And in today's talk, we're gonna talk about bias and unconscious bias and how it affects folks like us and tech workspaces and what we can do about it.

Great.

Um, so just a little bit more about me, my pronouns or she heard hers.

And I'm a PhD candidate at U C.

Berkeley.

I'm studying chocolate and how humans can save it.

So I know very important work.

But while my work doesn't have me playing around in Java script all that much, I do do a lot of data science and art and python.

But today, my day job doesn't matter.

Instead, we're going to talk about something that affects everyone in this room because we're all humans and that's unconscious bias.

So who here has gone to some sort of diversity training that they felt was a big waste of time?

Yeah, I definitely have, um, And as it turns out, studies have shown that a bad training can actually have a negative effect on people so they can come out of a bad training with more hostile attitudes towards people who are different from them.

And so, at the unconscious bias project, where most of us are either in grad school or have PhD some stunt fields.

We've always been really careful toe only promote evidence based approaches.

We also want the information we provide to empower you instead of leaving you even more deflated about the current state of the world.

That's why our motto is 100% boots.

Yeah, ah, 100% empowerment, 0% guilt trip.

And today I'm gonna teach you all tools to reduce the effect of unconscious bias.

And I want you to leave this conference as unconscious bias warriors are ambassadors that air dedicated to making a positive impact in your circle so that tech becomes more and more diverse, inclusive and equitable.

So I'll be going over a lot of tools.

And resource is today in my talk.

But don't worry.

If you miss something, you'll be able to access all of the pure reviewed literature, and all of the other resource is I mentioned on our website.

So finally, before we jump into the good stuff, I want to mention that I'll be touching on issues that are deeply personal, and some of the examples that I may present could be triggering to some of you in the audience, but I present them in the hopes of having a frank conversation about why they're harmful and what we can take.

What steps We can take us, individuals and bystanders to make the world a better place.

So, unfortunately, I won't really have any time for questions from the audience up here on stage.

But I encourage you to come find me if you have questions, concerns or comments about the presentation.

And so with that, let's start with a definition.

So we need to be on the same page about what bias ISS and biases prejudice in favor of or against one group, person or thing compared with another and usually away consider to be unfair, so unconscious or implicit bias is bias that you have, even though you don't consciously agree with it or even know that it's there.

And most people don't want to be racist or sexist.

But a lot of us are unconsciously biased against certain groups anyway, and this starts with negative stereotypes from the world around us.

What we see in TV shows and movies here on the radio reading books, see on the Internet and even pick up from our friends and family.

And so even if we don't unconsciously agree with these negative stereotypes, they can still worm their way into our unconscious and influence how we think and act.

So I'd like to call attention to a few examples of negative stereotypes from American culture to show you what I'm talking about.

Men are seen as breadwinners and women as caregivers.

Women can be beautiful or intelligent, but not both.

African Americans are commonly portrayed as loud, and bias can even come from simple associations of patterns that we notice unconsciously like that custodians are often racial minorities and before stereotypes even lead to bias stereotypes themselves or damaging.

Being stereotyped has been found to lead to short term aggression, inability to focus, which results in decrease performance and overeating.

People who regularly encounter the threat of being judged by negative stereotype are more likely to have hypertension be depressed and to rate their own health more poorly.

And being on the receiving end of positive bias or positive stereotypes hurts to implying someone is good at math because they're Asian might make the receiver of the comment dislike the speaker and invoke feelings of anger.

But when stereotypes lead toa unconscious bias about who can thrive in science and tech, this can be even.

This can have even more damaging effects by creating barriers toe entering stem fields.

And this is the so called pipeline problem, and folks start being affected by this bias at a very early age, and it happens around the world.

So this paper is actually from Germany, and I'll be presenting a few more papers.

And then in this section here, the researchers showed that teachers have both conscious and unconscious stereotypes about boys being better at math and girls being better at languages.

And those stereotypes influence whether the teachers recommend boys and girls for science and technology schools versus language oriented schools.

And this bias continues from grade school through graduate school.

But the pipeline is only the beginning of the problem.

Once marginalized, people get their foot in the door.

Unconscious bias leads to barriers to rising in step.

So study after study has found evidence of bias against almost any marginalized group you can think of in terms of who gets called back for an interview.

And as we all know, jobs are pretty important on this type of bias occurs even when that discrimination is illegal in that area.

So in the United States, there's bias against openly gay men and bias against people with disabilities, even with the disability, would not have affected the person's ability to perform the job.

In the United States and China, being a parent hurt job prospects for women, but it was actually the opposite for men.

Being a father helped job prospects and one last example, bias was found against people with Arabic sounding names, a bungalow that among both American and Dutch reviewers.

So imagine experiencing these biases every time you apply to a job or when you want to move up within your own company or switch to a different team and imagine how much harder that might be or how much worse that bias might be if you're in Arabic.

Lesbian mother in a wheelchair And studies have actually look specifically at this type of intersection, for instance, between gender and race, so women and racial minorities are both less likely to be given the benefit of the doubt, and the problem is only worse.

If you're both a woman and a racial minority.

So when women of color demonstrate leadership and competence, they're assertiveness is perceived negatively, and the data shows that they get pushed back for it.

So even when you're successful, unsupportive work environments air common reason for leading stem in the next few slides will be focusing on women.

But these trends are representative of most underrepresented groups and tech.

So let me be frank.

Women do leave stem at greater rates than they leave the non stem workforce.

The orange line that you see on this screen is women being retained in non stump fields.

Now let's look at step.

As you can see, the retention is much, much worse.

And less than 20% of the women who leave stump fields are also leaving the workforce, for instance, like taking care of family.

More than 80% of the women leaving the stem workforce are just getting jobs in other fields.

They're going to non stump fields, so let's look at a different control and focus in on just the tech industry.

When you compare the attrition rates of, um, of women to men in tech, it's more than twice as high 41% of women leave tech versus just 17% of men.

And on top of the well documented pay gap that exists there, many cultural accused that a company can give to signal that an employee is not valued, which in turn encourages that employee to leave One is feedback in performance reviews.

In this study, the majority of women received reviews with negative, unhelpful feedback, while the majority of men received only constructive feedback.

And the negative feedback for women was about personality in ways that reflect common unconscious biases, like telling women toe pipe down or be less abrasive.

So together, these barriers keep some groups under representative Stamen Tech and reinforce preexisting stereotypes, creating what we've dubbed the positive feedback loop of negative stereotypes.

And there's so so much more pure reviewed literature out there that shows that unconscious bias Israel and it is impacting diversity.

If you'd like to explore more, please head over to our Web site, where you can find all of the papers that I mentioned in the stock, as well as hundreds others about almost every aspect of bias, its effect and what we can do about it.

Okay, so let's take a breath because That was a lot of bad news, and I know some of you might be feeling a little low at this point in the talk.

But the good news is that we're only about halfway through, and that means we have a lot of time to talk about solutions.

So even those stereotypes come from our environment.

That doesn't make us powerless.

Happily, there's enough studies out there that we know how to reduce negative effects of bias and reliably reduce our biases, too.

So thoughts are actually our first line of defense when confronting bias.

So I'm gonna teach you to techniques that can help you decrease your own unconscious bias.

But before we start training, we need to cover some pre requisites.

In order for these techniques to be effective for you, you need to be motivated to overcome your unconscious bias.

Hopefully, the positive loop of negative stereo about stereotypes helps to give you that motivation.

You then need to take steps to become aware of your bias and wide exists, and we'll explore how to recognize your own bias in the first technique that I teach you.

But you can also do it through more technical ways.

By taking an implicit association test at Harvard's Project Implicit website, you'll need to learn the to detect the subtle influence of bias in your everyday surroundings, which helps, you know, win toe act.

And then you have to practice these strategies to reduce your bias that you know what to do in that moment when you recognize it.

And yes, you do have to practice without practice, there will be no change.

Okay, so let's learn our first strategy.

I want you to take a look at this picture and think to yourself what is your first reaction to it?

If I asked you to describe who these people are and what they were doing, what would you think?

What would you say?

Did you assume that each of these people are engineers or designers, beginners or experienced straight or queer, disabled or not communicating well or poorly?

When I first saw this picture, I thought young, inexperienced interns, and that's my bias.

So once you've acknowledged that your own biases are informing the way you see people, you can choose to replace any bias aspect of your thoughts or your reaction with a different, less stereotypical scenario.

and this is what we call breaking down the stereotype.

The idea here is to consciously recognize that I thought that you had came from a stereotype, and instead of leaving that bias buried in your subconscious, bring it to the surface and then replace it.

So in this case, I can choose to recognize my biased reaction and think CEOs, entrepreneurs, leaders experienced Okay, so let's move on to our second strategy, which is increasing opportunities for contact.

And it is probably one of the most important strategies that you'll find because it tends to help with all aspects of breaking down our biases.

It can make us confront her basic assumptions.

It helps us empathize with individuals who are different from us, and it can give us non stereotypic examples that we can continuously use to fight our own bias.

And there's many ways to do this.

Even if you aren't a social butterfly, so you can try going to a diverse conference like this one.

You could follow folks like the other amazing speakers that you've heard on Twitter.

You can contribute to an open source project with diverse maintainers, or you could mentor someone new or find a mentor for yourself.

Whatever feels like a good step for you, that's enough, and I'm not gonna lie.

Increasing opportunities for contact can be scary sometimes, too.

So if you struggle with this like I tend to d'oh, it's always a good move.

Thio, listen and be genuinely curious.

Twitter and blog's can be an awesome start because you can follow along and get a sense of what someone might or might not want to talk about.

It also helps to be open to hearing things you didn't expect, reading body language cues and believing what people say about their experiences, even if it seems contradictory.

Toe what to something that you thought you knew.

And if someone gives you a hard feedback or it just doesn't have time to talk, try and stay humble.

Other people are the main character in the their own story.

So as a group, let's send an intention to use the rest of this conference to meet new people and help increase our opportunities for contact with groups that are underrepresented in our workplaces.

And let's try and maintain those connections after this conference, even if it is just following a new person on Twitter.

So to wrap up this section, unconsciously biased thoughts are have it.

And like any habit, they can be broken.

Mostly you can never be quite curative, unconscious bias.

But over time, the strategies to reduce bias become habits themselves, and it will feel easier to quash unconscious bias when it comes up again.

So let's shift away from our internal struggles and dive into how we can respond to bias in our environments.

We've been working with an amazing cartoonists, Korea Hope Theresa Oh, born to illustrate real scenarios that come up and how we can react when they dio.

So we have cartoon showing bias against white women, people of color, bias against people with disabilities, against clear folks and so on.

But for this talk, I picked just a couple of cartoons that I hope are less emotionally charged than others, but still useful for practicing these techniques.

So who has heard this one before?

She's really smart, but I wish she wasn't so bossy.

So I have and I may have thought it one or two times to remember that we are all biased and we can even be biased against our own group, so let's identify this bias.

This cartoon showcases a common bias against women in leadership roles.

So what are your options when someone says this to you?

Instead of labeling the person who made the comment as racist or sexist?

Inciting reflection on the comment through four simple strategies will help to highlight the problematic nature of it and reflect and encourage a change in behavior rather than an argument.

Surfer strategy is just to observe the problem.

Instead of saints staying silent or moving on observed that the common was stereotypical and hurtful.

Something like Ouch, that's a bit harsh.

Or you could counter a micro aggression with a micro affection.

She's not bossy.

She's a leader.

Ah, positive comment like this can help weaken the negative stereotype for those around you and without being too confrontational or derailing the conversation are.

Bystander could also reflect the comment back, which would make the speaker do the work of challenging their own assumptions.