The Science of The Science of Unconscious BiasUnconscious Bias

Toni SchmaderToni SchmaderDepartment of PsychologyDepartment of Psychology

University of ArizonaUniversity of Arizona

Outline of PresentationOutline of Presentation

Understanding unconscious associationsUnderstanding unconscious associations

Demonstration of our biasesDemonstration of our biases

How unconscious bias affects our How unconscious bias affects our behaviorbehavior

Breaking free of biasesBreaking free of biases

Being of Two MindsBeing of Two Minds

Reflective systemReflective system for controlled processing for controlled processing Conscious, explicitConscious, explicit Effortful, requires motivationEffortful, requires motivation Takes more timeTakes more time

Reflexive systemReflexive system for automatic processing for automatic processing Often unconscious, implicitOften unconscious, implicit Requires little effortRequires little effort FastFast

Different neural structures distinguish the Different neural structures distinguish the twotwo Satpute & Lieberman (2006)Satpute & Lieberman (2006)

The Reflexive System UsesThe Reflexive System UsesImplicit AssociationsImplicit Associations

Cognitive links between concepts that co-varyCognitive links between concepts that co-vary

Bring one to mind, others are activatedBring one to mind, others are activated

Activation can happen unconsciouslyActivation can happen unconsciously

...can be at odds with conscious goals...can be at odds with conscious goals

… …can influence attention, can influence attention, perception, perception, judgment and behaviorjudgment and behavior

LAUNDRYLAUNDRY

The procedure is quite simple. First, you The procedure is quite simple. First, you arrange things into different groups. Of arrange things into different groups. Of course, one pile may be sufficient, course, one pile may be sufficient, depending on how much there is to do. If depending on how much there is to do. If you have to go somewhere else due to you have to go somewhere else due to lack of facilities, that is the next step; lack of facilities, that is the next step; otherwise you are pretty well set. It is otherwise you are pretty well set. It is important not to overdo things. That is, it important not to overdo things. That is, it is better to do too few things at once is better to do too few things at once than too many. At first the whole than too many. At first the whole procedure will seem complicated. Soon, procedure will seem complicated. Soon, however, it will become just another however, it will become just another facet of life.facet of life.

COWXXXXXXXX

Count the Number of Passes between White vs. Black shirted Players

Neisser (1979)

Unconscious Gender BiasesUnconscious Gender Biases Unequal gender distribution of men and Unequal gender distribution of men and

women in certain roles creates implicit women in certain roles creates implicit associationsassociations Eagly (1987); Glick & Fiske (1996)Eagly (1987); Glick & Fiske (1996)

With domains…With domains… Work = male; Family = femaleWork = male; Family = female Science = male; Arts = femaleScience = male; Arts = female

That generalize to traits…That generalize to traits… Male = independent, competentMale = independent, competent Female = cooperative, warmFemale = cooperative, warm

One Way to Measure One Way to Measure Unconscious BiasUnconscious Bias

The Implicit Association Test (IAT)The Implicit Association Test (IAT)Greenwald, McGhee, & Schwartz (1998)Greenwald, McGhee, & Schwartz (1998)

Measures strength of association Measures strength of association between conceptsbetween concepts

Based on premise that associated Based on premise that associated concepts will be easier to categorize concepts will be easier to categorize togethertogether

Microsoft PowerPoint Presentation

Men and Women both Show Men and Women both Show Implicit Gender BiasesImplicit Gender Biases

Association of math Association of math = male & = male &

arts = femalearts = female

Nosek et al. (2002)Nosek et al. (2002)

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400.0

500.0

IAT

eff

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Men

Women

Association of men Association of men = independent & = independent & women = communalwomen = communal

Rudman & Glick (2001)Rudman & Glick (2001)

0.0

0.5

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1.5

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Men

Women

Data on the IATData on the IAT(Nosek, Banaji, & Greenwald, 2005)(Nosek, Banaji, & Greenwald, 2005)

In comparison, effect size for gender differences in complex mathematical problem solving: d = .29

Hyde, Fennema, & Lamon, 1990

Implications for BehaviorImplications for Behavior Implicit Implicit racial biasesracial biases predict… predict…

Amygdala activation (fear response)Amygdala activation (fear response) Phelps et al. (2000)Phelps et al. (2000)

Lower performance ratingsLower performance ratings Amodio & Devine (2006)Amodio & Devine (2006)

Avoid the other groupAvoid the other group Amodio & Devine (2006); Phills & Kawakami (2005)Amodio & Devine (2006); Phills & Kawakami (2005)

More negative interactionsMore negative interactions Dovidio et al., (2002); McConnell & Leibold (2001)Dovidio et al., (2002); McConnell & Leibold (2001)

Predicted What

Was Said

Predicted How it

Was Said

Her view of the

Interactionr = -.41**

r = .40**

His view of the

Interaction

Degree of Implicit Bias“Black = Bad”

Degree of Explicit Bias

“I’m not prejudiced”

Dovidio et al., 2002

r = .36*

r = .34*

Implications for BehaviorImplications for Behavior Implicit Implicit gender biasesgender biases … …

Predict biased ratings of job candidates Predict biased ratings of job candidates Rudman & Glick (2001)Rudman & Glick (2001)

Might be manifested in letters of recommendationMight be manifested in letters of recommendation Schmader et al. (2008), Trix & Psenka (2003)Schmader et al. (2008), Trix & Psenka (2003) Men are more often described with superlatives & as having Men are more often described with superlatives & as having

abilityability Women are more often described as working hardWomen are more often described as working hard

Can contribute to women’s weaker association with Can contribute to women’s weaker association with mathmath

Even among math & science majorsEven among math & science majorsNosek et al. (2002)Nosek et al. (2002)

A Two Strategy SolutionA Two Strategy Solution

Unconscious Biases

Judgment &Behavior

Consciously OverrideBiases

Change ImplicitAssociations

1) Overriding Unconscious Bias1) Overriding Unconscious Bias

Be Be motivatedmotivated to control bias to control bias

Be Be awareaware of the potential for bias of the potential for bias

Take the Take the timetime to consider individual to consider individual characteristics and avoid stereotyped characteristics and avoid stereotyped evaluationsevaluations

ExampleExampleWhen writing evaluations, avoid:When writing evaluations, avoid:

1. Using first names for women or minority faculty and titles for men (Joan was anasset to our department.” –vs.- “Dr. Smith was an asset to our department.”)

2. Gendered adjectives (“Dr. Sarah Gray is a caring, compassionate physician” –vs.– Dr. Joel Gray has been very successful with his patients”)

3. Doubt raisers or negative language (“although her publications are not numerous”

or “while not the best student I have had, s/he”)

4. Potentially negative language (“S/he requires only minimal supervision” or“S/he is totally intolerant of shoddy research”)

5. Faint praise (“S/he worked hard on projects that s/he was assigned” or “S/he hasnever had temper tantrums”)

6. Hedges (“S/he responds well to feedback”)

7. Unnecessarily invoking a stereotype (“She is not overly emotional”; “He is very

confident yet not arrogant”; or “S/he is extremely productive, especially assomeone who attended inner city schools and a large state university”

A Two Strategy SolutionA Two Strategy Solution

Unconscious Biases

Judgment &Behavior

Consciously OverrideBiases

Change ImplicitAssociations

2) Changing Unconscious Bias2) Changing Unconscious Bias

The effectiveness of education The effectiveness of education (Rudman et al., (Rudman et al., 2001) 2001)

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Study 1 Study 2

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Control Class w/ White Professor

Prejudice Seminar w/ Black Professor

2) Changing Unconscious Bias2) Changing Unconscious Bias

The effectiveness of education The effectiveness of education (Rudman et al., (Rudman et al., 2001)2001)

The effectiveness of exposure The effectiveness of exposure (Dasgupta & Asgari, (Dasgupta & Asgari, 2004)2004)

2) Changing Unconscious Bias2) Changing Unconscious Bias

The effectiveness of education The effectiveness of education (Rudman et al., (Rudman et al., 2001)2001)

The effectiveness of exposure The effectiveness of exposure (Dasgupta & Asgari, (Dasgupta & Asgari, 2004)2004)

Take-Away PointsTake-Away Points

Implicit bias is distinct from conscious motivationImplicit bias is distinct from conscious motivation

We all have these biases due to cultural exposureWe all have these biases due to cultural exposure

They can affect behavior unless we override themThey can affect behavior unless we override them

They can be changed with education and They can be changed with education and exposureexposure

Questions, comments, insights?Questions, comments, insights?

Take other Implicit Associations Tests Online: https://implicit.harvard.edu/implicit/

Workplace ConversationsWorkplace Conversations

18 male and 18 female STEM faculty18 male and 18 female STEM faculty 88% response rate88% response rate

Electronically Activated Recorder (EAR)Electronically Activated Recorder (EAR) Sampled audio snippets during 3 workdaysSampled audio snippets during 3 workdays Participants complete workplace surveys of job Participants complete workplace surveys of job

satisfaction and disengagementsatisfaction and disengagement

CodingCoding Conversational snippets transcribed & coded Conversational snippets transcribed & coded

for contentfor content

Conversations with male colleagues

Conversations with female colleagues

Male Participants

Female Participants

Male Participants

Female Participants

Research talk…

Job disengagement -.42a .72b .44bc -.18acd

Job satisfaction -.27a -.23abd .33bc .41c

Collaboration talk…

Job disengagement -.26a .39b .51b .06ab

Job satisfaction -.24abc -.50ab .03abc .31ac

Social talk…

Job disengagement .51a -.50b -.22bc .50ad

Job satisfaction .29a .58ab -.25ac -.29cd

ConclusionsConclusions

Female faculty feel greater job Female faculty feel greater job disengagement and less satisfaction…disengagement and less satisfaction… to the degree that they discuss research and to the degree that they discuss research and

collaboration collaboration and and do notdo not discuss social topics discuss social topics

… …with their male with their male colleaguescolleagues