Anti-Racism Grant Winners Announced
Earlier this summer, the SIOP Foundation and SIOP announced the new Anti-Racism Grant, a step toward addressing racism in work contexts using I-O science and practice.
The call, aimed at enlarging our understanding of racism in the workplace, its causes, and its reduction, brought in 35 submissions. Five submissions received funding:
“Workplace racism is multifaceted and has persisted far too long,” said SIOP Foundation President Milt Hakel. “Each of these projects takes solid and needed steps toward understanding and improving the prospects of equal employment opportunity for all. I’m proud of the speed with which SIOP and the Foundation were able to create and award this set of small grants.”
I-O psychologists conduct and apply research that improves the well-being and performance of people and the organizations that employ them. Because the presence of overt and institutionalized racial discrimination constitutes direct and indirect threats to the well-being and performance of employees and employers, anti-racism in the workplace is a topic that I-O psychology as a field must address. More information about SIOP’s Stand Against Racism can be found online.
“This is a critical and timely topic for the workplace and society in general,” said Jeffrey Cucina, Awards Committee chair. “We had an amazing and rapid response from SIOP members. The SIOP Foundation was able to obtain $50,000 in donations from SIOP members and a total of 35 teams of SIOP members submitted proposals. In record-breaking time, a subcommittee of 22 volunteers conducted two rounds of reviews and ratings and decided the five winners.”
“The committee was impressed with the submissions that were received,” said Subcommittee Chair Sarah Walker. “Each of the awarded submissions provide a useful perspective for understanding and combating racial bias. From providing resources to equip organizations with best practices for responding to mega-threats, understanding how various organizational practices may result biased decision making, to understanding how individuals perceive and cope with bias. The funded work takes steps toward our ability to develop anti-racist practices and policies within organizations.”
The winning submissions:
Performative Gesture or Genuinely Supportive: The Impact of Workplace Responses to the Racial Injustice Movement on Employees
Lauren Collier-Spruel & Dr. Ann Marie Ryan
In the wake of racial justice protests and calls from individuals in the US and internationally to address police brutality and systemic injustice, many major corporations have released statements affirming or reaffirming their commitment to diversity, inclusion, and anti-racism. Although some statements were well received, others were considered to be opportunistic and disingenuous. Based on Leslie’s (2019) Theory of Unintended Consequences of Diversity Initiatives, the aims of this study are to examine organizational responses to racial injustice to determine: (a) what statements from actual organizations comprised; (b) how these statements as well as those from direct supervisors and coworkers, through signals they send, impact psychological and work-related outcomes for employees, and particularly for Black employees; and (c) which elements of organizational statements (e.g., declared actions, tone) are related to positive and negative perceptions and emotional reactions of employees, particularly Black employees. To address these aims, we will conduct computerized textual analyses of a compiled database of organizational public statements regarding anti-racism from the period following the death of George Floyd, conduct a survey of Black and other employee experiences surrounding communications from their organization, and conduct an experiment manipulating communication elements to evaluate their effects. Through these three studies, we hope to advance the conversation regarding how organizational anti-racism efforts are best articulated and undertaken.
Organizational Anti-Racism Initiatives: Advancing Scholarship and Guiding Practice on Effectiveness
Dr. Enrica Ruggs, Dr. Alison Vania Hall (Birch), Dr. Derek R. Avery, Dr. Benjamin E. Baran, & Christopher W. Everett
We propose a mixed-method study and an evidence-based practitioner resource of racism response initiatives and related organizational practices. Our project provides immediate and long-term contributions to scholarship and practice. The research will include interviews with senior-level human resource and diversity officers to determine organizations’ racism response practices and employee surveys within these organizations to examine employees’ awareness, appraisal, and responses to these practices. Results will allow us to (a) develop a taxonomy of racism response practices and a scientific evaluation of those practices and (b) answer research questions regarding the use of those practices. The practice-oriented element of our work will be a fully developed website—a free, evidence-based, platform devoted to ending racism at work. We own www.endingracismatwork.org and will begin development immediately upon funding. The site will announce the project, provide updates on organizational anti-racism initiatives, solicit additional participants, and report our initial research findings (the taxonomy) and guidance for practitioners. Longer term, the site will foster collaboration, publication of white papers, evaluation of emerging practices to reduce racism at work, and a database of interested organizations and leaders to facilitate data collection. Our team includes three academic researchers with expertise on racism and workplace discrimination, and organizational partners—the management consulting firm Indigo Anchor, which will provide pro-bono assistance with organizational access for data collection, project publicity via The Indigo Podcast, and creation and curation of the online resource.
Algorithmic Racial Bias in Automated Video Interviews
Louis Hickman, Dr. Louis Tay, Dr. Sang Eun Woo, & Sidney D'Mello
Artificial intelligence, and specifically machine learning (ML) algorithms, are increasingly being used to assess job applicants due to hopes that they will improve selection decisions and reduce costs, but there are persistent concerns about discrimination and bias against legally protected groups. Within the selection context, automated video interviews (AVIs) use verbal behavior (what interviewees say), paraverbal behavior (how interviewees speak), and nonverbal behavior (what interviewees do) to assess interviewee characteristics. Concerningly, consumer advocacy groups and U.S. senators have argued that AVIs are biased against Black interviewees. Their primary concern is that ML algorithms for analyzing facial expressions (i.e., nonverbal behavior) are less accurate for interviewees with darker skin tones. To address this concern, we propose to systematically investigate algorithmic racial bias by recruiting a targeted sample of Black undergraduate students (N=500) who will complete structured, asynchronous video interviews and be compared to existing data from a matched sample of White undergraduate students. We will also recruit and train four individuals to watch and rate the interview videos. Then, we will extract verbal, paraverbal, and nonverbal behaviors and train ML algorithms in four different ways to identify the specific sources and extent of racial bias in AVI assessments. Findings from our systematic investigation will inform policy, AVI vendors, and organizations as these virtual assessment techniques become increasingly popular. This proposed project will be a critical extension of our ongoing research efforts (funded by the National Science Foundation) for elucidating and mitigating algorithmic gender bias in AVIs.
Underestimating and Underreacting? Identifying and Addressing Empathy Gaps in Perceptions of Racial Microaggressions
Lindsay Y. Dhanani & Matthew L. LaPalme
Racial microaggressions are subtle yet harmful instances of racism that can have notable effects on the well-being of employees of color. However, despite their documented harm, microaggressions are often dismissed or minimized by White majority group members, thus perpetuating racial inequity in workplaces by allowing racial mistreatment to continue to flourish. We draw on the literature on empathetic forecasting to propose that the reason microaggressions are often ignored by majority group members is because they may fail to recognize the emotional harm of experiencing microaggressions, perhaps because of their seemingly minor and innocuous nature. We propose two studies that investigate this proposition by empirically examining if and to what extent White perceivers underestimate the psychological harm of racial microaggressions relative to people of color (which we refer to as the empathy gap). We also investigate whether underestimating the psychological harm of racial microaggressions decreases motivations to avoid engaging in microaggressions and willingness to intervene after witnessing a microaggression, both of which are critical for reducing microaggressions in the workplace. Finally, our second proposed study aims to develop and test an intervention designed to close the empathy gap by increasing empathic accuracy through emotional feedback. We further investigate whether this intervention can subsequently improve motivations to avoid engaging in microaggressions and bystander intervention responses. We aim to utilize our findings to develop training to combat subtle racial mistreatment at work.
Interpersonal Mistreatment, Perceived Discrimination, and Minority Identity Management: An Attribution Theory Perspective
Dr. Maria Kraimer, Dr. Lawrence Houston III, Jerry Liu, & Dr. Scott Seibert
Our study examines when interpersonal mistreatment experienced by a racial or ethnic minority employee is perceived as discrimination and why minority employees use different identity management tactics in response to mistreatment and perceived discrimination. Interpersonal mistreatment includes coworker incivility, ostracism, social undermining, and abusive supervision. Studies indicate that, compared to White employees, racial minorities experience more interpersonal mistreatment at work (McCord et al., 2018). Thus, it is important to understand how minority employees may react and respond to mistreatment. We consider four types of identity management tactics and two withdrawal behaviors (interaction avoidance and turnover intentions) as potential outcomes. We use attribution theory to identify potential moderators that explain our proposed relationships. First, we consider whether the minority employee attributes the mistreatment to the actor’s racism as a moderator that explains when interpersonal mistreatment will be perceived as discrimination. Second, we consider two moderators of the relationships between perceived discrimination and the outcomes: the employees’ attributions for the discrimination (the misbehaving actor and/or organizational environment is racist), and the employees’ diversity resources (diversity self-efficacy and work unit’s inclusion climate).We will test the model with employees from non-White racial and ethnic groups using a cross-level (between and within person) study design over 7 weeks. The results will have implications for understanding the sources of perceived discrimination and will help managers identify strategies for building an inclusive work group climate.