This paper explores how feminist and queer theories can inform voice design in technology, particularly in Human-Computer Interaction (HCI). It argues that biological sex and gender are socially constructed and performative, and that voice is a site where identity is both enacted and interpreted. Building on this framework, the paper examines the political and cultural implications of labels such as ``ambiguous'', ``queer'' and ``nonbinary'' in voice design. While ``ambiguous'' voices aim to reduce gendering broadly, ``queer'' and ``nonbinary'' voices intentionally represent gender-non-conforming people and challenge binary thinking. To ground this analysis in community perspectives, we report findings from a survey with nonbinary participants, examining how they label voices constructed from gender-expansive individuals and which terms they find most affirming. With this work, we offer practical guidelines for labelling voices in ways that affirm queer and nonbinary identities, clarifying when terms like ``queer'' and ``nonbinary'' are preferable and when ``ambiguous'' may be appropriate. Recognising these distinctions is key to inclusive design.
Autistic adults often use different communication styles than neurotypical individuals (NTs). While prior research has documented how such gaps disadvantage autistic job seekers, no study has systematically examined when these differences arise in language use and why autistic adults encounter interpretive gaps. This work seeks to datafy and characterize these communication challenges. We built an annotation interface and recruited 20 autistic adults to analyze 10 job postings each that they had selected as cases where they felt '' lost in translation.'' Participants annotated text spans using six categories informed by speech and language literature: unclear, ambiguous, incomplete, inappropriate, negative, and other. Follow-up interviews showed that lexical difficulties were rarely barriers; rather, challenges stemmed from interpreting implicit social arrangements or unstated expectations. We release the anonymized annotation data as the first-of-its-kind dataset documenting autistic–NT communication style differences. We conclude with implications for designing supports that foster clearer autistic–NT communication.
Autistic individuals sometimes disclose autism when asking LLMs for social advice, hoping for more personalized responses. However, they also recognize that these systems may reproduce stereotypes, raising uncertainty about the risks and benefits of disclosure. We conducted a mixed-methods study combining a large-scale LLM audit experiment with interviews involving 11 autistic participants. We developed a six-step pipeline operationalizing 12 documented autism stereotypes into decision-making scenarios framed as users requesting advice (e.g., “Should I do A or B?”). We generated 345,000 responses from six LLMs and measured how advice shifted when prompts disclosed autism versus when they did not. When autism was disclosed, LLMs disproportionately recommended avoiding stereotypically stressful situations, including social events, confrontations, new experiences, and romantic relationships. While some participants viewed this as affirming, others criticized it as infantilizing or undermining opportunities for growth. Our study illuminates how the intermingling of affirmation and stereotyping complicates the personalization of LLMs.
Human-Computer Interaction (HCI) scholars have invested deeply in community-based research; however, partnering with community advisory boards (CABs) in HCI remains rare and underexplored. In this paper, we translate traditions common in public health and community-based participatory research by presenting case studies of research partnerships with three CABs, each assembled to co-design technologies for and with transgender and queer people. Drawing upon comparative case study analysis and ethnographic-inspired reflections, our findings outline each CAB's operations across establishment, implementation, and sustainability stages. We then present four key facilitators of fostering meaningful partnerships with CABs: establishing expectations, transparency in decision-making, attending to positionality, and benefits to participation beyond research. Finally, we recommend that future community-based sociotechnical research adopt CABs to create meaningful relationships with community partners. However, we demonstrate that doing so requires careful deliberation around mutually beneficial research, contextually dynamic partnerships, and strategies for realignment between academic and community needs.
After Taiwan’s legalization of same-sex marriage in 2019, LGBTQ+ communities continue to face hostility on social media. Using the lens of hermeneutical injustice and autonomy, we examine how technological conditions affect LGBTQ+ individuals’ identity exploration, narrative seeking, and community resilience. We conducted a multi-stage study with Taiwanese LGBTQ+ individuals, including in-depth interviews, participatory design workshops, and evaluation sessions. Participants described fragile yet creative strategies such as seeking validation in online interactions, reframing hostile content through theory, and relying on allies. Building on these insights, we designed and evaluated a retrieval-augmented, LLM-powered chatbot with four modes of interaction: reflection, validation, discussion, and allyship. Findings show that the system fosters hermeneutical autonomy by helping participants reframe hostile narratives, validate lived experiences, and scaffold identity exploration, while reducing the hermeneutical labor of navigating social media hostility. We conclude by outlining design implications for AI systems that advance hermeneutical autonomy through fluid self-representation, contextualized dialogue, and inclusive community participation.
The ambiguity surrounding `creepy technology' in HCI poses significant challenges, as its interpretation varies considerably based on research focus. While it is often linked to the aesthetics of robots and concerns about personal data privacy and security, it is increasingly associated with functionality, unpredictability, and appropriateness. Clarifying this ambiguity is vital for designers, as design choices impact user experience and trust in technology. To address this, we undertook a systematic review of 115 papers based on content, identifying key themes related to design choices and contextual elements of creepiness. Through this review, we developed the \emph{Creepiness Framework}, which comprises two main components: the \emph{Structure of Creepiness} and \emph{Felt Creepiness}. The framework offers better understanding of the dynamics in creepy technology. Additionally, we provide insights into creepiness features that can assist in developing technologies that are more predictable and less likely to evoke unintended feelings of creepiness.
Human-Computer Interaction (HCI) has been critiqued for grounding technologies for disabled people in ableist paradigms, where the emphasis is placed on `fixing' autism rather than supporting autistic people. In contrast, the neurodiversity paradigm has helped many autistic people to develop an autistic identity, foster greater self-esteem, and build a sense of belonging within the broader neurodiversity community. Yet, little is known about how digital technologies might support information-seeking and self-reflection practices that contribute to autistic identity formation. Most HCI literature has largely focused on children, and has overlooked the experiences of autistic adults with intersecting gender and ethnic identities. This study addresses that gap by reporting findings from a survey (N=21) and participatory design workshops (n=8), where autistic cis and transgender women, as well as non-binary adults, reflected on their journeys towards identifying as autistic following a late autism diagnosis, and evaluated a prototype conversational agent designed to support this process. Our findings highlight the value of compassionate participatory design practices and contribute guidelines for designing agents that can support autistic adults and their identity formation.