Digital platforms often require users to select from a limited set of options that may force them to misrepresent their gender identities and sexual orientation, which disproportionately affects the LGBTQ+ population. To provide digital product teams with a feasible industry-focused tool to ensure the inclusion of this population, we surveyed 151 participants, including 81 who identify as LGBTQ+; conducted five interviews with LGBTQ+ participants and 11 interviews with product managers in the technology industry; and analyzed the user account creation processes of 45 digital platforms commonly used or mentioned in survey responses to understand LGBTQ+ users’ wants, needs, and pain points in navigating user account sign-up. Participants recounted instances of microaggressions or micro-affirmations, and often had strong feelings about companies based on their account creation experience. Based on these results, we present a ‘Playbook’ of design recommendations, which is online at bit.ly/LGBTInclusive_UAGuide.
doi.org/10.1145/3613904.3642784
Food tracking applications (apps) can provide benefits (e.g., helping diagnose food intolerances) but can also create harm (e.g., facilitating disordered eating). However, food tracking apps—viewed as a women’s health issue, and critically examined through the lens of feminist HCI—are absent from the discourse of sociocultural, ethical, and political implications of apps designed to track bodily data. We use a walkthrough method to critically analyze three commercial food tracking apps with differing marketing narratives and designs, applying a reflexive feminist lens grounded in a perspective of fat liberation. We articulate how these apps reproduce normativities of food and nutrition, health, and bodies, and how they perpetuate narratives of embodiment, simplification and quantification of health, and neoliberalism and the individualization of health. Our work exposes the normativities of bodies being propagated by food tracking apps, spotlighting how designs and interaction features are situated within prevalent anti-fat narratives.
doi.org/10.1145/3613904.3642600
LGBTQ+ people have received increased attention in HCI research, paralleling a greater emphasis on social justice in recent years. However, there has not been a systematic review of how LGBTQ+ people are researched or discussed in HCI. In this work, we review all research mentioning LGBTQ+ people across the HCI venues of CHI, CSCW, DIS, and TOCHI. Since 2014, we find a linear growth in the number of papers substantially about LGBTQ+ people and an exponential increase in the number of mentions. Research about LGBTQ+ people tends to center experiences of being politicized, outside the norm, stigmatized, or highly vulnerable. LGBTQ+ people are typically mentioned as a marginalized group or an area of future research. We identify gaps and opportunities for (1) research about and (2) the discussion of LGBTQ+ in HCI and provide a dataset to facilitate future Queer HCI research.
doi.org/10.1145/3613904.3642494
ChatGPT is a conversational agent built on a large language model. Trained on a significant portion of human output, ChatGPT can mimic people to a degree. As such, we need to consider what social identities ChatGPT simulates (or can be designed to simulate). In this study, we explored the case of identity simulation through Japanese first-person pronouns, which are tightly connected to social identities in intersectional ways, i.e., intersectional pronouns. We conducted a controlled online experiment where people from two regions in Japan (Kanto and Kinki) witnessed interactions with ChatGPT using ten sets of first-person pronouns. We discovered that pronouns alone can evoke perceptions of social identities in ChatGPT at the intersections of gender, age, region, and formality, with caveats. This work highlights the importance of pronoun use for social identity simulation, provides a language-based methodology for culturally-sensitive persona development, and advances the potential of intersectional identities in intelligent agents.
doi.org/10.1145/3613904.3642303
Large language models (LLMs) can generate personas based on prompts that describe the target user group. To understand what kind of personas LLMs generate, we investigate the diversity and bias in 450 LLM-generated personas with the help of internal evaluators (n=4) and subject-matter experts (SMEs) (n=5). The research findings reveal biases in LLM-generated personas, particularly in age, occupation, and pain points, as well as a strong bias towards personas from the United States. Human evaluations demonstrate that LLM persona descriptions were informative, believable, positive, relatable, and not stereotyped. The SMEs rated the personas slightly more stereotypical, less positive, and less relatable than the internal evaluators. The findings suggest that LLMs can generate consistent personas perceived as believable, relatable, and informative while containing relatively low amounts of stereotyping.
doi.org/10.1145/3613904.3642036
How can tangible, wearable design encourage affective, embodied reflections on queer history? We expand Queer HCI scholarship, using queer theory to inform the design of wearable experiences that explore archives of gender and sexuality. Our project, “Button Portraits,” invites individuals to listen to oral histories from prominent queer activists by pinning archival buttons to a wearable audio player, eliciting moving personal impressions. We observed 17 participants’ experiences with “Button Portraits,” and with semi-structured interviews, surfaced reflections on how our design evoked personal connections to history, queer self-identification, and relatability to archival materials. We offer the following design directions: (1) designing tangible archives of feeling; (2) queering tangible, wearable interactions in design; (3) designing for personal, archival experiences; and (4) designing within difference. Through this work, we foreground queer stories to affect emotional reflections on marginalized histories, entangling the complex connections between bodies, feelings, histories, and shared queer experiences.
doi.org/10.1145/3613904.3642312
In HCI there have been calls for diversity-driven research and insights into how this may be carried out in practice. One way of conducting diversity-driven HCI research is by doing participatory design. In this paper we contribute with lessons identified from organizing a PD workshop that enabled diverse ways of participating for our participants. The workshop design is based on insights from two years of doing diversity-driven PD with two middle school classes, which are particularly interesting settings to explore as diverse children spend substantial time together in a period of their development that is formative for their socialisation. We describe the workshop itself before reflecting on its structure and facilitation as well as the role of the physical space and the choice of design materials with the aim to distil insights and recommendations about what researchers can do to enable diverse pathways of participation in design processes.
doi.org/10.1145/3613904.3642240
When thinking about algorithms, cold lines of code and purely rational decisions may come to mind. However, this picture is incomplete. Numerous examples illustrate how human aspects shape algorithmic output (e.g., via biased training data). This study delves into how developers’ and users’ individual differences can influence algorithmic output, focusing on environmental and altruistic motivation. In an online survey, (N = 766) participants rated different emails on their likelihood of being spam as input for a hypothetical spam-filter algorithm. Participants’ environmental motivation was negatively correlated with classifying emails from environmental and humanitarian organizations as spam. Thus, individuals with a stronger environmental motivation rated the emails in such a way that the spam filter was biased toward the common good. However, altruistic motivation had no impact on the ratings. These findings suggest that environmental motivation extends beyond pro-environmental behaviors by also influencing prosocial behaviors, thus offering insights for developing sustainable algorithms.
doi.org/10.1145/3613904.3642404
Fatness sits at the intersection of many systems of oppression, such as race, gender, class, and (dis)ability. Anti-fat bias happens out in the open and is prevalent in Western society, yet there has been little to no consideration for the wider impact of digital systems in exacerbating, recreating, and repurposing anti-fat bias, or any engagement with designing for fat justice. Therefore, this paper argues that there needs to be a consideration for fat dignity in the design of digital systems, and an investigation of the (un)intended consequences of the datafication of fat lives. This paper offers a scoping literature review of HCI and Fat Studies to identify research gaps and argues that both disciplines would benefit from collaboration. Specifically, the standard of design justice would be increased through radical acceptance, and new questions could be asked to critique how technologies have been leveraged to exercise control over our bodies.
doi.org/10.1145/3613904.3642199
To improve people’s lives, human-computer interaction researchers are increasingly designing technological solutions based on behavior change theory, such as social comparison theory. However, how researchers operationalize such a theory as a design remains largely unclear. One way to clarify this methodological step is to clearly state which functional elements of a design are aimed at operationalizing a specific behavior change theory construct to evaluate if such aims were successful. In this paper, we investigate how the operationalization of functional elements of theories and designs can be more easily conveyed. First, we present a scoping review of the literature to determine the state of operationalizations of social comparison theory as behavior change designs. Second, we introduce a new tool to facilitate the operationalization process. We term the tool: Blueprints. A blueprint explicates essential functional elements of a behavior change theory by describing it in relation to necessary, and sufficient building blocks incorporated in a design. We describe the process of developing a blueprint for social comparison theory. Lastly, we illustrate how the blueprint can be used during the design refinement and reflection process.