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← How racial bias works -- and how to disrupt it

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Showing Revision 6 created 06/22/2020 by Erin Gregory.

  1. Some years ago,
  2. I was on an airplane with my son
    who was just five years old at the time.
  3. My son was so excited
    about being on this airplane with Mommy.
  4. He's looking all around
    and he's checking things out
  5. and he's checking people out.
  6. And he sees this man, and he says,
  7. "Hey! That guy looks like Daddy!"
  8. And I look at the man,
  9. and he didn't look anything
    at all like my husband,
  10. nothing at all.
  11. And so then I start
    looking around on the plane,
  12. and I notice this man was
    the only black guy on the plane.
  13. And I thought,
  14. "Alright.
  15. I'm going to have to have
    a little talk with my son
  16. about how not all
    black people look alike."
  17. My son, he lifts his head up,
    and he says to me,
  18. "I hope he doesn't rob the plane."
  19. And I said, "What? What did you say?"
  20. And he says, "Well, I hope that man
    doesn't rob the plane."
  21. And I said, "Well, why would you say that?
  22. You know Daddy wouldn't rob a plane."
  23. And he says, "Yeah, yeah,
    yeah, well, I know."
  24. And I said, "Well,
    why would you say that?"
  25. And he looked at me
    with this really sad face,
  26. and he says,
  27. "I don't know why I said that.
  28. I don't know why I was thinking that."
  29. We are living with such severe
    racial stratification

  30. that even a five-year-old can tell us
    what's supposed to happen next,
  31. even with no evildoer,
  32. even with no explicit hatred.
  33. This association between
    blackness and crime
  34. made its way into the mind
    of my five-year-old.
  35. It makes its way into all of our children,
  36. into all of us.
  37. Our minds are shaped by
    the racial disparities
  38. we see out in the world
  39. and the narratives that help us
    to make sense of the disparities we see:
  40. "Those people are criminal."
  41. "Those people are violent."
  42. "Those people are to be feared."
  43. When my research team
    brought people into our lab

  44. and exposed them to faces,
  45. we found that exposure to black faces
    led them to see blurry images of guns
  46. with greater clarity and speed.
  47. Bias cannot only control what we see,
  48. but where we look.
  49. We found that prompting people
    to think of violent crime
  50. can lead them to direct their eyes
    onto a black face
  51. and away from a white face.
  52. Prompting police officers
    to think of capturing and shooting
  53. and arresting
  54. leads their eyes to settle
    on black faces, too.
  55. Bias can infect every aspect
    of our criminal justice system.

  56. In a large data set
    of death-eligible defendants,
  57. we found that looking more black
    more than doubled their chances
  58. of receiving a death sentence --
  59. at least when their victims were white.
  60. This effect is significant,
  61. even though we controlled
    for the severity of the crime
  62. and the defendant's attractiveness.
  63. And no matter what we controlled for,
  64. we found that black
    people were punished
  65. in proportion to the blackness
    of their physical features:
  66. the more black,
  67. the more death-worthy.
  68. Bias can also influence
    how teachers discipline students.

  69. My colleagues and I have found
    that teachers express a desire
  70. to discipline a black
    middle school student more harshly
  71. than a white student
  72. for the same repeated infractions.
  73. In a recent study,
  74. we're finding that teachers
    treat black students as a group
  75. but white students as individuals.
  76. If, for example,
    one black student misbehaves
  77. and then a different black student
    misbehaves a few days later,
  78. the teacher responds
    to that second black student
  79. as if he had misbehaved twice.
  80. It's as though the sins of one child
  81. get piled onto the other.
  82. We create categories
    to make sense of the world,

  83. to assert some control and coherence
  84. to the stimuli that we're constantly
    being bombarded with.
  85. Categorization and the bias that it seeds
  86. allow our brains to make judgments
    more quickly and efficiently,
  87. and we do this by instinctively
    relying on patterns
  88. that seem predictable.
  89. Yet, just as the categories we create
    allow us to make quick decisions,
  90. they also reinforce bias.
  91. So the very things that help us
    to see the world
  92. also can blind us to it.
  93. They render our choices effortless,
  94. friction-free.
  95. Yet they exact a heavy toll.
  96. So what can we do?

  97. We are all vulnerable to bias,
  98. but we don't act on bias all the time.
  99. There are certain conditions
    that can bring bias alive
  100. and other conditions that can muffle it.
  101. Let me give you an example.

  102. Many people are familiar
    with the tech company Nextdoor.
  103. So, their whole purpose is to create
    stronger, healthier, safer neighborhoods.
  104. And so they offer this online space
  105. where neighbors can gather
    and share information.
  106. Yet, Nextdoor soon found
    that they had a problem
  107. with racial profiling.
  108. In the typical case,
  109. people would look outside their window
  110. and see a black man
    in their otherwise white neighborhood
  111. and make the snap judgment
    that he was up to no good,
  112. even when there was no evidence
    of criminal wrongdoing.
  113. In many ways, how we behave online
  114. is a reflection of how
    we behave in the world.
  115. But what we don't want to do
    is create an easy-to-use system
  116. that can amplify bias
    and deepen racial disparities,
  117. rather than dismantling them.
  118. So the cofounder of Nextdoor
    reached out to me and to others

  119. to try to figure out what to do.
  120. And they realized that
    to curb racial profiling on the platform,
  121. they were going to have to add friction;
  122. that is, they were going
    to have to slow people down.
  123. So Nextdoor had a choice to make,
  124. and against every impulse,
  125. they decided to add friction.
  126. And they did this by adding
    a simple checklist.
  127. There were three items on it.
  128. First, they asked users to pause
  129. and think, "What was this person doing
    that made him suspicious?"
  130. The category "black man"
    is not grounds for suspicion.
  131. Second, they asked users to describe
    the person's physical features,
  132. not simply their race and gender.
  133. Third, they realized that a lot of people
  134. didn't seem to know
    what racial profiling was,
  135. nor that they were engaging in it.
  136. So Nextdoor provided them
    with a definition
  137. and told them that it was
    strictly prohibited.
  138. Most of you have seen
    those signs in airports
  139. and in metro stations,
    "If you see something, say something."
  140. Nextdoor tried modifying this.
  141. "If you see something suspicious,
  142. say something specific."
  143. And using this strategy,
    by simply slowing people down,
  144. Nextdoor was able to curb
    racial profiling by 75 percent.
  145. Now, people often will say to me,

  146. "You can't add friction
    in every situation, in every context,
  147. and especially for people who make
    split-second decisions all the time."
  148. But it turns out we can add friction
  149. to more situations than we think.
  150. Working with the Oakland Police Department
  151. in California,
  152. I and a number of my colleagues
    were able to help the department
  153. to reduce the number of stops they made
  154. of people who were not
    committing any serious crimes.
  155. And we did this by pushing officers
  156. to ask themselves a question
    before each and every stop they made:
  157. "Is this stop intelligence-led,
  158. yes or no?"
  159. In other words,
  160. do I have prior information
    to tie this particular person
  161. to a specific crime?
  162. By adding that question
  163. to the form officers complete
    during a stop,
  164. they slow down, they pause,
  165. they think, "Why am I considering
    pulling this person over?"
  166. In 2017, before we added that
    intelligence-led question to the form,

  167. officers made about 32,000 stops
    across the city.
  168. In that next year,
    with the addition of this question,
  169. that fell to 19,000 stops.
  170. African-American stops alone
    fell by 43 percent.
  171. And stopping fewer black people
    did not make the city any more dangerous.
  172. In fact, the crime rate continued to fall,
  173. and the city became safer for everybody.
  174. So one solution can come from reducing
    the number of unnecessary stops.

  175. Another can come from improving
    the quality of the stops
  176. officers do make.
  177. And technology can help us here.
  178. We all know about George Floyd's death,
  179. because those who tried to come to his aid
    held cell phone cameras
  180. to record that horrific, fatal
    encounter with the police.
  181. But we have all sorts of technology
    that we're not putting to good use.
  182. Police departments across the country
  183. are now required to wear body-worn cameras
  184. so we have recordings of not only
    the most extreme and horrific encounters
  185. but of everyday interactions.
  186. With an interdisciplinary
    team at Stanford,

  187. we've begun to use
    machine learning techniques
  188. to analyze large numbers of encounters.
  189. This is to better understand
    what happens in routine traffic stops.
  190. What we found was that
  191. even when police officers
    are behaving professionally,
  192. they speak to black drivers
    less respectfully than white drivers.
  193. In fact, from the words
    officers use alone,
  194. we could predict whether they were talking
    to a black driver or a white driver.
  195. The problem is that the vast majority
    of the footage from these cameras

  196. is not used by police departments
  197. to understand what's
    going on on the street
  198. or to train officers.
  199. And that's a shame.
  200. How does a routine stop
    turn into a deadly encounter?
  201. How did this happen
    in George Floyd's case?
  202. How did it happen in others?
  203. When my eldest son was 16 years old,

  204. he discovered that
    when white people look at him,
  205. they feel fear.
  206. Elevators are the worst, he said.
  207. When those doors close,
  208. people are trapped in this tiny space
  209. with someone they have been taught
    to associate with danger.
  210. My son senses their discomfort,
  211. and he smiles to put them at ease,
  212. to calm their fears.
  213. When he speaks,
  214. their bodies relax.
  215. They breathe easier.
  216. They take pleasure in his cadence,
  217. his diction, his word choice.
  218. He sounds like one of them.
  219. I used to think that my son
    was a natural extrovert like his father.
  220. But I realized at that moment,
    in that conversation,
  221. that his smile was not a sign
    that he wanted to connect
  222. with would-be strangers.
  223. It was a talisman he used
    to protect himself,
  224. a survival skill he had honed
    over thousands of elevator rides.
  225. He was learning to accommodate the tension
    that his skin color generated
  226. and that put his own life at risk.
  227. We know that the brain is wired for bias,

  228. and one way to interrupt that bias
    is to pause and to reflect
  229. on the evidence of our assumptions.
  230. So we need to ask ourselves:
  231. What assumptions do we bring
    when we step onto an elevator?
  232. Or an airplane?
  233. How do we make ourselves aware
    of our own unconscious bias?
  234. Who do those assumptions keep safe?
  235. Who do they put at risk?
  236. Until we ask these questions
  237. and insist that our schools
    and our courts and our police departments
  238. and every institution do the same,
  239. we will continue to allow bias
  240. to blind us.
  241. And if we do,
  242. none of us are truly safe.
  243. Thank you.