The cycle of workplace bias and how to interrupt it

The cycle of workplace bias and how to interrupt it
Nicole M. Stephensa,
*, Lauren A. Riveraa
, Sarah S.M. Townsendb
aManagement and Organizations Department, Kellogg School of Management, Northwestern University, USA bManagement and Organization Department, Marshall School of Business, University of Southern California, USA
A R T I C L E I N F O
Article history:
Available online 31 August 2021
Keywords:
Diversity
Bias
Bias reduction
Organizations
Workplace evaluations
Inequality
Gender
Race
Equity
Inclusion
Interventions
A B S T R A C T
A rich body of research throughout the social sciences demonstrates that bias—people’s tendency to
display group-based preferences—is a major obstacle in the way of promoting diversity, equity, and
inclusion in the workplace. The current article moves beyond the single-level focus of prior theories of
workplace bias to propose a novel theoretical model that conceptualizes workplace bias as a multilevel
cycle. First, we discuss the theoretical foundations of our bias cycle theory and describe why
understanding the nature of workplace bias—and effectively reducing it—requires considering the
reciprocal influences of both individual and organizational levels of the cycle. Specifically, we describe
how workplace bias operates as a cycle and then propose that successfully reducing workplace bias
requires multilevel interventions that interrupt bias across both the individual and organizational levels
of the cycle. Second, because workplace bias is reproduced through both of these levels, we review and
bring together literatures that are often considered separately: psychology research on reducing bias at
the individual level and sociology and management research on reducing bias at the organizational level.
Third, we use our bias cycle theory to formulate general principles for determining how to begin and how
to pair interventions across levels. Finally, we conclude by discussing our theoretical contributions and
outlining directions for future research.
© 2021 Elsevier Ltd. All rights reserved.
The cycle of workplace bias and how to interrupt it
The diversity, equity, and inclusion space is a booming “big
business” (Zelevansky, 2019). By some estimates, organizations in
the United States spend $8 billion annually (Mehta, 2019). Despite
organizations’ widespread interest in improving diversity, equity,
and inclusion, one key obstacle that stands in the way is bias: the
tendency to show a disproportionate preference for people or
groups based on social group membership (e.g., gender, race,
sexuality, social class; Allport, 1954; Banaji & Greenwald, 2016;
Eberhardt, 2019). Bias can emerge due to reliance on group-based
stereotypes and/or prejudice toward social groups—i.e., animosity
or antipathy.
For decades, scholars across disciplines have sought to develop
theories to better understand the sources, functions, and
consequences of bias. Most theories of bias focus on a single level
without considering the other level. That is, they consider bias at
either the individual level (i.e., in hearts and minds) or organizational level (i.e., policies and practices; Banaji & Greenwald, 2016;
Bielby, 2000; Dovidio et al., 2008; Eberhardt, 2019; Petersen &
Saporta, 2004). Just as prior theories of bias have focused on a
single level, so too have interventions to reduce bias (e.g., a
diversity training; Bezrukova, Spell, Perry, & Jehn, 2016; Onyeador,
Hudson, & Lewis, 2021; Stephens, Markus, & Fryberg, 2012).
In this article, we move beyond this “single-level” focus to
propose a novel theoretical model that conceptualizes workplace
bias as a multilevel cycle (the “workplace bias cycle”). Consistent
with research on the interdependence between people and their
social contexts (Hamedani & Markus, 2019; Markus & Kitayama,
2010; Plaut, 2010; Stephens, Fryberg, Markus, Johnson, &
Covarrubias, 2012), we theorize that workplace bias is produced
and reproduced through the ongoing cycle through which
individuals and organizations reciprocally influence each other.
Given the cyclical nature of bias, our theory helps to explain why
single-level interventions that change either the individual or
organizational level in isolation often fail to reduce bias. Building
on this insight, our theory also suggests that successfully reducing
workplace bias requires multilevel interventions that interrupt the
workplace bias cycle at both the individual level (i.e., changing
hearts and minds) and the organizational level (i.e., redesigning
policies and practices).
We proceed as follows. First, we discuss the theoretical
foundations of our bias cycle theory and describe why
* Corresponding author at: Kellogg School of Management, Northwestern
University, 2211 Campus Drive, Evanston, IL 60208, USA.
E-mail address: [email protected] (N.M. Stephens).
https://doi.org/10.1016/j.riob.2021.100137
0191-3085/© 2021 Elsevier Ltd. All rights reserved.
Research in Organizational Behavior 40 (2020) 100137
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understanding the nature of workplace bias—and effectively
reducing it—requires considering the reciprocal influences of both
individual and organizational levels of the bias cycle. Second, we
review empirically supported interventions for reducing the
expression of bias in the workplace. Because workplace bias is
reproduced through both individual and organizational levels of
the bias cycle, we review and bring together literatures that are
often considered separately: psychology research on reducing bias
at the individual level and sociology and management research on
reducing bias at the organizational level. Third, we use our bias
cycle theory to formulate general principles for determining how
to begin and how to pair interventions across levels. We conclude
by discussing our theoretical contributions and outlining promising directions for future research.
Workplace bias operates as a cycle
Bias can occur at either an implicit or explicit level—that is,
either outside of or within the bounds of conscious awareness (e.g.,
Dovidio, Kawakami, & Gaertner, 2002; Greenwald & Banaji, 1995).
At the more implicit level, bias involves automatic associations,
including stereotypes based on social group membership (e.g.,
Bodenhausen, 1990; Greenwald & Banaji, 1995). Such associations
develop, in part, due to humans’ cognitive limitations and resulting
need for heuristics or mental shortcuts (Tversky & Kahneman,
1974). At the more explicit level, bias involves prejudice, typically
defined by more conscious feelings of negative affect or antipathy
toward individuals or groups based on their social group
membership (Allport, 1954). Throughout this article, we use the
term bias to broadly refer to the preference for people and social
groups based on the use of stereotypes and/or reliance on
prejudice.
As noted above, existing theories of bias tend to focus on either
the individual or organizational level of the bias cycle. Indeed,
research in psychology often examines how and why bias emerges
at an individual level, considering how bias becomes embedded in
and expressed through individuals’ attitudes and behavior, as well
as how these attitudes and behavior can affect the nature and
quality of their interactions with others (e.g., Banaji & Greenwald,
2016; Dovidio et al., 2002; Eberhardt, 2019). Likewise, research in
sociology and management more often examines how bias
becomes embedded in—and reproduced through–policies and
practices at an organizational level (e.g., Correll, 2017; Kalev, 2009;
Pedulla & Thébaud, 2015; Stamarski & Son Hing, 2015).
The current article moves beyond this single-level focus to
propose that it is necessary to understand that workplace bias is
reproduced in a multilevel cycle. As shown in Fig. 1, understanding
workplace bias as a cycle means recognizing the reciprocal
influences of bias across individual and organizational levels:
biased attitudes and behavior give rise to biased policies and
practices, and, in turn, biased policies and practices fuel biased
attitudes and behavior (Hamedani & Markus, 2019; Markus &
Kitayama, 2010; Stephens, Fryberg et al., 2012; Stephens, Markus,
& Phillips, 2014). Specifically, biased attitudes can foster intergroup
interactions that are infrequent and low quality (i.e., stressful and
depleting),1 and lead to a preference for biased policies and
practices at the organizational level. In turn, biased policies and
practices can lead to infrequent and low-quality intergroup
interactions, and sustain and perpetuate biased attitudes and
behavior at the individual level. By emphasizing the reciprocal
influences of bias across levels, our theory broadens our
understanding of the sources of bias and enhances our understanding of how bias is produced and reproduced.
To illustrate how the workplace bias cycle operates, as a starting
point, consider how bias at the individual level can both shape
interactions with others, as well as the policies and practices that
are adopted at the organizational level. Take, for example, the
situation of a manager who endorses the negative stereotype that
women are not suited for leadership positions because they are too
relational (Cuddy, Glick, & Beninger, 2011; Cuddy, Fiske, & Glick,
2004; Glick & Fiske, 2001). Given this biased view, research
suggests the manager will have lower quality interactions with
women in their organization (e.g., Kray, Kennedy, & Van Zant, 2014;
Richeson, Trawalter, & Shelton, 2005; Richeson & Shelton, 2007),
and be less likely to mentor or promote them (Milkman, Akinola, &
Chugh, 2012; Moss-Racusin, Dovidio, Brescoll, Graham, & Handelsman, 2012). Moreover, they will also be more likely to prefer—and
ultimately, be more likely to enact—policies and practices that
reflect their biased preferences (Cech & Blair-Loy, 2010; Cunningham & Sartore, 2010; Soni, 2000). In the case of establishing the
criteria for hiring, they may be more likely to define merit based on
the characteristics that are stereotypically linked to masculinity in
our society (Bian, Leslie, & Cimpian, 2017; Ensmenger, 2010;
Gaucher, Friesen, & Kay, 2011; Kray & Kennedy, 2017; Lerchenmueller, Sorenson, & Jena, 2019). For example, they may include
confidence, the ability to challenge others’ opinions, or even
willingness to work on nights and weekends. In other words, they
are likely to define merit based on a masculine default or ideal
(Cheryan & Markus, 2020).
After these masculine ideals become embedded in policies and
practices, the cycle continues. Consider how bias embedded at an
organizational level (e.g., biased hiring criteria) can further shape
and amplify bias in individuals’ attitudes and behavior, as well as in
interactions with others. For example, to the extent that the
manager relies on the masculine criteria for hiring, the manager
would assume that “good” job candidates are those who display
more stereotypically masculine qualities and are therefore more
likely to be men. Accordingly, the manager would likely find
interactions with women to be more stressful or depleting, rate
women as less qualified than men, and hire women less frequently
(e.g., Cuddy et al., 2004). Now that these masculine criteria are
institutionalized as part of the hiring process, they may further
encourage the manager to see merit through the lens of gender
stereotypes. This gendered view of merit may lead the manager to
use these criteria to evaluate members of their team and to
generally assume that their female colleagues have less merit and
potential than their male counterparts (e.g., Turco, 2010). As a
result, they may be even less likely to seek out opportunities to
Fig. 1. The cycle of workplace bias.
1 Research suggests that biased attitudes foster interactions characterized by
emotional and cognitive depletion, stress, and threatfor both parties involved in the
intergroup interactions (e.g., Richeson et al., 2005; Richeson & Shelton, 2007).
N.M. Stephens, L.A. Rivera and S.S.M. Townsend Research in Organizational Behavior 40 (2020) 100137
2
work with women and to advocate for or promote women (e.g.,
Castilla & Benard, 2010; Heilman, Manzi, & Caleo, 2019; Joshi, Son,
& Roh, 2015; Milkman, Akinola, & Chugh, 2015). As the cycle
continues, workplace bias across levels of the cycle will be
reproduced, sustained, and ultimately even more entrenched over
time.
The cycle of workplace bias informs intervention
Our theory extends single-level theories of bias by emphasizing
that bias is produced via a multilevel cycle. Theories of bias not
only guide scholars’ understanding of the nature of how bias
operates, but also the interventions that they develop to reduce the
expression of bias. Indeed, the single-level focus of prior theories
has inspired interventions that target a single level (e.g., a diversity
training; Bendick, Egan, & Lofhjelm, 2001; Chang et al., 2019; Cox,
1994). In psychology, interventions typically seek to reduce bias
embedded in individuals’ hearts and minds2 3 (e.g., Dixon, Levine,
Reicher, & Durrheim, 2012; Onyeador et al., 2021; Paluck, Porat,
Clark, & Green, 2021; Paluck & Green, 2009). We refer to these as
individual level interventions. Conversely, in sociology and
management, interventions often seek to reduce bias embedded
in organizational level policies or practices (e.g., Kalev, 2009; Kalev,
Dobbin, & Kelly, 2006; Pedulla & Thébaud, 2015; Reskin, 2000;
Stamarski & Son Hing, 2015). We refer to these as organizational
level interventions.
Why single-level approaches to intervention so often fail
By conceptualizing workplace bias as a multilevel cycle, our
theory explains why interventions at a single level are often fragile
or hard to sustain, or just plain ineffective (Bezrukova et al., 2016;
Kalev et al., 2006; Onyeador et al., 2021). Indeed, an individual
level intervention on its own is likely to be ineffective.
Interventions that target the individual level, such as countering
stereotypes or perspective taking, have been shown to reduce the
reliance on group-based stereotypes, reduce prejudice toward
outgroups, and improve the quality of intergroup interactions (e.g.,
Brambilla, Ravenna, & Hewstone, 2012; Galinsky & Moskowitz,
2000; Todd, Bodenhausen, Richeson, & Galinsky, 2011). However,
given that workplace bias operates as a cycle, changing the
individual level on its own (e.g., reducing the tendency to express
bias in behavior) will not necessarily lead to a reduction in biased
outcomes (e.g., hiring or promotion decisions) unless individual
level interventions are paired with organizational level changes to
policies and practices. For example, encouraging intergroup
contact could reduce individual employees’ prejudice toward
other employees and increase their motivation to make more fair
and less biased hiring decisions. However, if an organization’s
policy for sourcing job applications or scoring re’sume’s results in
an interview pool that is homogenous, managers will have limited
ability to act on intentions to make less biased decisions. Thus,
even when individuals are motivated to avoid bias, the policies and
practices that guide their decisions can nevertheless be conduits of
bias (e.g., Kalev, 2009; Pedulla & Thébaud, 2015; Stamarski & Son
Hing, 2015).
Conversely, organizational level interventions in the absence of
individual level interventions are also likely to fail to reduce
workplace bias over time. Indeed, a lack of internal support for
diversity programs is a major reason why they are not successfully
adopted (Dobbin, Kim, & Kalev, 2011). If individuals are not open to
diversity and motivated to reduce bias, organizational efforts to
reduce bias are likely to have little impact or even elicit resistance
among employees. Indeed, employees may actively resist these
organizational level changes and refuse to adopt them (Dobbin,
Schrage, & Kalev, 2015; Plant & Devine, 2001). In sum, a single-level
approach is likely to fail because of the ongoing bias cycle through
which both individual and organizational levels influence one
another to sustain biased outcomes.
Interrupting workplace bias requires multilevel intervention
By conceptualizing bias as a mutually reinforcing cycle, our
theory goes beyond illuminating why single-level approaches
often fail to suggest that effectively interrupting workplace bias
requires multilevel intervention. That is, interventions should
interrupt the workplace bias cycle at both the individual level (i.e.,
changing hearts and minds) and the organizational level (i.e.,
redesigning policies and practices). Intervening at both levels
should render the desired changes more likely to endure because
reducing bias at one level tends to reinforce and amplify the
reduction of bias at the other level in an ongoing cycle.
Consider the impact of a multilevel intervention with the
example of the manager who endorses gender stereotypes. To
reduce the impact of these stereotypes and reduce gender
disparities in hiring, an organization could pair an individual level
intervention to counter group-based stereotypes with an organizational level intervention to reduce the influence of stereotypes
on hiring decisions. By reducing bias in the manager’s attitudes, the
individual level intervention should increase their motivation to
behave in less biased ways. As a result, they should have higher
quality interactions with female employees and be more open to
mentoring and supporting them. To capitalize on the manager’s
newfound motivation to reduce bias, our theory suggests that the
organization should also implement policies to reduce bias at the
organizational level. In turn, when the manager engages with the
new egalitarian policies, this behavior should reinforce and
increase their motivation to behave in less biased ways.
Just as our theory suggests that interventions to reduce bias
should be multilevel, so too does it suggest that indicators of
successful bias reduction should be evident across both individual
and organizational levels. Focusing on the goal of reducing gender
disparities in hiring outcomes, at an individual level, there should
be improvements in individual employees’ attitudes and behavior
(e.g., more receptiveness toward gender diversity, higher quality
cross-gender interactions). At an organizational level, there should
be parallel improvements in the equity of hiring outcomes (e.g.,
resume screens, hiring decisions). These multilevel improvements
should persist over time and serve to increase gender diversity.
In sum, our bias cycle theory clearly suggests that interventions
to reduce workplace bias should target multiple levels. In the
section below, we therefore review and bring together empirically
supported interventions for reducing bias across both individual
and organizational levels. We first review the individual level and
then the organizational level separately. Afterward, we offer a
discussion of multilevel intervention principles to determine how
to begin to intervene in an organization and how to pair
interventions across levels.
Individual level interventions to reduce bias
In this section, we review psychology research on reducing bias
at the individual level (e.g., in attitudes and behavior). We first
provide a brief overview of research on diversity training because it
is the applied, multifaceted approach that is most commonly used
2 Individual level interventions—those designed to change hearts and minds—can
be delivered to individuals in isolation or through interactions (e.g., intergroup
interactions).
3 We do not include construal interventions in our article because these
interventions are not designed to reduce bias (Walton & Wilson, 2018). Instead,they
tend to focus on changing the mindsets of negatively stereotyped and/or lower
status individuals in a way that can empower them to improve their academic
performance.
N.M. Stephens, L.A. Rivera and S.S.M. Townsend Research in Organizational Behavior 40 (2020) 100137
3
by organizations (Bendick et al., 2001; Cox, 1994). Second, we
highlight five promising individual level interventions that can be
incorporated into diversity training to make it more effective:
increasing intergroup contact, countering stereotypes, encouraging perspective taking, finding common ground, and leveraging
social influence.
To identify these five interventions, we drew from psychology
research on interventions that seek to reduce bias in hearts and
minds (e.g., Paluck et al., 2021). We focused on interventions that
met the following four criteria: (a) are organizationally relevant,
(b) have the stated goal of reducing bias, (c) have some empirical
support for their effects, and (d) are conceptually distinct4 from
each other. Although these five interventions are not an exhaustive
or comprehensive list of all potential individual level interventions,
they represent some of the more promising options for organizations to reduce bias at this level.
Diversity training
Diversity training is a broad, heterogeneous category that can
incorporate many different types of content (e.g., awareness of
bias, strategies to reduce bias) and use various formats (i.e., lecture,
video, group activities). Diversity training has been defined as a
“distinct set of instructional programs aimed at facilitating positive
intergroup interactions, reducing prejudice and discrimination,
and enhancing the skills, knowledge, and motivation of participants to interact with diverse others” (Bezrukova et al., 2016, p.
1228). In a recent review of individual level interventions, Paluck
et al. (2021) explained that diversity training “typically involve(s)
more than one theoretical mechanism, and so experiments testing
their outcomes are more akin to program evaluations than to
theoretical tests” (p. 541). At a high level, what these trainings
share in common is their efforts to increase people’s understanding of what bias is and how it affects behavior.
Although such training is ubiquitous in today’s Fortune 500
organizations (Bendick et al., 2001; Cox, 1994), there are very few
rigorous evaluations of its efficacy in changing individual attitudes
and behavior. For example, Paluck et al. (2021) counted only six
experimental studies examining the efficacy of diversity training in
the past decade. Furthermore, they identified the Chang et al.
(2019) study as the only experimental study to test the outcomes
associated with a diversity training in an actual organization.
Given the heterogeneity of content included in diversity
training, evaluations of its impact often produce inconsistent
results. Review papers that compare its efficacy to other types of
individual level interventions find that diversity training is among
the least effective (i.e., based on effect sizes) for changing attitudes
and behavior (Paluck et al., 2021). The small body of research on
the efficacy of diversity training suggests that, under optimal
conditions, diversity training can have small benefits. Specifically,
it can help individuals acquire new knowledge about diversity,
change implicit and explicit attitudes, and even increase behaviors
that foster diversity (e.g., Carnes et al., 2012; Devine, Forscher,
Austin, & Cox, 2012; Lai, Hoffman, & Nosek, 2013; Shields,
Zawadzki, & Johnson, 2011).
In sum, diversity training—the most commonly used applied
approach to reduce bias in organizations—has potential to increase
people’s understanding of and motivation to reduce bias. However,
we suggest diversity training will be more effective to the extent
that it incorporates empirically supported individual level
interventions.
Empirically supported individual level interventions
The individual level interventions that have the most empirical
support in the psychological literature on prejudice reduction
include: increasing intergroup contact, countering stereotypes,
encouraging perspective taking, finding common ground, and
leveraging social influence (Paluck et al., 2021). Although these
individual level interventions are widely examined by psychologists, they are typically studied in the laboratory.5 Despite few
studies that test these interventions in the workplace, our bias
cycle theory clearly points to the need to leverage—and also test—
these individual level interventions in the workplace.
Increasing intergroup contact
The most studied individual level intervention for reducing the
affective dimensions of bias—namely, group-based prejudice—is
intergroup contact. Intergroup contact simply means participating
in an interaction with people who are members of an outgroup
(Allport, 1954).6
Research clearly shows that intergroup contact interventions
can improve attitudes and reduce prejudice toward outgroups
(e.g., race, social class, religion; Boag & Wilson, 2014; Dovidio,
Gaertner, & Kawakami, 2003; Lemmer & Wagner, 2015; Lowe,
2021; Pettigrew & Tropp, 2006; Scacco & Warren, 2018; Schroeder
& Risen, 2016). Intergroup contact interventions have sought to
reduce bias in various ways. For example, intergroup contact
interventions have assigned soldiers to live with roommates from
different ethnic backgrounds (Finseraas & Kotsadam, 2017);
encouraged Iraqi Christians and Muslims to play soccer together
on the same team (Mousa, 2020); and asked college students from
different racial backgrounds to complete a bonding task involving
self-disclosure (Page-Gould, Mendoza-Denton, & Tropp, 2008).
Countering stereotypes
A second intervention that can be used to reduce bias at the
individual level of the bias cycle is countering stereotypes.
Countering stereotypes refers to being presented with or imagining
a member of an outgroup who is inconsistent with a stereotype of
their group (e.g., based on attributes or behavior). According to
Paluck et al. (2021), the goal of these interventions is to “alter a
particular aspect of a person’s cognitive association with or
assessment of an outgroup through practice or repeated contradictory pairings” (p. 543). In other words, these interventions seek
to interrupt and alter people’s automatic, stereotypic associations
with outgroups.
Research finds that providing counter-stereotypic information
can reduce the activation of stereotypes, suppress the expression of
prejudice, and reduce discriminatory behavior (Dasgupta &
Greenwald, 2001; Devine & Monteith, 1999; Kawakami, Dovidio,
Moll, Hermsen, & Russin, 2000; King & Ahmad, 2010; King,
Shapiro, Hebl, Singletary, & Turner, 2006; Mendoza, Gollwitzer, &
Amodio, 2010; Olson & Fazio, 2006; Singletary & Hebl, 2009).
Interventions that seek to counter people’s stereotypes of outgroups have done so in various ways. For example, these
interventions have provided counter-stereotypic information
4 For example, we did not include educational programs such as intergroup
dialogues or cross-cultural training because they incorporate interventions such as
perspective-taking and countering stereotypes that we review elsewhere.
5 Among the interventions we review, to our knowledge, the only one that has
been examined in the workplace is intergroup contact. The few studies that have
been conducted on intergroup contact in the workplace suggest that this
intervention is beneficial for reducing bias in the workplace (e.g., the impact of
ageism on hiring; Fasbender & Wang, 2017; Pagotto, Voci, & Maculan, 2010). 6 The original contact hypothesis proposed that the benefits of intergroup contact
only occur in situations that have equal status, intergroup cooperation, common
goals, and institutional support (Allport, 1954). More recent research, however,
found no empirical support for the claim that these conditions are necessary to
realize the benefits of intergroup contact (Pettigrew & Tropp, 2006).
N.M. Stephens, L.A. Rivera and S.S.M. Townsend Research in Organizational Behavior 40 (2020) 100137
4
about Muslims (e.g., in a resume; King & Ahmad, 2010), exposed
people to counter-stereotypic representations of women (e.g., as
strong and capable; Blair, Ma, & Lenton, 2001), and trained people
to have positive reactions when encountering Black people (e.g., an
“approach response”; Kawakami, Phills, Steele, & Dovidio, 2007;
Stewart & Payne, 2008).7
Encouraging perspective taking
A third intervention that can be used to reduce bias at the
individual level of the bias cycle is perspective taking. Perspective
taking means actively considering others’ psychological experiences (e.g., thoughts or emotions; Dovidio et al., 2004). This could
be accomplished by either imagining how another person feels or
imagining how you would feel if you were in another person’s
situation. In either case, these interventions work to decrease bias
toward outgroups by “lead[ing] to a merging of the self and the
other, in which the perspective-taker’s thoughts toward the target
become more ‘selflike’” (Galinsky & Moskowitz, 2000, p. 709; see
also Davis, Conklin, Smith, & Luce, 1996). By connecting outgroups
to the self—and therefore to one’s ingroup, this intervention can
redirect typical ingroup favoritism processes so that the positive
evaluation typically reserved for one’s ingroup is extended to
outgroups.
Research from both the laboratory and the field finds that
perspective taking interventions can reduce bias toward outgroups—i.e., reduce the accessibility and application of stereotypes, foster more positive emotions or attitudes, and create more
approach-oriented behaviors (e.g., Batson et al., 1997; Berthold,
Leicht, Methner, & Gaum, 2013; Broockman & Kalla, 2016; Finlay &
Stephan, 2000; Galinsky & Moskowitz, 2000; Todd et al., 2011;
Vescio, Sechrist, & Paolucci, 2003). Interventions that have
encouraged perspective taking have done so in various ways.
For example, they have asked people to adopt the perspective of a
Black man in a video or photograph (Todd et al., 2011); asked
people to write an essay describing the experience of a person from
a negatively stereotyped group (e.g., Álvarez-Castillo, Equizábal,
Cámara, & González, 2014); and used virtual reality to encourage
people to actually “see” themselves in someone else’s shoes (e.g.,
Banakou, Hanumanthu, & Slater, 2016; Oh, Bailenson, Weisz, &
Zaki, 2016).
Finding common ground
A fourth intervention that can be used to reduce bias at the
individual level of the bias cycle is finding common ground. Finding
common ground means finding something in common with an
outgroup member—for example, a common experience or activity,
value, preference, background, or identity. The literature has
referred to this intervention as creating a “common ingroup
identity” or a “superordinate identity” (Gaertner, Dovidio, Nier,
Ward, & Banker, 1999; Gaertner et al., 2000).
Finding common ground builds on some of the key tenets of
social identity theory: the idea people prefer their ingroups to
outgroups and that simply categorizing people as “ingroup” is
enough to shift that preference (Tajfel, 1974; Turner, 1975; Turner,
Brown, & Tajfel,1979). Accordingly, finding common ground works
by broadening the circle of others included in one’s ingroup or by
altering how groups are perceived within existing group
boundaries. If outgroups are viewed instead as part of and
connected to that self and one’s ingroup, then people should show
the same kind of “ingroup” preference for people or groups
previously viewed as “outgroup.”
Research suggests that finding common ground can help to
reduce bias against outgroup members—i.e., increase positive
attitudes and decrease intergroup threat (Craig & Richeson, 2012;
Gaertner & Dovidio, 2000; Gaertner, Dovidio, Anastasio, Bachman,
& Rust, 1993; Hall, Crisp, & Suen, 2009). Interventions have
encouraged people to find common ground in various ways. For
example, finding common ground interventions have made a
shared “American” identity salient among Democrats and Republicans (Riek, Mania, Gaertner, McDonald, & Lamoreaux, 2010);
asked people to write about characteristics that the ingroup and
outgroup have in common (Hall et al., 2009); and reminded
different disadvantaged groups (e.g., racial and sexual minorities)
of their common experiences of discrimination (Cortland et al.,
2017).
Leveraging social influence
A fifth intervention that can be used to reduce bias at the
individual level of the bias cycle is leveraging social influence
(Blanchard, Crandall, Brigham, & Vaughn, 1994; Crandall, Eshleman, & O’brien, 2002; Monteith, Deneen, & Tooman,1996; Sechrist
& Stangor, 2001; Stangor, Sechrist, & Jost, 2001). Leveraging social
influence means using social norms or pressure (e.g., from peers or
ingroup members) to reduce bias. The literature has referred to
these types of interventions as “social norm” or “social consensus”
interventions.
These interventions build on theories of the power of social
norms to guide and change people’s attitudes and behavior (e.g.,
Cialdini, Reno, & Kallgren, 1990). These interventions work by
changing people’s views about which attitudes or behaviors are
normative, desirable, or appropriate (e.g., among their peers;
Goldstein, Cialdini, & Griskevicius, 2008; Paluck et al., 2021;
Prentice & Paluck, 2020). Based on these altered norms, people
then shift their attitudes or behavior to bring them into alignment
with the norms.
Research from both the laboratory and the field suggests that
leveraging social influence can help to reduce endorsement of
group-based stereotypes as well as the expression of prejudice
(Blanchard et al., 1994; Crandall et al., 2002; Gómez, Tropp,
Vázquez, Voci, & Hewstone, 2018; Monteith et al., 1996; Patel,
2013; Robinson, 2010; Sechrist & Milford-Szafran, 2011; Sechrist &
Stangor, 2001; Stangor et al., 2001). Interventions have leveraged
peer influence to reduce bias in various ways. For example, they
have made salient non-prejudiced norms toward gay men
(Monteith et al., 1996); shared peer group norms about the
frequency of others’ cross-group friendships (Gómez et al., 2018);
and provided consensus information about others’ different beliefs
about racial groups (Stangor et al., 2001).
Summary
In this section, we provided an overview of research on diversity
training, as well as the individual interventions that have the most
empirical support in the psychological literature on prejudice
reduction. Although these individual level interventions can be
incorporated into diversity training, they could also be used in
other ways. For example, organizations could increase intergroup
contact by holding regular events or workplace gatherings,
training sessions, or ad-hoc initiatives in which diverse employees
are likely to interact in meaningful ways.
Enacting one or more of these individual level interventions
should, on average, help employees to become more aware of and
motivated to reduce bias. However, given that bias operates as a
7 Although most of these studies about countering stereotypes focus on reducing
people’s reliance on stereotypes of outgroups, stereotypes are widely shared and
culturally produced (e.g., stereotypes about women are held by both men and
women; Banaji & Greenwald, 2016; Correll, 2017; Eberhardt, 2019; Reuben,
Sapienza, & Zingales, 2014; Ridgeway, 2011). Interventions for countering
stereotypes should therefore be broadly relevant and effective in reducing the
use of group-based stereotypes more generally, even when those stereotypes are
about ingroups (see Kawakami, Dovidio, & Van Kamp, 2007 for example).
N.M. Stephens, L.A. Rivera and S.S.M. Townsend Research in Organizational Behavior 40 (2020) 100137
5
cycle, changing the individual level on its own often fails to
produce long term changes in attitudes and behavior. Although
employees who benefit from individual level interventions should
become more receptive to changes in organizational policies and
practices aimed at reducing bias, good intentions are not enough.
Individual level interventions often fail because, as part of the
workplace bias cycle, individuals’ attitudes and behavior are
continually shaped by the biases that are embedded in policies and
practices at an organizational level (e.g., Kalev, 2009; Pedulla &
Thébaud, 2015; Stamarski & Son Hing, 2015). Our bias cycle theory
therefore suggests that successfully reducing bias requires
intervening not only at the individual level, but also at the
organizational level.
Empirically supported organizational level interventions
Given the importance of also intervening at the organizational
level, in this section, we drew from research from sociology and
management to highlight some possible interventions that seek to
reduce bias in policies and practices. To identify the interventions
to include in our review, we first selected interventions that met
the following three criteria: (a) are organizationally relevant, (b)
have the stated goal of reducing bias, and (c) have some empirical
support for their effects. We then categorized these interventions
into four conceptually distinct, overarching categories: diversifying opportunity, increasing transparency, making evaluation more
systematic, and creating accountability.8 Although these five
interventions are not an exhaustive or comprehensive list of all
potential organizational level interventions, they represent some
of the more promising options for organizations to reduce bias at
this level.
Diversifying opportunity
The first category of interventions that can be used to reduce
bias at the organizational level of the bias cycle is aimed at
diversifying opportunity: adopting organizational policies and
practices that widen the pool of individuals considered for jobs,
work assignments, and sponsorship opportunities (e.g., Johnson,
Hekman, & Chan, 2016). Diversifying opportunity can reduce bias
by reducing the influence of managers’ biased personal preferences about whom to hire or work with.
In hiring, diversifying opportunity entails widening the
channels companies use to source talent. Many organizations rely
on recruitment channels (e.g., super-elite colleges and universities)
that are biased against groups that are underrepresented in their
context (e.g., Rivera, 2012a, 2015a, b). Organizations can reduce
such pipeline bias by recruiting talent from a wider and more
diverse array of sources, such as recruiting programs at Historically
Black Colleges and Universities (Dobbin et al., 2015).
After employees gain access to jobs, organizations can diversify
the opportunities available to underrepresented groups—and
reduce bias in the process—by developing formal systems to
equitably assign projects. Tracking assignments helps to ensure
that work assignments are distributed equitably, rather than based
on managers’ group-based stereotypes (Madden, 2012; Tulshyan,
2018). Formal systems should also be used to assign all employees
to a mentor or multiple mentors (Blau, Currie, Croson, & Ginther,
2010; Dobbin et al., 2015; Kalev et al., 2006). Such a system can
distribute mentorship and/or sponsorship more equitably by
preventing potential mentors and mentees from falling prey to the
biases that would otherwise inform this process (e.g., Ibarra,
Carter, & Silva, 2010).
Increasing transparency
The second category of interventions that can be used to reduce
bias at the organizational level of the bias cycle involves increasing
transparency. Increasing transparency in polices and practices can
help to reduce bias by more equitably providing access to
information so that all employees, rather than just those from
high status groups, are aware of opportunities and the “rules of the
game” for how to succeed.
In the domain of hiring, firms can increase transparency by
widely circulating job postings and by making the requirements of
those jobs clear. Formal job posting systems, as opposed to filling
roles through referrals and word-of-mouth, decrease bias by more
equitably sharing the information needed to gain access to jobs
(Baron & Bielby,1980; Beaman, Keleher, & Magruder, 2018; DiPrete,
1989; Hodson & Kaufman, 1982; McDonald, Lin, & Ao, 2009;
Pedulla & Pager, 2019; Reskin, 2000).
After entering an organization, transparency about promotions
is critical for reducing bias in access to advancement opportunities
(e.g., Garcia-Izquierdo, Moscoso, & Ramos-Villagrasa, 2012).
Transparency can help to more equitably distribute information
so that a broader range of employees gain access to the information
needed to access promotions (see Kalev et al., 2006 for discussion).
It is important to be transparent about the promotion process by
providing clear job ladders: a map of job levels within an
organization and the required pathways to achieve them. Another
key step to be transparent about the process is to inform all
employees when they are eligible to be promoted. This means that
organizations should avoid relying on employees’ self-nomination,
a process that is typically informed by gender and racial biases
(Bear, 2011; Bowles, Babcock, & McGinn, 2005; Leibbrandt & List,
2015). It is also critical to be transparent with employees by
sharing the clear and specific criteria on which promotions will be
based (Castilla, 2015).
Making evaluation more systematic
The third category of interventions that can be used to reduce
bias at the organizational level of the bias cycle involves making
evaluation more systematic. Making evaluation systematic has two
components that we discuss in the sections below. We first discuss
how to de-bias evaluative tools and then how to de-bias evaluative
procedures. Making these evaluations more systematic works to
reduce bias by reducing the influence of group-based stereotypes.
De-biasing evaluative tools
Organizations can reduce bias in hiring decisions by replacing
open-ended interviews with structured interviews. Indeed,
structured interviews are far less prone to bias than unstructured
interviews (Huffcutt, 2011).9 They reduce bias, in part, because
they prevent evaluators from relying on group-based stereotypes,
as well as “gut” feelings of “fit,” “chemistry” and “spark” (Rivera,
2012b, 2015a). One example of a structured interview is a
behavioral interview, in which evaluators ask job candidates
questions about how they handled themselves in specific
situations that are relevant to performance on the job (e.g., in a
8 Although some of these interventions could be used at an individual level (e.g.,
increasing accountability with goal setting), we categorize these interventions as
“organizational level” because most of the research that supports them focuses on
reducing bias in policies and practices.
9 While using structured interviews is associated with reducing bias in hiring,
organizations need to think carefully about whether the questions developed are
themselves biased (for examples, see Dittmann et al., 2020; Rivera, 2015b).
N.M. Stephens, L.A. Rivera and S.S.M. Townsend Research in Organizational Behavior 40 (2020) 100137
6
client service role, “Tell me about a time when you had a difficult
client and how you managed the situation.”).
Reducing bias in evaluative tools is also important for
performance evaluations. The design of a performance appraisal
method can make group-based stereotypes more or less salient.
Stereotypes are more salient when individuals are asked to make
subjective, category-dependent, relative evaluations (e.g., “Is this
person tall?”) than when they are asked to make absolute
evaluations (e.g., “Please list this person’s height in inches; Biernat
& Vescio, 2002). Consequently, designing performance prompts in
a way that elicits objective rather than subjective information can
help reduce bias. For example, rather than asking if someone is a
“rainmaker,” ask them how many clients or how much revenue
they brought in.
De-biasing evaluative procedures
In addition to de-biasing evaluative tools, it is also necessary to
de-bias the evaluative procedures. One key step is to make the
criteria for evaluation more systematic. To do so, it is critical for
organizations to specify—and to also ask employees to commit to—a
set of evaluative criteria in advance (Uhlmann&Cohen, 2005). These
systematic criteria should be used in resume screening, interviewing, performance evaluations, compensation setting, and promotion
reviews. Without these criteria, evaluators frequently cherry pick
criteria after the fact to justify their preferred employees (Biernat &
Vescio, 2002; see also, Elvira & Graham, 2002).10
Reducing bias in evaluative procedures also requires making
the criteria for evaluation more equitable. To do so, it is critical to
ensure that the criteria are based on the skills needed to succeed in
an organization, rather than the characteristics common among
high status social groups. Indeed, organizations often rely on
criteria that reflect “masculine defaults” that are biased against
members of underrepresented groups (e.g., Acker, 1990; Bem,
1993; Cheryan & Markus, 2020; Cox, 1994; Dittmann, Stephens, &
Townsend, 2020; Gilligan, 1993; Ridgeway, 2011). For example,
technology companies frequently evaluate employees based on
stereotypically masculine defaults (e.g., advanced math skills,
independent work, beliefs about innate brilliance) that can repel
women from jobs in technology or computer science (see Cheryan
& Markus, 2020).
Increasing accountability
The fourth category of interventions that can be used to reduce
bias at the organizational level of the bias cycle involves increasing
accountability: adopting organizational policies and practices that
require people to report, explain, and/or justify their behavior to
others. Accountability can help to reduce bias by increasing
people’s awareness of how others will view them, and therefore
encouraging them to engage in more thoughtful, careful, and less
biased behavior (e.g., Kruglanski & Freund, 1983).
One key way that organizations can increase accountability is
by creating positions or entities that are responsible for overseeing
initiatives intended to increase workplace equity (e.g., an equity
committee; Kalev et al., 2006). Creating these roles establishes
authority and oversight to enforce adherence to policies intended
to reduce bias. For example, an equity committee could hold
employees accountable for making fair and equitable promotion
decisions (Tetlock & Kim, 1987; Tetlock, 1983; Tetlock, 1985). As
part of this process, employees could be informed that the
committee will review their decisions for fairness, and that they
will also be asked to explain the rationale for their decisions (e.g.,
Castilla, 2015). Doing so encourages employees to be more
thoughtful about the equity of their decisions (Lerner & Tetlock,
1999).
Another way that organizations can increase accountability is
by setting specific and clear goals or targets for what the
organization hopes to achieve with respect to reducing bias. For
example, they might specify that the organization’s goal is to
increase the percentage of Black employees from 2 to 4% over the
next 2 years. For those making decisions about whom to hire,
having these goals should reduce bias by leading them to make
more careful decisions and also encouraging them to follow
through on their desires or intentions (e.g., a commitment device;
Gollwitzer & Sheeran, 2006; Kruglanski & Freund, 1983; Milkman,
Beshears, Choi, Laibson, & Madrian, 2011; Rogers, Milkman, John, &
Norton, 2015).
Summary
In this section, we provided an overview of the organizational
level interventions to reduce bias that have the most empirical
supportinthe sociologyandmanagementliterature. Enacting oneor
more of these organizational level interventions should, on average,
helpemployees toengage inless biasedandmoreequitable behavior.
However, given that workplace bias operates as a cycle, changing the
organizationallevel alone is unlikelytoproducelongterm changes in
attitudes and behavior. Organizational level interventions often fail
because,aspartoftheworkplacebias cycle, individuals often actively
resist these organizational level changes and refuse to adopt them
(e.g.,Dobbinet al.,2015).Inthenext section, emphasizing the critical
importance of multilevel interventions, we suggest general principles to determine how to begin and how to pair interventions across
levels.
Principles for designing effective multilevel interventions
Before beginning any intervention effort, it is important to first
identify the domain in which intervention is needed most.
Although our workplace bias cycle theory does not speak directly
to this decision, the selection of domain should be based on an
analysis of where bias and its resulting group-based disparities are
most pronounced in the organization (Luca & Bazerman, 2020;
Wullert, Gilmartin, & Simard, 2019). For example, if the largest
group-based disparities emerge at the point of hiring, then one’s
efforts to reduce bias should be focused on intervening in the
domain of hiring (e.g., resume review, interview process). If, on the
other hand, group-based disparities do not emerge until the point
of promotion to managerial positions, then interventions should be
focused on reducing bias in the domain of promotion (e.g.,
mentoring and developing talent, criteria for promotion).
Even after identifying the domain of focus, organizations must
determine how to begin and choose from a wide range of
potentially effective interventions at individual and organizational
levels. How should an organization begin? And, which interventions and cross-level pairs of interventions should an organization
choose? Our workplace bias cycle theory provides general
principles for determining how to begin and how to pair
interventions across levels.
How to begin
Our multilevel approach to reducing bias clearly suggests that
an organization should begin by doing a multilevel assessment of
10 When it comes to standardizing evaluation, some scholars advocate complete
formalization in which criteria and scoring rubrics are fixed and managerial
discretion is eliminated entirely (e.g., Reskin, 2000). Others have found that
complete standardization can elicit resistance to the organization’s efforts (Dobbin
et al., 2015; Jencks, 1998; Steele & Aronson,1998; Walton, Spencer, & Erman, 2013).
What is clear is that evaluative criteria are needed, and that it is also important for
managers to buy into these criteria (Uhlmann & Cohen, 2005).
N.M. Stephens, L.A. Rivera and S.S.M. Townsend Research in Organizational Behavior 40 (2020) 100137
7
the organization’s current and previous efforts to reduce bias.11
Focusing on the domain in which intervention is needed most (e.g.,
hiring), one should ask what kinds of bias reduction efforts are in
place currently (or have been implemented previously) at both
individual and organizational levels. Specifically, have there been
interventions at one level, but not the other level? The bias cycle
theory suggests that bias reduction interventions at one level will
not have the intended effects without also changing the other level.
Thus, organizations may benefit from implementing new interventions at the level where interventions have been absent, while
continuing their efforts at the other level.
For example, if an organization has previously trained
individuals to motivate them to reduce their bias in hiring
decisions (e.g., a diversity training), but neglected the organizational level, then these individual level efforts on their own are
unlikely to realize their intended benefits. In this case, employees
may be motivated to make less biased decisions about whom to
hire or promote, but their organization’s hiring practices will still
likely produce biased hiring decisions. Thus, to reduce bias in
hiring, it is important to add new interventions at the organizational level (e.g., providing equitable and systematic criteria),
while also continuing to build momentum at the individual level
by introducing additional interventions (e.g., leveraging social
influence or encouraging perspective taking; see Correll, 2017).
How to pair interventions across levels
After ensuring that an organization has addressed both levels,
there are still a multitude of effective interventions at both levels
that one might enact. Which specific interventions will be most
effective to pair across levels? Our bias cycle theory suggests that it
is importantto pair interventions across both levels of the cycle in a
way that capitalizes on their potential to reinforce and enable the
benefits of each other. Since the two levels reinforce each other, we
theorize that pairing interventions in a synergistic way can harness
the cycle to reduce bias throughout the organization. We use the
term pairing to emphasize the importance of simultaneously
intervening at both the individual and organizational levels of the
bias cycle. For the sake of simplicity, in our discussion below, we
focus on how to pair a single intervention at one level with a single
intervention at the other level. However, organizations may also
opt to use multiple interventions at a given level to pair with a
single intervention at the other level.
For example, diversifying the candidate pool at the organizational level could be paired with an intergroup contact intervention at the individual level. An intergroup contact intervention at
the individual level could enable or amplify the benefits of the new
policy to diversify the candidate pool. Specifically, by decreasing
prejudice against potential new hires from diverse backgrounds,
this intergroup contact intervention could encourage employees to
support the effort to diversify the candidate pool and also
encourage them to welcome the diverse hires into the organization. In turn, when employees take part in the new policy to
diversify the candidate pool, they should have more intergroup
contact as a result of this policy, further amplifying the benefits of
the intergroup contact intervention.
As another example, an intervention to counter gender
stereotypes at an individual level could be paired with an
organizational level intervention to reduce gender bias in the
criteria for promotions. Countering gender stereotypes should lead
managers to question the assumption that women are less
qualified to be leaders, and potentially increase their support for
women colleagues. Such changes in attitudes and behavior should
also increase managers’ motivation to make less biased promotion
decisions. This individual level change can thereby facilitate and
enable the benefits of the new policy to make and use promotion
criteria that are more egalitarian and less gendered. In turn, by
developing and employing the new, more equitable criteria,
employees should avoid relying on stereotypes in their decisions,
which should help to further challenge their stereotypes.
General discussion
In the United States and across the globe, the 2020 COVID-19
pandemic has served to widen existing racial and economic
inequalities (Pappas, 2020; Thorbecke & Mitropoulos, 2020). These
inequalities have been accompanied by rising support for
collective action and movements (e.g., Black Lives Matter) to
improve racial and economic justice (Cohn & Quealy, 2020). These
movements have increased pressure on organizations to take
action to improve diversity, equity, and inclusion. Despite
organizations’ increased interest in improving their diversity,
equity, and inclusion, bias is one key obstacle that still stands in the
way of their efforts.
Extending prior theory and research, our workplace bias cycle
theory provides several important theoretical contributions. First,
it advances psychological and sociological understandings of the
nature of bias. Existing theories of workplace bias typically focus
on either the individual or organizational level in isolation. By
focusing on a single level, they limit our understanding of the
nature of bias and how it operates. Building on existing theories,
our theory enhances our understanding of the sources of bias and
how it operates in and through organizational systems. Specifically, our bias cycle theory clarifies that bias is never exclusively
individual or organizational in nature. Instead, it is always
dynamically produced through the reciprocal influences of both
biased individual attitudes and behaviors, as well as biased
organizational policies and practices.
Second, by conceptualizing workplace bias as a self-reinforcing,
multilevel cycle, our theory explains why single-level interventions are likely to fail (e.g., Kalev et al., 2006; Kidder, Lankau,
Chrobot-Mason, Mollica, & Friedman, 2004; Naff & Kellough, 2003;
Rynes & Rosen, 1995; Sidanius, Devereux, & Pratto, 1992). Indeed,
prior psychological and sociological theories of bias have inspired
single-level interventions (e.g., diversity training) that are insufficient to successfully reduce bias on their own. However, our bias
cycle theory reveals why interrupting workplace bias at a single
level is not enough: individual behavior is not only shaped by
individuals’ attitudes, but also by organizational level policies and
practices. Thus, a single-level intervention is unlikely to be enough
to interrupt the full cycle through which workplace bias is
reproduced.
Building on this theoretical insight about why single-level
approaches fail, our third contribution is to propose that effectively
reducing workplace bias requires multilevel interventions that
interrupt the workplace bias cycle at both the individual level (e.g.,
changing attitudes and behaviors) and the organizational level
(e.g., redesigning policies and practices). This contribution extends
prior work that points to the benefits of multiple interventions
(e.g., multiple training sessions over time or more than one type of
intervention delivered simultaneously; Bendick et al., 2001;
Bezrukova et al., 2016; Carter et al., 2006; Castillo, Brossart, Reyes,
Conoley, & Phoummarath, 2007; Dobbin & Kalev, 2016; Earley,
1987). Our bias cycle theory clarifies that more interventions may
not always be better than fewer interventions. Instead, to harness
the bias cycle to produce change, successfully reducing bias in an
11 Support from top management might be considered a necessary precondition
before enacting interventions (e.g., Dobbin et al., 2015). In other words, it will be
challenging—if not impossible—to implement bias reduction interventions at the
individual and organizational levels without support from top management.
N.M. Stephens, L.A. Rivera and S.S.M. Townsend Research in Organizational Behavior 40 (2020) 100137
8
organization requires multilevel interventions that target both
individual and organizational levels.
Fourth, we used our bias cycle theory to formulate general
principles for designing effective, multilevel interventions. Based on
understanding bias as a multilevel cycle, we began to answer the
questions of “how to begin” and “how to pair interventions” across
levels. We suggested the importance of assessing an organization’s
prior and current efforts to reduce bias to ensure that both levels of
biashavebeenaddressed.Wealsosuggested theprincipleof creating
pairings of synergistic interventions that have the most potential to
enable and amplify the effects of each other across levels.
Limitations and future directions
One limitationofour reviewis thatwe did notinclude all possible
interventions at an individual and organizational level. We only
included interventions that have some empirical evidence, are
conceptually distinct, are organizationally relevant, and have the
stated goal of reducing bias. For example, there were many
interventions we did not include based on the requirement that
the research have the stated goal of reducing bias. Accordingly, our
review did not include research on fostering belonging or inclusion
(Cheryan, Plaut, Davies, & Steele, 2009; Friedman & Holtom, 2002;
Stephens, Fryberg et al., 2012; Stephens, Townsend, Markus, &
Phillips, 2012; Walton & Cohen, 2011), creating psychological safety
(Bradley, Postlethwaite, Klotz, Hamdani, & Brown, 2012; Edmondson, 1999; Nembhard & Edmondson, 2006), or leveraging the
strengths of diversity in groups and teams (Chatman, Greer,
Sherman, & Doerr, 2019; Goncalo, Chatman, Duguid, & Kennedy,
2015; Homan & Greer, 2013). Although we did not review these
research areas, we acknowledge thatthey are likely to be effective in
reducing bias because they foster psychological experiences (e.g.,
inclusion) that tend to go hand-in-hand with bias reduction.
Moreover, because our review focused on reducing bias at the
individual and the organizational level, another limitation of our
article is that we did not discuss additional interventions that can
be used to reduce bias in groups and teams.12 Indeed, to the extent
that groups and teams have their own policies or practices that
diverge from the organizational level, bias reduction interventions
could also be delivered to groups and teams. For example, to reduce
group-based disparities in who speaks in team meetings, a
manager could enact a turn-taking policy, such that all team
members are expected to share their perspectives. A manager
could also encourage team members to amplify the voices of other
team members whose voices might otherwise be overlooked or
unheard (Bain, Kreps, Meikle, & Tenney, 2021).
Despite these limitations, our bias cycle theory provides novel
theoretical insights about how bias operates in organizations and
how to reduce it. These insights point to several critical avenues for
future research. First, moving beyond the typical single-level focus
of most previous research, future work should do more to examine
the reciprocal influences of bias across both levels of the cycle,
specifically, how the expression of bias at one level shapes the
other level and vice versa. That is, research should examine how
bias in individuals’ hearts and minds impacts support for
organizational level policies and practices, as well as how bias
in policies and practices can affect individuals’ hearts and minds.
Second, our theory suggests that simultaneous interventions at
multiple levels will more effectively reduce bias than the same
number of simultaneous interventions at a single level. Future
research should test this claim in the field by comparing the
effectiveness of multilevel and single-level intervention efforts in
organizations over time. Third, our theory suggests that interventions should be paired in a synergistic way such that
interventions at one level amplify the benefits of interventions
at the other level. Future research should examine which specific
pairings of interventions most effectively amplify the benefits of
each other. To do so, research should more fully and concretely
identify how interventions at one level amplify and enable the
effects of the other. For example, at an organizational level, how
does an intervention that makes evaluation more systematic alter
employees’ interactions with each other, and, in turn, their hearts
and minds? How might the initiation of this set of processes
amplify the benefits of an individual level interventions such as
perspective-taking or intergroup contact?
Conclusion: reducing bias is not enough
In this article, we introduced a novel workplace bias cycle
theory that advances our understanding of how it operates in
organizations. Because workplace bias is necessarily multilevel,
interventions to reduce bias should also be multilevel—that is, they
should target both individual and organizational levels. We
therefore brought together and reviewed empirically supported
interventions to reduce bias in individuals’ hearts and minds and in
organizations’ policies and practices. By conceptualizing workplace bias as a mutually reinforcing cycle, our bias cycle theory also
provides principles about how to design more effective, multilevel
interventions to reduce bias.
Although our theory provides a clear path for better understanding the nature of bias and how to reduce it, it is important to
recognize that reducing bias is only the first step in a two-step
process of creating high performing, diverse, equitable, and
inclusive organizations. Indeed, to increase diversity, organizations
must first reduce bias throughout all levels of the organization.
From a public-facing view, achieving this diversity might give
organizations “diversity credentials.” However, these organizations and their employees will not fully benefit from this diversity
without careful and systematic efforts to foster inclusion: taking
steps to ensure that all employees from diverse backgrounds are
fully engaged, empowered, and respected, and feel part of the
organizational community.
Conflict of interest
None.
Acknowledgements
We thank Jordi Kleiner, Hazel Rose Markus, and Zoe SchwingelSauer for their comments on prior versions of this manuscript.
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