Trust in Large Language Model chatbots depends not only on what these systems do but also on how their behavior is governed and communicated. We present Trust Mediator, a workbench that supports service owners in authoring and assessing principle sets for LLM-driven chatbots through persona-based exploration and structured scaffolds. To examine this workflow, we use three analytic lenses—specificity, coverage, and coherence—to characterize the principles produced. In an exploratory between-subjects study, we compared manual and assisted principle authoring. Participants in both conditions viewed principles as useful for governing and assessing chatbot behavior. Assisted authoring was generally perceived as more supportive and tended to broaden coverage. Manual authoring required more effort but yielded principles that were significantly more specific.These findings highlight complementary strengths of assisted and manual pathways and illustrate the value of treating principle sets as design objects within governance workflows. Beyond their analytic role in this study, the lenses themselves suggest opportunities for supporting the construction and inspection of principle sets.
This work examines how leading generative artificial intelligence companies construct and communicate the concept of "safety" through public-facing documents. Drawing on critical discourse analysis, we analyze a corpus of corporate safety-related statements to explicate how authority, responsibility, and legitimacy are discursively established. These discursive strategies consolidate legitimacy for corporate actors, normalize safety as an experimental and anticipatory practice, and push a perceived participatory agenda toward safe technologies. We argue that uncritical uptake of these discourses risks reproducing corporate priorities and constraining alternative approaches to governance and design. The contribution of this work is twofold: first, to situate safety as a sociotechnical discourse that warrants critical examination; second, to caution human-computer interaction scholars against legitimizing corporate framings, instead foregrounding accountability, equity, and justice. By interrogating safety discourses as artifacts of power, this paper advances a critical agenda for human-computer interaction scholarship on artificial intelligence.
Women's entrepreneurship is a key driver of socio-economic empowerment in the Global South, yet patriarchal sociocultural contexts limit entrepreneur’s autonomy and, despite increasing attention to gender issues in HCI, shifting digital infrastructures cause privacy, security, and logistical challenges. We conduct 15 interviews with women entrepreneurs in Bangladesh who rely on digital technology, offering insight into who they are, their business and supply chains, technology use, and the gendered challenges of balancing work with family. We present women’s accounts of navigating in-person and online harassment and crime, including through payment platforms, and banking tools that legally enforce gender discrimination. We discuss how digital technology design must adapt to these pervasive issues and propose digital interventions to support developing their businesses and achieving financial independence. Our work contributes to understanding how HCI can take a transformative role in overcoming barriers and advancing mechanisms for women's financial empowerment in the Global South.
Extended reality (XR) technologies have become more advanced and affordable in recent years, leading to greater familiarity and adoption among US families and youth-serving institutions. While these tools show promise in enhancing children’s education, healthcare, and recreation, ethical considerations around safety, accessibility, and impact—particularly for children from historically marginalized racial and ethnic groups—warrant further investigation. This study engaged 17 local, primarily Black, middle school male youth in evaluating and co-designing utopian and dystopian XR use cases to surface their ethical perspectives. We found that our participants emphasized individual responsibilities like self-discipline, self-care, and skepticism of virtual content; broader societal concerns about entrapment and diminished community agency; and design opportunities for promoting equity and access. Based on these findings, we offer design and methodological recommendations to better integrate the perspectives of male youth targeted for racial oppression into XR innovation to ensure that these tools are ethical, inclusive, and responsive to the communities they serve.
Pull-up objects form 3D shapes by pulling a string routed through a 2D material, offering low-cost 2D fabrication and reversible transformation. However, existing approaches rely on origamic folding, which creates faceted, oftentimes rigid surfaces and requires manual pull-up string routing. We introduce EmbroForm, a digital fabrication pipeline for fully soft pull-up objects with organic, higher-fidelity shapes. Instead of folding, EmbroForm forms 3D shapes by seaming the boundaries of a flexible 2D patch unwrapped from the target. To enable this, we contribute a fabrication technique that automates the routing of sliding strings on flexible sheet materials with machine embroidery, which we extend on to design zig-zag lacings for seaming the boundaries. Then we introduce an end-to-end pipeline that, given a 3D mesh, creates an optimized 2D unwrapped patch and generates pull-up string routing paths for fabrication. We provide a design tool for customization and validate our approach with technical experiments and implemented application cases.
Everyday digital feminism refers to the ordinary, often pragmatic ways women articulate lived experiences and cultivate solidarity in online spaces. In China, such practices flourish on RedNote through discussions under hashtags like ''women's growth''. Recently, DeepSeek-generated content has been taken up as a new voice in these conversations. Given widely recognized gender biases in LLMs, this raises critical concerns about how LLMs interact with everyday feminist practices. Through an analysis of 430 RedNote posts, 139 shared DeepSeek responses, and 3211 comments, we found that users predominantly welcomed DeepSeek's advice. Yet feminist critical discourse analysis revealed that these responses primarily encouraged women to self-optimize and pursue achievements within prevailing norms rather than challenge them. By interpreting this case, we discuss the opportunities and risks that LLMs introduce for everyday feminism as a pathway toward women's empowerment, and offer design implications for leveraging LLMs to better support such practices.
Low-resource countries represent over 90% of maternal deaths, with Pakistan among the top four countries contributing nearly half in 2023. Since these deaths are mostly preventable, large language models (LLMs) can help address this crisis by automating health communication and risk assessment. However, sexual and reproductive health (SRH) communication in conservative contexts often relies on indirect language that obscures meaning, complicating LLM-based interventions. We conduct a two-stage study in Pakistan: (1) analyzing data from clinical observations, interviews, and focus groups with clinicians and patients, and (2) evaluating the interpretive capabilities of five popular LLMs on this data. Our analysis identifies two axes of communication (referential domain and expression approach) and shows LLMs struggle with semantic drift, myths, and polysemy in clinical interactions. We contribute: (1) empirical themes in SRH communication, (2) a categorization framework for indirect communication, (3) evaluation of LLM performance, and (4) design recommendations for culturally-situated SRH communication.