypes function as what we might
think of as a cognitive shortcut in information processing. So let me just talk about
the orchestra one last time. Imagine that orchestra is auditioning
like 100 musicians for just two or three openings. And that would not be uncommon
at a major orchestra. If you’re one of those judges, that’s
a lot of information to take in, right, 100 different people performing. You’re having to keep all
that information straight. In those information heavy contexts,
we understandably look for shortcuts to help us process
all that information. And that’s not a bad thing. I mean, none of us today, in our jobs, as busy as we are, could get anything
done at work if we didn’t have some sort of shortcuts that we took in
processing that information. But unfortunately,
stereotypes about gender and other categories of people function
as one of those shortcuts. And when they do, they’re going to create
some, I think, undesirable outcomes. So, how does this work? This slide here summarizes 30 years
worth of work on stereotypes, so I’m going through it quickly, 30 years. So what the research shows us about
stereotypes, is that we instantly, within milliseconds, sex categorize
any person we interact with. That is, we take notice whether we think
that person is male or female, and we do it in just milliseconds, okay? Cannot help doing it. In the United States we do this with race,
as well. So the things I’m going to talk
about with gender, work for race as well in the United States. In other countries, they have different
things that they may instantly categorize people on, but in all
known societies, sex is one of those. Why is that important? Well, once you put someone in a category,
or put anything in a category, you unconsciously, or implicitly expect that
person to be something like that category. So, research shows here,
with data from over 30 countries, that what happens when we
categorize someone as a man, is we’re more quick to
associate him with leadership. All the words that have to do with
leadership, we can make these quick, unconscious, mental
associations with leadership. Whereas with women instead, we make
slower associations with leadership, but quicker associations with things like
being a supporter, a follower and contributor, but not a leader. What this means, is that for men, we tend
to expect men to act more like leaders. Psychologists called us agentic. To act active and capable of getting things dona and
decisive, and the way that leaders act. Where we expect women to be warm and
communal, nice, concerned about others. The kind of things we might expect
of someone who is being supportive. And we certainly don’t expect women
to be dominant and assertive, okay? We might expect men to be,
again, at an unconscious level, better at male-type tasks like technology,
and women better at female-type tasks. These stereotypic expectations that
occur our of awareness are important because they frame or
shape how we judge people’s performances. Such, the very same performance
looks slightly different to us if it’d been offered by
a man versus a woman. And we saw that in the case
of the orchestras. The bottom bar, the problem with this
then, when we’re thinking about the world of work and
how people might advance into leadership. These quick associations effect how
we evaluate people in the workplace. Whether when we’re hiring people,
thinking about promoting people, who to put on projects. It effects the kind of opportunities
we give to people in the work place. And it effects the amount
of influence people have. When someone make a suggestion,
does it sound like a good idea, okay? Does it sound like something
worth funding, okay? I want to talk to you today about a couple
of ways that these stereotypes work, and show you some examples, and then we’ll
turn to the important ending point that we want to get to today,
how do we block these effects? Okay, so
the first way that way stereotypes work, is they shift the standard
that we use to judge people. So it turns out our standards
shift around a little bit, depending on if we’re evaluating
a man versus a woman. Or if we’re evaluating,
in the case of race, someone who’s white
versus a person of color. If you think about why this would be,
I’ll use gender as an example here. If a woman performs well, and especially
if it was in a male typed domain, this runs counter to those
quick associations we have. So one thing that we tend to do, is to
more carefully scrutinize her performance, and we do this even in a situation
where we’re in awe of her. So I’ve been talking
a lot about Mary Barra, the CEO of General Motors, Stanford alum. So General Motors announced the new CEO,
and it was a woman. I don’t know about you, but
this caught me by surprise, right? This is the automobile industry. Who would have seen this coming? So I found myself reading and
reading about, how did she get to this point in her life? If General Motors had announced
the new CEO was a man, I probably would have turned the page and
read something else. It wouldn’t have been news to me. But that extra scrutiny can, under certain
circumstances, open the door to bias. So let me give you a couple
of examples of this. I want to start with an example that
comes from the field of psychology. And this is an experiment where what the
authors of this study did, is they they created a resume for a person who had
just gotten his or her PhD in psychology. So it had some publications on it,
teaching experience, stuff like that. And they sent it out to psychology
faculty all over the United States and they said, evaluate this person and
importantly, tell us whether or not you think this person would be worthy of a
tenure track position in your department. The experiment was this. Half the people out there received
a resume with a man’s name on it. And the other half of the psychology
faculty doing the rating, received the very same resume,
except with a woman’s name on it. So this is a really great way to
see whether gender matters, right? The resume’s the same,
the only things different is the name. What they found, was again,
rather striking. 79% of the people who got a resume with
a man’s name on it said he would be worthy of hire. Compared to only 49% of people
who got the same resume except with a woman’s name on it. And in case you’re wondering, it did not matter whether the person
doing the rating was male or female. Male and female raters exhibited
the same level of bias. We find this constantly in these studies
and sometimes this disappoints people. They want women to be
better raters than men. But the issue is, these are stereotypes
that we’re all kind of commonly aware of and they’re affecting our
judgments on an unconscious level. Now, in a second phase of the study,
what they did, is they had people evaluate these same resumes, except now these
people are more experienced, okay? So now we’re talking about people you
might want to move into leadership. So they have more grants,
more publications and the like. And what they found with these
more advanced candidates, is that people wrote four times more doubt
raising statements on the rating forms for women compared to men. So I would need to see evidence she
had gotten these grants on her own, for example. Notice that extra scrutiny
that’s going on there. Or it would be impossible to make
such a judgment without seeing teaching evaluations. Now if you think about it, a teaching evaluation and wanting to
see people’s teaching evaluations before you hire them as a professor,
that’s a very legitimate thing, right? I would hope that we
would want to see that. But the criteria is being enforced more
rigidly for women than it is for men. Now I want to just switch
gears just slightly and show you another very similar study
that was done in the context of race. We work a lot at the Clayman Institute for
Gender Research on gender issues, but a lot of the things that we’re
talking about work similarly for race. So if we’re trying to create
more inclusive workplaces, a lot of the take home messages
here will be the same. So this study was done in 2014. And what the authors of the study did,
is they created a legal memo that was ostensibly written by a third year
law associate named Thomas Meyer, who had gotten his law degree at NYU. And in the memo what they did, is they embedded it with
certain numbers of errors. So there were some spelling errors. There were some factual errors. And there were some analytical errors. And then they sent it out to law partners
and asked the law partner to rate the memo and give the person some
feedback on how they were doing. And so, the experiment very similar to
the last one, the only difference was that half the the people were told
that Thomas Meyer was white and the other half were
told that he was black. But the memo’s the same. And what we find is this, there were three
times more edits and comments written on the black Thomas Meyer’s memo than
compared to the white version, okay? Again, the same memo. And they were twice as
likely to find mistakes. So notice again that extra scrutiny
that’s going on for the person for whom people probably didn’t expect they
were going to be as good to start with. They were doing what they
were supposed to here, right? They were supposed to be
finding the mistakes. But the person over here was
getting kind of a leniency bias. And this is what we see a lot in these
studies is this extra scrutiny of women and people of color. With criteria that’s very legitimate
being applied more rigidly to them. This affected how people rates the memos. Not surprisingly the rating
was considerably and significantly for white Thomas Meyer
than for black Thomas Meyer. And it also affected their
qualitative judgements. So a white Thomas Meyer is generally
a good writer, has potential. Black Thomas Meyer needs lots of work,
can’t believe he went to NYU. So these sort of drastic differences
in how they’re talking about this performance. So you can imagine how this would affect
advancement into leadership going forward. One final example I want to give in this
area comes from some work that I’ve done, and when we think about the experiences
women have in the workplace, the experiences women have in
the workplace are not just because they’re a woman. Because no one’s just a woman, right? You’re a woman, you also have a race,
you have a sexual orientation, you might have children,
you might not, you might be disabled. And all these other things
combine to affect the judgements that we make of people. So I’m doing some work, I’m looking at how being a mother might
lead to disadvantages in the workplace. There’s some literature out there on wage
gaps that show that mothers experience a 5-7% wage penalty per child
compared to childless women, okay? And this is if you’re
comparing childless women and mothers who are in the same kind of jobs. So I was concerned whether this
kind of biasing process might be affecting mothers as well. So what we did as an experiment, where we
had people evaluate either two women or two men, one of whom was a parent and
one of whom was childless. So down in the resume of one of the two
members of the pair you learned that the person was an officer in an elementary
parent/teacher association, okay? So that’s a subtle indicator
that someone might be a parent. You don’t have to be
a parent to be an officer in an elementary school
parent/teacher association. But I don’t really think ever
in the history of the PTA has there been an officer
who was not a parent. So this very effectively
conveyed parent status. Now, before starting the study, what we
did is we pre-tested all of our materials to be sure that we had two people who,
when we didn’t know their gender, and we didn’t know their parental status,
were judged to be equally qualified. So just based on their resumes and
performance evaluations. So there was no difference. Put names on the files,
mark one as a parent. What happens? All of a sudden the mother is seen
as significantly less hire-able. They said they would recommend 84%,
so they would recommend the person who is childless,
compared to only 47% for the mother. Further if they were
going to hire the person, they were going to pay her
significantly and substantially less. Okay?
So we see some evidence of a bias. For fathers no such bias. In fact fathers are actually preferred
compared to childless women and if they are going to be hired they
are going to be paid significantly more than childless men. So we see how parenthood is working
differently for moms than for dads. We drilled down one more layer to try
to figure out what’s going on here. And what we found is that people were
stereotyping the mothers as being less competent at their jobs and
less committed to them. Compared to the fathers who
were seen as more competent and more committed to their jobs. Now, when I got these results, I sort of suspected that I would
get this difference in commitment. because there’s pretty strong stereotypes
out there that mothers aren’t as committed to their jobs. It turns out that there’s not
a lot of data to support that, but there is these stereotypes. But the competence thing’s kind of weird. Why would someone all of a sudden have
less brain power after they’ve had a child? So I went to talk one of my friends,
Deborah Roady, in the law school. And I was telling her about this. And she had just done some work
where she was interviewing law associates coming back
from maternity leave. And these law associates were complaining
that when they came back from maternity leave, they weren’t getting as
interesting of work anymore. They were getting paralegal level work,
and not the kind of work they
had been getting before. And she told me that one of the people
that she interviewed told her boss, I had a baby not a lobotomy that
kind of drive home that point. So what we’ve seen here is that
stereotypes can lead into this extra scrutiny, right? And we’ve seen it now for women,
we saw it for Afro-American man, we’ve seen it for mothers. We might ask whether or
not women might be able to overcome doubts about competence and
get beyond the effects of stereotypes. What stereotypes are doing is causing
us to see people as less competent then what they are. Could we get past this barrier
by asking women to self-promote? Toot your own horn. Make sure people are listening to you. Could that help get beyond this barrier? Well, Lori Redmond has done some
interesting work in this regard. She’s done a series of experiments where people are evaluating people
who are interviewing for a job. So if you were in this study you’d be
watching somebody who was interviewing for a job and
then you’d give feedback to that person. Half the people are interviewing women,
I mean half the people are rating women, half the people are rating men. And half the people are rating
people who are modest, so in the interview they talk
about what they’ve done, but maybe they give credit to their teammates,
or I got lucky or something like that. The other half are evaluating
people who are self-promoting. So you can imagine this person. I drove sales. I did this, a lot of the language of I. So the question is, does this work? We often tell this to women. You need to self-promote. If you don’t toot your own horn,
no-one else will. I don’t know if you’ve heard that saying. It’s interesting- that’s
a very Western saying. In certain Eastern countries there’s the
corollary statement that says the loudest duck gets shot. [LAUGH] Okay? That means something different
than toot your own horn. At least in the United States and
many Western countries, this is what we tell people. Does it work? Well it turns out for
both men and women, yes. People who self promoted both men and women were judged to be more competent
than their more modest counterparts. So it raised people’s sense
of perceived competence. So that’s a good thing. But for
women it also decrease their likability. So these self promoting women
were seen as more competent, but people didn’t like em, okay? What’s going on there? Well our stereotypes about women are that
they should be modest, not dominant or assertive. So this was a violation
of a stereotype and was creating what scholars
call this likeability penalty. Men occur no such penalty, okay? The more self-promoting man was just as
liked as his more modest counterpart. You might think, so what? If I’m interviewing for a job,
I want to be seen as competent. That’s more important than likeable right? That’s the tradeoff. I would rather be competent than likable,
right? As my colleague, Maggie Niel here in the
graduate school of business likes to say, if you want to be liked, get a dog. This is work. But it turns out, it matters, okay? For the man who is more self promoting, he was more likely to be recommended for
hire. People liked him and
they thought he was competent. That’s a win, win. But for
the woman who is more self promoting, she was no more likely to be hired. People didn’t want to hire her
because they didn’t like her and they didn’t want to hire her more modest
counterpart because they didn’t think she was very competent. Okay, so this is a bad trade off, right? This likability penalty is especially
important for woman as they move into leadership roles, because leadership roles
are really about sort of enacting more agentic self-promoting
behavior to some extent, okay? So if we’re trying to
advance women’s leadership, we’ve got to get past
this likability penalty. I want to show you one more example
of the way stereotypes work and then we’ll turn to solutions. And that is stereotypes also can
shift around the very criteria we use when making decisions about people. So I’ll just show you
this particular study. In this study, the context is people are being
considered to be hired as a police chief. So police chief is a leadership position,
head of the police department. It’s also kind of male typed job. And so what the authors of this study did,
is they created resumes for two candidates for police chief, okay? And they created them to
be Equivalently qualified, except one person had more education that
was relevant to being a police chief, and the other person had more experience. So these are kind of two
criteria you might care about. And one person’s strong on the one,
and one’s strong on the other. And that’s often when we’re making hiring
and promotion decisions, that’s how it is. Somebody seems better on this hand,
but the other’s better on that hand. So in the first phase of the experiment
they have no names on the file. We don’t know who’s male or female or anything else about them
except what they’ve done on the job. And what we find is that people
overwhelmingly prefer the person on the left. And when they’re asked to justify their
choice, they say, he has more education, or this person has more education. So all this is telling us is that in
this population, people are weighting the criteria of education more heavily
than they’re weighting experience. Okay, so that’s all we’ve learned. In the next wave of the experiment, what
they do is they put names on the files. They get a different set of raters
to rate the two applicants, okay. And now we have the man’s name on
the file that has more education. And the woman’s name on the file
that has more experience. So what we would expect
here is that people, based on what we learned in the first
condition of the experiment. We would expect that people would prefer
the man, because he has more education, and education seems to be the criteria
that people were weighting more heavily. And that’s what we find. Okay, so people prefer the man. And asked to justify their choice,
they said, he has more education. What gets interesting is
this third condition, okay. Now we grab a different set of raters,
okay. And we give them the same two resumes,
we just swap the names around. So now the woman’s name is on
the file with more education. And I’ve seen a couple of
people in the room laughing, they see where this is going, right. So what we, if education is
the criteria that carries the day. If it’s where we’re weighting
things more heavily, we would expect that the woman
would be chosen for the job. And all the people shaking
their heads are betting no. It wouldn’t make any sense if this was in
my slide show if that was what happened. And instead what happens,
is they still prefer the man and when they justify their choice,
it’s because he has more experience. So notice what’s happened, is the criteria has shifted from
education to experience to justify probably what was people’s gut hunch
this person was more right for the job. Okay, so we’ve seen a lot of depressing
stuff here on Reunion Week on back on a sunny day on the farm. We’ve seen how stereotypes shift our
criteria around, our standards around, the likeability pill all this. Let’s end on a positive note, by talking
how we can get beyond these effects, okay? And what I want to suggest is that our
solutions share one thing in common. And that is they have to break the
tendency to use stereotypes as a shortcut. That’s what got us into
trouble to begin with. Good, well intentioned people who
are very busy tried to process all the information on their job and
in an unimplicit or unconscious way, stereotypes
are effecting those judgements. So, how can we get beyond that? We’ve been doing a lot of
work at the Clayman Institute on a project that we colloquially
like to call See Bias, Block Bias. I’m working with companies
in the Silicon Valley and beyond, to first help people
see bias in their workplace. Because these biases are unconscious or
implicit they’re often hard to see. So what can we do to
help people see bias and then what kind of tools can we devise
to block the use of that bias? Well on the seeing bias front one thing
that really helps is teaching people about how stereotypes work. Once people understand
how stereotypes work. They tend to be more careful and
thoughtful in their own decision making. So this is a good first step. However, it’s not going to take us all
that far, and I think we all know why. That is, any kind of education or
training that you’ve ever had, even if it was really impactful,
right, it impacts you a lot. Today, it may be next week,
and the week after. It’s like a New Year’s resolution, right? We’re good in January. We’re still okay in February. March comes, it’s gone. These things wear off, and
I think about this on reunion weekend. Every time I’m on campus, I think about, what if I could remember
all the stuff I had learned at Stanford? I hadn’t forgotten any of it. How smart I would See,
these things were away. So we’re going to have to do something
more than just educate people. We’re going to have to
change the way we work. So what I want to end with and
I’m going to turn it over to Laurie. I want to talk just a little bit about
what organizations can do to get beyond bias. And then Laurie is going to talk about
what we as individuals can do, okay. And that’s how we’ll end up today. So in terms of what organizations can do, there’s really two broad buckets
of things that we like to work on. The first is that we can change
the stereotypes about leadership, or more generally, change the stereotypes in our
organization about what success is like. So in the case of leadership, even though
we know that leaders embody a diverse array of traits, people’s stereotypes
about leaders are very narrow. They’re the Steve Jobs of the world. These born geniuses that drive change, and even if they have to step on
people it doesn’t matter. We have those stereotypes
about leadership, and that causes women to not see
themselves as being as leader-like. And it causes people judging women’s
performances to not see them as leaderlike. The Association of Women in Science
is an interesting example here. This is a group of women’s groups
that are across the 22 professional science societies in our country. So like The American Chemical Society,
for example. And what they noticed is that
women were winning very few career achievement awards. The awards that signal that you’re
just at the pinnacle of your career. Very few women were getting them even
though the pipeline of women was getting fuller and fuller. So what they did in some of
the societies was an experiment where they changed the words they used and
the call for nominations. And rather than describing the person
as just being a genius and path-breaking, they said, please nominate people who have had
considerable achievements in their career. And that makes sense because these
were career achievement awards, right? But that language, changing that language,
caused many more women to apply for the awards and for women to start
winning the awards at a higher rate. So broadening stereotypes about
leadership and success can be useful. Secondly, we need to change our evaluation
processes when we’re hiring and promoting people to block
the effects of stereotypes. And I want to give you just
a few quick examples here. One is that we need to develop clear
criteria before people make evaluations. That police chief study I told you about,
there was one final condition. And in this condition what they said
to the new set of writers is this, before we show you any applicants
write down what really matters to you. And guess what,
people wrote down education. And then when they saw women who had more
education, they chose them for the job. There’s about two decades worth of
research that shows the clearer the criteria, the more likely we
are to hire and promote women and people of color. When you have clear criteria you
don’t need the shortcuts that stereotypes provide. Secondly, we need to ensure that the
criteria is evenly applied to all people. So think back to the psychology study. I would need to see evidence
of her teaching evaluations. If you’re in a meeting and someone says
something like that, what somebody in the room needs to be doing, and
we call this person a criteria monitor. This person needs to be saying if we’re
going to consider teaching evaluations, why don’t we go back and
apply that to everyone. Okay?
That can be very helpful. Third, we need to increase
accountability and transparency, okay? With accountability people are asked
to justify their choices and when people have to justify
who they’re hiring or who they’re promoting they tend to
make more thoughtful decisions. If I’m going to have to explain to you why
I preferred someone I can’t just say, hm, it was a hunch. I have to sort of think through
what the criteria are and how the person mapped onto those. Transparency, posting numbers, keeping track of how you’re doing in terms
of hiring women and other diverse groups. And we do this at Stanford. Every year in the Spring quarter, one of
the Vice Provost comes to the faculty Senate and
gives a report we call gains and losses. And basically what we are doing
here is we’re looking at how have we done in
gaining women faculty and gaining faculty of color relative
to losing those groups of people. The goal is that we want our faculty
to look more like our student body and by being transparent and collecting data
on that We keep ourselves focused on that goal and managing towards that goal. And then, finally, question,
don’t assume, meritocracy. We work in a place, especially here in
the Silicon Valley where people tend to think their organization is meritocratic. They’re quantitative,
data-oriented people, and they think they are meritocratic. But recent research has shown
that organizations who think they are meritocratic,
are actually more prone to biases than organizations that know that
they still have work to do, right? So if meritocracy is your goal, but
if you treat it like a reality, it undermines the goal. And it makes sense when
you think about it, right? If you think you already are meritocratic,
there’s no biases in your organization, you don’t have a problem. You’re probably not going to be that
conscious of trying to solve the problem. So questioning meritocracy and
constantly asking, and wanting evidence about how we’re doing,
in terms of being fair in hiring and promotion is actually
really quite important. Now, I know that not everyone here is
running an organization where these points are that relevant. So what I want to do is
turn it over to Laurie, who is now going to talk a little bit
with you about what individuals can do, tomorrow, to start driving us towards
a world that is more meritocratic.>>I think you’ve seen from
the research that we’re in a society with these shared cultural
beliefs, it’s something we all share. So sometimes people say that’s the point
in the presentation where your kind of enthusiasm goes down, and
it’s my job to bring you back up so that we can do something together. I’m going to actually ask
you to see the unseen. And when I think about that,
I think about these puzzles. How many of you can see the face
of an old lady in this puzzle? Okay, and how many of you can see
the face of a young lady in this puzzle? Oh, great. It’s funny, when I do this
with a lot of tech companies, the young face gets a lot of hands. And the old face doesn’t get as many. So I think we have some age bias
going on in Silicon Valley. So the interesting thing is, it can actually take you some time
to be able to see both these faces. At one reunion weekend this
one boy had never seen it, and he got it in about a minute. And sometimes I find the older I get,
the harder it is for me to see both sides of it in equation. The good news is though,
that what we’ve learned, is once your brain identifies both,
it cannot unsee them again. So I hadn’t seen this puzzle for
about five years. And when they showed it to me again,
I’m like, oh yeah, there’s an old face and
a young face. So our goal, with all of our
bias training, is to ensure that we present you a way to see bias
in a way you can’t unsee it again. And then to have the tools
to be able to block bias. We’re going to start with
an experiment in language, so yes, you get to do,
this class is without quizzes. I’m not going to quiz you, but we’re
going to do some experiments together. We’re going to do
an experiment in language, because language is the most
common way that we maintain and replicate cultures in our families,
in our communities, and in our workplaces. I’m going to have you do an experiment, so you should’ve gotten a piece
of paper when you came in. You don’t have to use it. I find also a lot of people
like to use their devices. So, there’s a piece of paper,
we have some pens as well. And all I want you to do is
describe a top performer. So if you think of that in a workplace
context, it might be a team you’re on and there’s one person you
can always count on. It could be in your community. Where I live there’s this one family,
they always hosts all the block parties. So, I would count on that family
to host the block parties. It could be in your family. So my job in my family is
to plan all our vacations. And in that context, I would be called the top performer
of my family’s vacation planning. So whatever context you have,
think of a top performer, and on that sheet of paper, just take
a minute to describe in a few words, the behaviors and
attributes of that top performer. Doesn’t have to be a complete sentence or
a resume, just a few words to describe a top performer, whether it’s at home,
at work, or in your family. And thank you for passing out the pens. Oh, a pen here. You thought this was
classes without quizzes. So think of that person in particular and
not a general top performer. In a few words,
to describe the behaviors and attributes of that top performer, okay? Does everyone have at least one
word down for their top performer? Great, now here’s the thought experiment. And I’m going to show you
two descriptions, and they’re written differently intentionally. So this is never going to be
how it would show up in life. But just come along with me on this
journey of this thought experiment. Imagine that I’ve taken
that top performer away. And I’m going to show you
the description of two different people. And I’m going to have you pick the person
to replace your top performer. So for example, in my family, if I no
longer were planning our vacations, I’d say to my family, pick the person
to plan the top vacation, right? So in the workplace,
it could be on your team. Imagine that person got recruited or promoted out of your team, and
you’re looking for a replacement. And I’m going to ask you
to pick Description A or Description B to replace
your top performer. And yes, they’re written very differently. This is just an experiment. Now, how many would replace their
top performer with Description A? I would say it’s 15%, 20%. How about with Description B? Okay, maybe 75%. All right, interesting, did you notice
I’ve been priming you all the time by saying top performer,
top performer, top performer? Notice how language has created
association of a type of person. And even when you’re asked to pick
a substitution for that person, with just four words, we’re able to do it,
80% of us pick Description A. If I had said, instead, imagine the person you count on the most
to support you in your times of need. Even if that’s the same person, you might
have picked a different description. Notice how language is priming us to
make associations, as Shelly said. And make decisions off just a few words. Now why does this matter? Researchers at Rice University went
through 400 letters of recommendation for the position of medical chief. Imagine a medical chief is the person
who’s making life or death situations for a lot of people. And the researchers noticed that the more
communal language that was used, which is Description A, the less likely
a candidate was to be put forward. So when I think of communal language, I think of it as the language of we,
of community, and of collaboration. The more agentic language that was used,
so when I think of agentic language,
I think of agency or the language of I. I am independently driving to an outcome. The more a communal
language that was used, the less likely that candidate
was to be put forward. Now thinking about us doing
a presentation on one’s leadership, guess what kind of person is more likely
to be described with communal language? Women, with the exact same qualifications. So the letter writers are the people who
most want this person to be considered as the top candidate. And simply by using language that
was more communal in nature, their advocacy was less effective. Why does this matter? So as Shelly said, we’re using
stereotypes as these cognitive shortcuts. Now are their any native
Russian speakers in the room? So apparently in Russian there’s
two words for the color blue. So if I showed you
something that was blue and you’re a native Russian speaker your brain
would take a slight longer bit to sort it. because you’re sorting is that blue or
is that light blue or dark blue? But in English, there’s only one color. So if I show you something that’s blue,
you’ll sort it more quickly. So the more binary something is, the
faster our brain can make these decisions. The more shades of gray there are,
the slower those cognitive processes are. Now part of what starts to
happen is you assume in this binary world that
the other doesn’t exist. So if I assume that you’re very communal,
you’re a very good team player, I might wonder are you also
willing to drive a decision home? And if you’re more agentic,
you’re more driven, I might wonder are you also
able to be a great team player? Now here’s the thing about leadership. When we’re asked quickly to decide
about someone’s leadership, we’re more likely to associate
leader with agentic qualities. Even though we want a spectrum
of qualities with leadership, when we’re making those cognitive
shortcuts we’re much more likely to rely on agentic terms in
making those decisions. So you can see that the very use of
language as an automatic function, seeing somebody who’s equally qualified but
foregrounding different qualifications, has them show up differently when being
evaluated for a leadership position. Here’s the kind of list there is, that list is also on the back
of your handout for you to use. Oftentimes my friends will use this so, I
just wrote a letter or recommendation for somebody to get into college. And submitted it to the common app. And i was very conscious of the kind of
language that I was using in my letter of recommendation. Often people will go look
at their LinkedIn profiles to see how they’ve described
their own accomplishments. Or they might even look at
their LinkedIn endorsements. How have you,
in a quick endorsement of someone, used language that might not have
them seem as much of a leader? I have a friend who’s
a project manager and she’s really effective. And she said, everyone just says I’m
friendly and no one says I’m strategic. And I said, oh, she’s also asian. Asians are perceived to
be very good at tasks. So when someone sees her,
they see the task orientation she has. And they forget that she was very
strategic in how she planned the events. So after she did the presentation,
the next time she asked for a LinkedIn endorsement, she primed that person to
talk about certain qualifications she had. So she would finally have a LinkedIn
endorsement that didn’t say she’s really good a managing tasks. I just want to give you an example. So at our institute, we’re often
given informal recommendations. So when we’re hiring someone for a job, someone will send a note to
someone to send to us, so that they know that their person
should be highly considered for a job. So I want to show you
a little bit of that. I’m going to diagnose
the language that was used. This is also a warning, never send me a letter of recommendation
if you don’t want it to show up on screen.>>[LAUGH]
>>No, I’m just kidding. So this is for
someone who worked on capitol hill. It was for us one of our most
senior positions, it’s for the position of marketing director. And this person went to one person to
another person to really get me this, because as you see this was high,
high praise for this candidate. I’m going to dissect
the language a little bit. Notice the words in black. These are her strongest
endorsements of the candidate. Notice it’s very vague. Scholar of what? Professional who led what accomplishment? So even this was high praise,
I actually don’t know much more about this candidate then I would from
a letter that didn’t say much about her. Another thing we know about women is
they’re more often described through their personalities than
with their accomplishments. And when their accomplishments are
described, they’re often much more vague. They don’t have business
outcomes attached to it, so this is another trend
we know from our research. Notice that word actually. She and I actually worked together. Our research also shows that there
are many more doubt-raising statements in women’s performance evaluations. She managed to lead a good team. Not, she led a good team. In the end she managed to
deliver the project on time. Why do we need to say in the end? In the end implies there wasn’t
always going to be on track, right? So this kind of doubt raising statement
we also find is much more common in our evaluations of women. And lastly look at
the traits of this person. So this person I later learned
was a highly rated scholar, who had used her scholarship to advance
an agenda that went to Congress. None of that was mentioned here. All I got was that she was passionate,
committed, and determined. Now, I don’t know about you,
but as a woman, I’m often called tirelessly dedicated. I don’t know if that’s code for something,
but when we look through the performance evaluations of women, they’re also more
commonly coded as tirelessly dedicated. And one of the things I always think is so
funny is we’re in this culture of genius, right? We want the next Steve Jobs. We want the next startup. In this culture of genius, it kind of
is supposed to just come to you and the rest of us are working tirelessly and
dedicated.>>[LAUGH]
>>So, this research we did, as I talked about,
was performance evaluations. Which, we redacted and
took the gender out. And then we evaluated them for
the way language was used. The reason we do this at the Clayman
Institute is that we want to provide practical solutions for companies to
then block bias in their processes. So if I broadly say to you,
don’t make big praise, that’s one thing. But if I said, here’s exactly the way
vague praise works in your company, you’re more able to train people
not to use praise in that way. So this was posted recently
in the Wall Street Journal, it’s part of a two year research project
we’ve been working on with some sites across the country to understand
exactly how does bias play out. You can see some of the things we talked
about, women are given much less feedback. And when they are given feedback,
it’s not very specific. So I thought this was fake,
but it’s an actual citation. One woman was told to
show it more at work. That was her feedback she got. I don’t really know for why,
what would the outcome be, and what would that provide for
me to produce more results. The man, on the other hand, was told,
combine technology A with technology B and together that will help you
launch this new platform. You can hear that that vagueness
doesn’t really help me much on my job. So women are getting less
developmental feedback. They’re getting a lot more criticism
of their communication style. Do you remember when Shelly talked
about the likeability penalty? The way the likeability penalty will show
up at work is you’ll either be called not clear and concise at entry-level,
or off-putting at the senior level. So we notice the way communication
shows up as a likeability penalty in performance reviews. We’re really excited that we’re launching
this new research in a three part launch. And more excited that we’ll be launching
this research as part of a national summit in March 2017. Thanks to the generous support
of GSB alum, Bruce Golden and his wife Michelle Mercer who
was an undergrad in law degree, we’ll be launching this as a national
conversation to try to see and block bias in all of our workplaces. So this is the end of our presentation
because we promised to allow some time for questions. So Shih do you want to come back on stage? One action you could do tomorrow, Shelly said I would give you
solutions that you could do tomorrow. One thing you can do, endorse a woman. Do you remember when Shelly said
that if you toot your own horn, people might not like you? An experiment was done where
a professor said in one experiment, here’s my T.A.
and just mentioned her name. In another Condition,
he tooted her horn for her. And said how amazing she was, what publications she had,
why they should listen to her. In the condition where
the professor tooted the horn for her, her ratings went up. So even if women might have to
navigate the likeability penalty around tooting their own horn You
can toot their the horn for her. So always introducing a woman, making sure
you vouch for her competence is one way that you can work towards her being
recognized as an expert, as leader. Another thing you can do is just
block the automatic use of language. Don’t write a letter of recommendation
without thinking what am I trying to say about somebody. You could also, I noticed this with my
kids too, what I’m criticizing about them by gender and trying to make
sure I do that equally for them. And lastly you can update your resume or
LinkedIn in profile, or have someone you know update
their resume or LinkedIn profile. To be reflective of their true
accomplishments in ways that will help them attain everything they
want in leadership so. With that,
we’ll see if you have any questions.>>There’s a couple of
microphones in the room.>>Yes, that’s right.
>>So if you have a question if you
could go to the microphone. Otherwise we have to repeat it and
we may botch it. [LAUGHTER] Yes?>>Thanks so much. This is really helpful for me. I work at the World Bank in Washington and we’re actually going
through an edge survey. Right now is part of the gender
strategy for the organization. I hope that they make the comments public,
for at least the staff, because they did when it was both men and
women commenting and this is something that is
going to mesh to the women.>>That’s great.>>But a lot of this resonates very much. My question is,
I am the mother of three teenage girls. And my middle daughter is, I think, has a lot of very intrinsic
leadership qualities. But those things can sometimes make it
difficult, she’s in the tenth grade. And I’m looking for different kinds of
programs or ways to support her, and all three of them, but especially her. That she’s got that, we were in the power,
I was in the power one earlier. The little girl that was,
if any of you were in that one, but they were talking about girls versus boy. She’s got some of those characteristics
that are sometimes off-putting I think to both girls and boys. And I want to help to give her the tools
she needs as well as my other girls. I just wondered if you had anything for
that kind of next generation.>>It’s a very common
finding with young girls that are exhibiting leadership behavior to be
called bossy which is a derogatory term. And I think serves to
dampen their ambition. It’s something I think we just
absolutely don’t want to do. So the question is what can we do
then to provide a good space for them to develop those skills and
recognize those skills. I think, one, as a,
to Lori’s point about endorsing the competence of other people to
very clearly try to correct some of those things in amongst the people
who might be critical of her. So I think it’s Important when a girl’s
exhibiting leadership skills and there’s negative attention drawn to that,
for somebody to be able to say about her. I think she actually could be running
her class, or something like that. Cheryl Sandburg loves to say,
say she has executive presence, instead of she’s bossy. I mean to reframe what it means,
to be a leader for a young girl, I think is actually really important. There’s starting to emerge
new kinds of workshops and things that you can send her to
where she’ll be around other people- peers that are more like
her- which helps validate that. So we’ve been, we have a program we call
Seeds of Change that is a middle school, high school girls kind
of a leadership program. Not only does it teach skills, but it puts
them in contact with other girls who value those same skills and that’s very
important is to have that peer group. That’s a great question.>>Yeah, we also have some free videos
online under Voice and Influence. So there are professors like Maggie Neale
from the business school and Deb Gruenfeld here as well. I have a girl who’s in seventh grade,
and I’ve watched them with her and talked about them. And one of the things we know about young
girls is you can’t always figure out what their peers will say. It can give them ideas about how you
can frame opportunities for them, but another thing to think about
is why they’re doing things. Being in touch with a leadership purpose,
or vision purpose, or something like that can
help you figure out. Oh, maybe it’s worth having
someone call me by bossy because I’m going to go change the world. So sometimes our work, I’ve seen
some change part of what’s in there, is helping young girls find the why. And then going back to that why when they
do face some of that pushback externally.>>Okay. So we’ll go here and then over here next. Go ahead.>>Okay.
As to the feedback loops and the degree to which women receive
positive feedback relative to men. Has any work been done on
looking at the sexuality aspect? Positive input is the language
of intimacy at some level. And some men feel far more
uncomfortable with that or knowing how to rephrase or
refrain what they want to say. So that it doesn’t take on context
>>Yeah.>>Or that doesn’t bother their
own subconscious feelings.>>Right.>>Has there been any work on this? Yeah, there is, so there is some work that
shows that that is one of the barriers that some men will describe in
say mentoring women for example. I mean, how is it going to look? I mean hanging out with us all in a bar,
how are people going to read that. And worrying about those kind of things. I think the solution to that is similar to a lot of the other solutions
that we’ve offered. And that is, we need more clear
criteria about how you do mentorship. How you give feedback. So for example on the work
we’re doing with language. We’ve been evaluating lots of
performance evaluations, and the language use overly creative. I mean, people are writing things that
are just crazy in some of these reviews, it’s just not good. So what we’ve been doing is working a
little bit on teaching people what kind of things you say,
because if you’re a manager and you’re told these are the kind
of things you talk about. And your subordinate knows
these are the kind of things your manager’s going to say. It’s not going to be misread. It’s going to be what the company
is suggesting that people do. So we have to provide tools
to help people do that.>>Also some training in mentorship.>>Exactly.>>And what’s appropriate behavior
on the part of the mentor. And what the mentors own subconscious
feelings are during that interface.>>Yes, very good. Yes, thank you sir.>>because we’re doing a video
actually in our new voice and influence series on having effective
mentoring relationships and we talk about
>>The road blocks, which include protective hesitation on the
part of the mentor to give hard feedback, and protective defensiveness on the part
of the mentee, to hear the hard feedback. So we’ll be tackling that next year.>>I hope it’s in another building.>>Exactly.>>Yes. Question over here.>>Yes, hi. I’m Suzanne Butler, I’m Class of 1964. 50 years ago,
when I was an undergraduate at Stanford, there were almost no women on the faculty. George Spindler was chairman of
the anthropology department. And my one experience with a woman faculty
member was his wife, Lois Spindler. And she was a teaching assistant or
something along those lines. The gender ratio at the undergraduate
level I think was five men to three women? It might have been five to two. I thought that was great,
but that was then. My question now is how much progress
has Stanford made on hiring women, full faculty, and giving them tenure.>>So, I chair the provost
committee on faculty equity. So I usually have these data handy. So Actually at the student level
body we’re doing great, okay? Like most universities really
pretty close to 50/50. At the faculty level at
this point in time amongst our assistant professors we’re 27% female,
okay? We’re a little over a quarter. When it comes to full professors
we’re more between 21 and 22%. So about one in five. So we’re not where we want to be. That’s on par with our peers, so
it’s not like Stanford’s having a unique problem here, but
we’re not where we want to be with that. And I think there’s
a real concerted effort, especially in trying to hire
women in the STEM fields and in the business school,
where women are especially in low numbers. And importantly trying to hire
faculty of color as well. But we’re not where we want to be
at this point, yet, with that. Partly this is.>>[INAUDIBLE]
>>Yeah. So on tenure, when we talk about tenuring
people from assistant to associate professor, there is not a gender
gap in who gets tenured. And this, I think, the university has given a lot of thought to how it is that
we are evaluating people for ten years. So it’s not that gender never matters, but overall the pattern looks
really pretty good there. So our question, I think, is really about, our challenge is hiring people and
getting them here. And then I think we’re doing
okay on the other dimension. I see we’re almost out of time. Maybe we could do one more question and then I’m happy to answer a few
questions individually afterwards. So, I think she was here first. I’m sorry.>>Your comment on seeing the bias. Is the mother of a tuba player,
female tuba player, five years ago when the woman was hired for
the Philadelphia Symphony. And there was all the news articles on how
a woman had finally landed the position. None of them mentioned that women
had been winning the position for years on the blind auditions, and
that when they saw a woman was chosen on the blind auditions,
they redid them visible. Not one news article. So I wrote in about
the statistics because I had them.>>Yeah.
>>From the tuba player with a Masters degree. Is there a place we
should keep our eye to? To check in with some of the statistics. Because my awareness is
business is all the time. I’m with people who do not see
acknowledge that there is a bias, and I have to have constant statistics,
language, to keep asking, having paraphrase,
asking for more information. Can you give us something
to keep our eye to?>>Yeah so the statistics are going to be
spread out depending on what the category is but I just want to underline what
you’re doing as being very important. That is, now it is pretty easy to
Google and find statistics on things. When someone says to you
there are no women here. There are no women in the pipeline. There are no women that are eligible for
this. That we should not take that as an answer. That’s almost always not the case, right? So if I see major awards have
just been given to people and there’s only one woman there out of all
ten people that have been nominated, I write and say where are the women. And often I hear back Well,
no one nominated them, or [INAUDIBLE], there’s all these excuses. But there are women out there, and I think
we have to help point that out to people. So I would just underscore that in those
situations if you hear there are no women, dig a little bit and find some for them,
because there are women there, and we need to help promote women, all of us, if we’re going to
really advance women’s leadership. And I’ll just end by saying again
this is not just about women. This is about, this is about really
driving the best innovation, scientific discovery, and
solving the biggest problems in our world. We need to have all people involved. If the cure for cancer is in the head of
some young African American woman and we’re not listening to her,
we’re all losing out on that. So this is something that really
affects us at a societal level. Thank you all very much. [APPLAUSE]
[MUSIC]

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