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Wearable technology for physical activity promotion is a frequent research topic within HCI and health, and researchers have documented that much of our knowledge is sourced from understanding the needs of populations from college educated, racially privileged, Western backgrounds. However socioeconomic class, a core component for how people perceive physical activity, wearables, and even wearable studies, has not often been contended with. In this critical discussion of the literature, incorporating examples from over 30 deployment studies involving wearables and over 70 other related works, we investigate how socioeconomic class shows up in study design and identify how class cultures are embedded in the design of wearable technology. We hypothesize that common study components related to time and activity type engenders high SES class cultures and ultimately risk creating intervention generated inequalities. We discuss the implications of ignoring class such as further perpetuating inequities in subsequent waves of wearable device maturity.
Involving Black and Latina/o communities early and often in emerging technology design can make innovation more democratic, address bias, and reduce harm against these marginalized groups. To the best of our knowledge, no work has examined how recently incarcerated and gang affiliated young adults conceptualize mixed reality (MR) use for social collocated scenarios based on their everyday interactions and meaning-making. To explore this topic, we used a design-based implementation research (DBIR) and community-based participatory design (CBPD) approach to elicit social-technical insights grounded in the personal and critical perspectives of these youth. We find participants frequently grounded design ideas as embodied design elements to surface intangible and invisible qualities such as emotions and reflections on lived experiences, namely criticizing institutional structures that have maintained exclusionary practices against them. We discuss how DBIR and CBPD can uncover larger societal issues impacting marginalized communities through emerging technology design, and we contribute design recommendations for social collocated interactions in MR.
LGBTQ+ individuals are increasingly turning to chatbots powered by large language models (LLMs) to meet their mental health needs. However, little research has explored whether these chatbots can adequately and safely provide tailored support for this demographic. We interviewed 18 LGBTQ+ and 13 non-LGBTQ+ participants about their experiences with LLM-based chatbots for mental health needs. LGBTQ+ participants relied on these chatbots for mental health support, likely due to an absence of support in real life. Notably, while LLMs offer prompt support, they frequently fall short in grasping the nuances of LGBTQ-specific challenges. Although fine-tuning LLMs to address LGBTQ+ needs can be a step in the right direction, it isn't the panacea. The deeper issue is entrenched in societal discrimination. Consequently, we call on future researchers and designers to look beyond mere technical refinements and advocate for holistic strategies that confront and counteract the societal biases burdening the LGBTQ+ community.
This paper explores how conceptions of societal impact are produced and performed during academic computer science research, by leveraging critical technical practice while building a digital agriculture networking platform. Our findings reveal how everyday practices of envisioning and building infrastructure require working across disciplinary and institutional seams, leading us as computer scientists to continuously reconceptualize the intended societal impact. By self-reflectively analyzing how we accrue resources for projects, produce research systems, write about them, and maintain alignments with stakeholders, we demonstrate that this seam work produces shifting simulacra of societal impact around which the system’s success is narrated. HCI researchers frequently suggest that technical systems’ impact could be improved by motivating computer scientists to consider impact in system-building. Our findings show that institutional and disciplinary structures significantly shape how computer scientists can enact societal impact in their work. This work suggests opportunities for structural interventions to shape the impact of computing systems.