Robots, salad and anthropomorphism: UMSI research roundup
University of Michigan School of Information faculty and PhD students are creating and sharing knowledge that helps build a better world. Check out UMSI’s recent publications and learn more about their research interests and contributions to the field of information below.
“Not robots; Cyborgs — Furthering anti-ableist research in human-computer interaction.” Josh Guberman and Oliver Haimson
Publication: First Monday
This theoretical essay builds on existing literature to draw out the consequences of dehumanizing and disseminating autism discourses within the field of human-computer interaction (HCI). Focusing mainly on narratives in HCI that frame autistic people as or like machines, we explore how dominant constructions of autism in HCI work to normalize the field’s complicity in violent autism intervention paradigms, despite HCI researchers’ well-meaning intentions. We work towards developing crip-cyborgs as an alternative framework for understanding autistic people (as opposed to computers or robots) and suggest crip technoscience as a framework for research based on this alternative understanding. In doing so, we hope to enroll misguided but well-intentioned researchers in dismantling anti-autistic ableism, both in and beyond HCI.
“What Does It Mean to Anthropomorphize Robots? Food For Thought for HRI Research.” Samia Cornelius Bhatti and Lionel Peter Robert
Publication: Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
Anthropomorphism is a well-used but vague concept that demands further understanding and clarification to be effectively used in HRI research. Although most HRI research defines and uses anthropomorphism as a human-like attribution process, there is a lack of distinction between its deployment in design versus its manifestation in user response. Furthermore, researchers need to separate mindless from mindful anthropomorphism and find ways to theorize and measure each. Researchers also need to consider the dynamic and contextual nature of anthropomorphism to generate relevant findings for research as well as practice.
“Recommendations for design of a mobile application to support management of anxiety and depression among Black American women.” Terika McCall, Megan Threats, Malvika Pillai, Adnan Lakdawala, and Clinton S. Bolton
Publication: Frontiers in Digital Health
Black American women experience adverse health outcomes due to anxiety and depression. They face systemic barriers to accessing culturally appropriate mental health care leading to the underutilization of mental health services and resources. Mobile technology can be leveraged to increase access to culturally relevant resources, however, the specific needs and preferences that Black women feel are useful in an app to support management of anxiety and depression are rarely reflected in existing digital health tools. This study aims to assess what types of content, features, and important considerations should be included in the design of a mobile app tailored to support management of anxiety and depression among Black women. Focus groups were conducted with 20 women (mean age 36.6 years, SD 17.8 years), with 5 participants per group. Focus groups were led by a moderator, with notetaker present, using an interview guide to discuss topics, such as participants' attitudes and perceptions towards mental health and use of mental health services, and content, features, and concerns for design of a mobile app to support management of anxiety and depression. Descriptive qualitative content analysis was conducted. Recommendations for content were either informational (e.g., information to find a Black woman therapist) or inspirational (e.g., encouraging stories about overcoming adversity). Suggested features allow users to monitor their progress, practice healthy coping techniques, and connect with others. The importance of feeling “a sense of community” was emphasized. Transparency about who created and owns the app, and how users' data will be used and protected was recommended to establish trust. The findings from this study were consistent with previous literature which highlighted the need for educational, psychotherapy, and personal development components for mental health apps. There has been exponential growth in the digital mental health space due to the COVID-19 pandemic; however, a one-size-fits-all approach may lead to more options but continued disparity in receiving mental health care. Designing a mental health app for and with Black women may help to advance digital health equity by providing a tool that addresses their specific needs and preferences, and increase engagement.
How active-learning techniques can benefit students in computing courses.
Publication: Association for Computing Machinery
“What does salad have to do with racial justice? Promoting solidarity in the time of COVID-19.” Matthew Bui, Rachel Kuo, and Anne L. Washington
Publication: First Monday
In the late spring and summer of 2020, a local build-your-own salad restaurant chain, along with many mid-size corporations and local non-profit organizations, sent an e-mail statement in response to the death of George Floyd by the police. Different from corporations and large institutions, these businesses and organizations — what we collectively term the “salad group” within our sample — associated their product or service (ranging from salads to yoga mats to chocolate) with the project of creating a more local, socially just, and inclusive community. A thematic analysis of 81 crowdsourced organization e-mail messages identified the use of both internal and external appeals for action, although organizations chiefly focused on their internal actions. Our analysis revealed that these e-mails primarily offered solutions that invited or highlighted Black participation in their business enterprises. We describe such statements as salad solidarity, a genre of promotion that simultaneously appeals to consumers and social change. Indeed, the framing of possible external responses as tied to consumer choice — and internal responses as tied to a company’s growth and reach — do not directly address the structural problems that spurred these e-mail campaigns. Consequently, such corporate and digital messaging of social movements provokes questions about the commercialization of political movements and the value that language and digital tools hold in building solidarity. We conclude with observations on how e-mails, and digital platforms more broadly, can and cannot facilitate political change, from the analytical lens of racial capitalism. These findings have broader implications for the study of corporate-social responsibility, networked social movements, and mediated communication.
“Three Strikes and you are out!: The impacts of multiple human-robot trust violations and repairs on robot trustworthiness.” Connor Esterwood and Lionel P.Robert
Publication: Computers in Human Behavior
Robots like human co-workers can make mistakes violating a human’s trust in them. When mistakes happen, humans can see robots as less trustworthy which ultimately decreases their trust in them. Trust repair strategies can be employed to mitigate the negative impacts of these trust violations. Yet, it is not clear whether such strategies can fully repair trust nor how effective they are after repeated trust violations. To address these shortcomings, this study examined the impact of four distinct trust repair strategies: apologies, denials, explanations, and promises on overall trustworthiness and its sub-dimensions: ability, benevolence, and integrity after repeated trust violations. To accomplish this, a between-subjects experiment was conducted where participants worked with a robot co-worker to accomplish a task. The robot violated the participant’s trust and then provided a particular repair strategy. Results indicated that after repeated trust violations, none of the repair strategies ever fully repaired trustworthiness and two of its sub-dimensions: ability and integrity. In addition, after repeated interactions, apologies, explanations, and promises appeared to function similarly to one another, while denials were consistently the least effective at repairing trustworthiness and its sub-dimensions. In sum, this paper contributes to the literature on human–robot trust repair through both of these original findings.
“Why do volunteer content moderators quit? Burnout, conflict, and harmful behaviors.” Angela M. Schöpke-Gonzalez, Shubham Atreja, Han Na Shin, Najmin Ahmed, and Libby Hemphill
Publication: New Media & Society
Moderating content on social media can lead to severe psychological distress. However, little is known about the type, severity, and consequences of distress experienced by volunteer content moderators (VCMs), who do this work voluntarily. We present results from a survey that investigated why Facebook Group and subreddit VCMs quit, and whether reasons for quitting are correlated with psychological distress, demographics, and/or community characteristics. We found that VCMs are likely to experience psychological distress that stems from struggles with other moderators, moderation team leads’ harmful behaviors, and having too little available time, and these experiences of distress relate to their reasons for quitting. While substantial research has focused on making the task of detecting and assessing toxic content easier or less distressing for moderation workers, our study shows that social interventions for VCM workers, for example, to support them in navigating interpersonal conflict with other moderators, may be necessary.
“Virtual teams in a gig economy.” Teng Ye, Wei Ai, Yan Chen, Qiaozhu Mei, Jieping Ye, and Lingyu Zhang
Publication: Proceedings of the National Academy of Sciences of the United States of America
While the gig economy provides flexible jobs for millions of workers globally, a lack of organization identity and coworker bonds contributes to their low engagement and high attrition rates. To test the impact of virtual teams on worker productivity and retention, we conduct a field experiment with 27,790 drivers on a ride-sharing platform. We organize drivers into teams that are randomly assigned to receiving their team ranking, or individual ranking within their team, or individual performance information (control). We find that treated drivers work longer hours and generate significantly higher revenue. Furthermore, drivers in the team-ranking treatment continue to be more engaged 3 mo after the end of the experiment. A machine-learning analysis of 149 team contests in 86 cities suggests that social comparison, driver experience, and within-team similarity are the key predictors of the virtual team efficacy.
“Uptake of and Engagement With an Online Sexual Health Intervention (HOPE eIntervention) Among African American Young Adults: Mixed Methods Study.” Alicia Williamson, Andrea Barbarin, Bettina Campbell, Terrance Campbell, Susan Franzen, Thomas M Reischl, Marc Zimmerman, and Tiffany Christine Veinot
Publication: Journal of Medical Internet Research
Selected as one of the best consumer health informatics papers of the year in the Yearbook of Medical Informatics 2022.
Background: Regarding health technologies, African American young adults have low rates of uptake, ongoing usage, and engagement, which may widen sexual health inequalities.
Objective: We aimed to examine rates of uptake and ongoing usage, and factors influencing uptake, ongoing usage, and engagement for a consumer health informatics (CHI) intervention for HIV/sexually transmitted infection (STI) prevention among African American young adults, using the diffusion of innovation theory, trust-centered design framework, and O’Brien and Toms’ model of engagement.
Methods: This community-based participatory mixed methods study included surveys at four time points (n=315; 280 African American participants) among young adults aged 18 to 24 years involved in a blended offline/online HIV/STI prevention intervention (HIV Outreach, Prevention, and Education [HOPE] eIntervention), which was described as a “HOPE party.” Qualitative interviews were conducted with a subset of participants (n=19) after initial surveys and website server logs indicated low uptake and ongoing usage. A generalized linear mixed-effects model identified predictors of eIntervention uptake, server logs were summarized to describe use over time, and interview transcripts were coded and thematically analyzed to identify factors affecting uptake and engagement.
Results: Participants’ initial self-reported eIntervention uptake was low, but increased significantly over time, although uptake never reached expectations. The most frequent activity was visiting the website. Demographic factors and HOPE party social network characteristics were not significantly correlated with uptake, although participant education and party network gender homophily approached significance. According to interviews, one factor driving uptake was the desire to share HIV/STI prevention information with others. Survey and interview results showed that technology access, perceived time, and institutional and technological trust were necessary conditions for uptake. Interviews revealed that factors undermining uptake were insufficient promotion and awareness building, and the platform of the intervention, with social media being less appealing due to previous negative experiences concerning discussion of sexuality on social media. During the interaction with the eIntervention, interview data showed that factors driving initial engagement were audience-targeted website esthetics and appealing visuals. Ongoing usage was impeded by insufficiently frequent updates. Similarly, lack of novelty drove disengagement, although a social media contest for sharing intervention content resulted in some re-engagement.
Conclusions: To encourage uptake, CHI interventions for African American young adults can better leverage users’ desires to share information about HIV/STI prevention with others. Ensuring implementation through trusted organizations is also important, though vigorous promotion is needed. Visual appeal and targeted content foster engagement at first, but ongoing usage may require continual content changes. A thorough analysis of CHI intervention use can inform the development of future interventions to promote uptake and engagement. To guide future analyses, we present an expanded uptake and engagement model for CHI interventions targeting African American young adults based on our empirical results.
“Mobile phones at borders: logics of deterrence and survival in the Mediterranean Sea and Sonoran Desert.” Angela M. Schöpke-Gonzalez and Florian Schaub
Publication: Information, Communication & Society
Migrant death rates at international borders have risen sharply since the 1980s. Through archival research, we analyze the European Union’s and the United States’ international border infrastructures to illuminate how technological developments may have contributed to this spike in death rates. Based on an analysis of archival materials, we show how the mobile phone has emerged as an inadvertent identification technology at two border sites – the Mediterranean Sea and the Sonoran Desert – and how this technology supports survival in increasingly dangerous border-crossing experiences while also leading to death, detention, and deportation. We find that mobile phones have become identification technologies central to both migrants’ survival and border infrastructures’ attempts to deter cross-border mobility with profound consequences for human life and agency. We conclude with suggestions for future work to investigate reshaping border infrastructures in ways that do not rely on the galvanizing power of false and dangerous narratives of a symbolic Other.
“Modeling Information Change in Science Communication with Semantically Matched Paraphrases.” Dustin Wright, Jiaxin Pei, David Jurgens, and Isabelle Augenstein
Publication: Association for Computational Linguistics
Whether the media faithfully communicate scientific information has long been a core issue to the science community. Automatically identifying paraphrased scientific findings could enable large-scale tracking and analysis of information changes in the science communication process, but this requires systems to understand the similarity between scientific information across multiple domains. To this end, we present the SCIENTIFIC PARAPHRASE AND INFORMATION CHANGE DATASET (SPICED), the first paraphrase dataset of scientific findings annotated for degree of information change. SPICED contains 6,000 scientific finding pairs extracted from news stories, social media discussions, and full texts of original papers. We demonstrate that SPICED poses a challenging task and that models trained on SPICED improve downstream performance on evidence retrieval for fact checking of real world scientific claims. Finally, we show that models trained on SPICED can reveal large scale trends in the degrees to which people and organizations faithfully communicate new scientific findings. Data, code, and pre-trained models are available at http://www.copenlu. com/publication/2022_emnlp_wright/.