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1. THINKING BEYOND THE DEFAULT USER: THE IMPACT OF GENDER AND STEREOTYPES ON DESIGNERS’ INTERPRETATION OF USERS AND THEIR NEEDS

   Schauer, A.M.K.; Nunn, M.; Schaufel, H.; Fu, K. (August 2023, ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC/CIE2023)

   Throughout the mechanical design process, designers, the majority of whom are men, often fail to consider the needs of women, resulting in consequences ranging from inconvenience to increase risk of death or serious injury. Although these biases are well-studied in other fields of research, the mechanical design field lacks formal investigation into this phenomenon. In this study, undergraduate engineering students (n = 151) took a survey in which they read a Persona describing a student makerspace employee and a Walkthrough describing their interaction with the makerspace while completing a project. During the Walkthrough, the user encountered various obstacles, or Pain Points. Participants were asked to recall and evaluate the Pain Points that the user encountered, then evaluated their perceptions of the makerspace and user. Six different experimental conditions were used to investigate the impact of gender-stereotyped tasks and the gender of a user on designers’ interpretation of them and their needs. In addition to finding that the gender of a user impacted the way a task environment was perceived, results confirmed the presence of androcentrism, or “default man” assumptions, in the way designers view end users of unknown gender. Future work will explore methodologies of overcoming this bias so that designers are able to consider the diverse needs of a range of users. 

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2. Finding Meaning in Makerspaces: Exploring How Gender Influences Makerspace Definition Among First-Year Engineering Students

   Bushra, J.; Budinoff, H.D.; Shivers-McNair, A.; Berger, E. (June 2024, ASEE annual conference exposition)

   Makerspaces, intended for open and collaborative learning, often struggle to attract a diverse group of users, particularly concerning gender diversity. These issues include makerspaces becoming associated primarily with white male students, gendered connotations of machines and materials, and women’s perceived lack of self-efficacy in using makerspace tools. As a result, women may view makerspaces as unwelcoming, and societal stereotypes can affect their engagement in these spaces. Efforts to create more inclusive makerspaces are essential to fully realize the potential of makerspaces, encourage and boost confidence in marginalized groups to pursue careers in different engineering areas, and promote a diverse and collaborative maker culture. Moreover, defining makerspaces is challenging due to conflicting perceptions, the uniqueness of spaces, and the abstract elements in these environments, revealing a gap between academic definitions and the diverse voices of people interested in utilizing makerspaces. Our goal is to see if there are differences in the fundamental academic makerspace definition and makerspace definition by different genders, providing insights into how inclusive our makerspace is. We focus on gender because our interviewees focused more on gender than other identity markers in our conversations, but we also report additional demographic data that likely impacted participants’ experiences, namely, their racial and ethnic identities. Our corpus is drawn from semi-structured interviews with students enrolled in an introductory first-year engineering course. Out of 28 students interviewed, 10 identified as women, 16 as men, one as both women and questioning or unsure, and one as women and nonbinary and transgender. In terms of racial/ethnic identifications, nine participants identified as White or Caucasian; six identified as Latinx or Hispanic; five identified as Latinx or Hispanic, White or Caucasian; three identified as Black or African American; two identified as Asian, Desi, or Asian American; one identified as Latinx or Hispanic, Native American or Alaska Native; one identified as Southwest Asian, Middle Eastern, or North African, White or Caucasian; and one identified as Native African. In this ongoing study, from interview transcripts, we extracted participant responses to questions regarding their definitions of and impressions of makerspaces to identify commonalities and differences. Specifically, we use natural language processing techniques to extract word frequency and centrality and synthesize commonalities into a shared definition of a makerspace. We also separated responses from participants by gender identities to evaluate how definitions varied with gender. These emergent definitions are compared with commonly accepted definitions derived from research papers. Additionally, we conduct a complementary discourse analysis of students’ definitions and impressions of makerspaces, qualitatively examining how diverse students characterize ways of being and doing in the makerspace. 

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3. Gender Prototypes Hinder Bystander Intervention in Women’s Sexual Harassment

   https://doi.org/10.1177/01461672231203290  

   Schachtman, Rebecca; Gallegos, Jonathan; Kaiser, Cheryl_R (October 2023, Personality and Social Psychology Bulletin)

   Bystander intervention is a powerful response to sexual harassment that reduces victims’ burden to respond. However, gender prototypes depicting sexual harassment victims as prototypical women (i.e., stereotypically feminine) may hinder intervention when harassment targets women who deviate from this prototype. Across four preregistered experiments (N= 1,270 Americans), we test whether bystanders intervene less readily in nonprototypical (vs. prototypical) women’s sexual harassment. Participants observed a man manager ask a series of increasingly sexually harassing job interview questions toward either a gender prototypical or nonprototypical woman by traits (Studies 1–3) or gender identity (Study 4). Participants were instructed to intervene to stop the interview if/when they judged the questions as inappropriate. A meta-analysis revealed participants had a greater threshold for intervention when harassment targeted a nonprototypical (vs. prototypical) woman—a small but meaningful effect. Efforts to foster bystander intervention in sexual harassment would benefit by recognizing this neglect of nonprototypical women. 

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4. On the Importance of User Backgrounds and Impressions: Lessons Learned from Interactive AI Applications

   https://doi.org/10.1145/3531066  

   Nourani, Mahsan; Roy, Chiradeep; Block, Jeremy E.; Honeycutt, Donald R.; Rahman, Tahrima; Ragan, Eric D.; Gogate, Vibhav (April 2022, ACM Transactions on Interactive Intelligent Systems)

   While EXplainable Artificial Intelligence (XAI) approaches aim to improve human-AI collaborative decision-making by improving model transparency and mental model formations, experiential factors associated with human users can cause challenges in ways system designers do not anticipate. In this paper, we first showcase a user study on how anchoring bias can potentially affect mental model formations when users initially interact with an intelligent system and the role of explanations in addressing this bias. Using a video activity recognition tool in cooking domain, we asked participants to verify whether a set of kitchen policies are being followed, with each policy focusing on a weakness or a strength. We controlled the order of the policies and the presence of explanations to test our hypotheses. Our main finding shows that those who observed system strengths early-on were more prone to automation bias and made significantly more errors due to positive first impressions of the system, while they built a more accurate mental model of the system competencies. On the other hand, those who encountered weaknesses earlier made significantly fewer errors since they tended to rely more on themselves, while they also underestimated model competencies due to having a more negative first impression of the model. Motivated by these findings and similar existing work, we formalize and present a conceptual model of user’s past experiences that examine the relations between user’s backgrounds, experiences, and human factors in XAI systems based on usage time. Our work presents strong findings and implications, aiming to raise the awareness of AI designers towards biases associated with user impressions and backgrounds. 

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5. Recognition of Subtle Bias Tempers Explicit Gender Stereotyping Among STEM Students

   Slade Morris, D.; Burley, L C.; Sekaquaptewa, D.; & Meadows, L. A. (January 2022, Zone 1 Conference of the American Society for Engineering Education)

   The overarching goal of this research project is to provide a novel contribution to perceived bias research by testing the hypothesis that mere exposure to instances of subtle gender bias in STEM settings can have important effects on observers, depending on whether they recognize such events as gender bias or do not see it as bias. The goal of the first of five experiments was to assess how witnessing subtle gender bias events influences explicit stereotype activation among people who recognize the events as gender stereotyping as well as those who do not. We utilized video materials that were developed and tested in our previous NSF research that show a group of four engineering students, 2 women and 2 men, working together on an engineering design task. There are two versions of the video: one in which the students engaged in subtle gender bias (bias version), and one in which the students engaged in neutral interactions (control version). Over 400 participants were recruited from a large midwestern research university from computer science and engineering majors in which 30% or fewer majors are women. The survey included assessments of perceptions of gender stereotyping in the video, general stereotype endorsement and STEM stereotype endorsement, and three individual difference measures (gender-based rejection sensitivity, sexism sensitivity and negative emotionality) used as covariates in analyses. We found that participants who saw the bias video reported greater explicit stereotyping when they failed to recognize gender bias in the video. When they did recognize bias, they reported explicit stereotyping at levels similar to those in the control condition. This pattern suggests that exposure to subtle gender bias events may have activated gender stereotypes, but when participants recognized the events as gender bias, they tempered their explicit stereotyping. 

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