Civic Care in Place: Subtle Technologies and Community Stewardship in a Marginalized ContextHow do communities sustain public spaces when formal infrastructure fails? In Stanley, UK a post-industrial town facing infrastructural neglect and climate-related flooding, residents sustain their environment through micro-acts that formal participation metrics fail to capture. Through surveys, interviews and a diary study conducted in partnership with Wear Rivers Trust, a charity advancing Nature-based Solutions (NbS), we examine how communities perceive and enact care under conditions of environmental precarity and low institutional trust. We found that care practices are embedded in daily routines and social ties, shaped by both pride and frustration, and sustained through informal networks. We contribute: (1) empirical insights into everyday civic care as emotional, negotiated, and place-based; and (2) a framework of six design dimensions, embeddedness, visibility, reciprocity, autonomy with support, coordination without formalization, and frustration as data --- to guide HCI/CSCW in developing respectful, lightweight, and situated systems that amplify rather than replace community capacities.2026ACAnna R. L. Carter et al.Northumbria UniversityCommunity Engagement & Civic TechnologySustainable HCIHuman-Nature Relationships (More-than-Human Design)CHI
"I Want It That Way": Enabling Interactive Decision Support Using Large Language Models and Constraint ProgrammingA critical factor in the success of many decision support systems is the accurate modeling of user preferences. Psychology research has demonstrated that users often develop their preferences during the elicitation process, highlighting the pivotal role of system-user interaction in developing personalized systems. This paper introduces a novel approach, combining Large Language Models (LLMs) with Constraint Programming to facilitate interactive decision support. We study this hybrid framework through the lens of meeting scheduling, a time-consuming daily activity faced by a multitude of information workers. We conduct three studies to evaluate the novel framework, including a diary study to characterize contextual scheduling preferences, a quantitative evaluation of the system’s performance, and a user study to elicit insights with a technology probe that encapsulates our framework. Our work highlights the potential for a hybrid LLM and optimization approach for iterative preference elicitation, and suggests design considerations for building systems that support human-system collaborative decision-making processes.2025CLConnor Lawless et al.Human-LLM CollaborationAI-Assisted Decision-Making & AutomationRecommender System UXIUI
Privacy Norms of Transformative Fandom: A Case Study of an Activity-Defined CommunityTransformative media fandom is a remarkably coherent, long-lived, and diverse community united primarily by shared engagement in the varied activities of fandom. Its social norms are highly-developed and frequently debated, and have been studied by the CSCW and Media Studies communities in the past, but rarely using the tools and theories of privacy, despite fannish norms often bearing strongly on privacy. We use privacy scholarship and existing theories thereof to examine these norms and bring an additional perspective to understanding fandom communities. In this work, we analyze over 250,000 words of "meta'' essays and comments on those essays, reflecting the views and debates of hundreds of fans on these privacy norms. Drawing on Solove's theory of privacy as an aggregation of different ideas and on a variety of other academic theories of privacy, we analyze these norms as highly effective at protecting the integrity of fannish activities. We then articulate the value of studying these sorts of diverse "activity-defined'' communities, arguing that such approaches grant us greater power to understand privacy experiences in ways that are specific, contextual, and intersectional yet still generalizable where possible.2024AMAbby Marsh et al.Session 3c: Evolving Approaches to PrivacyCSCW
Counting Carrds: Investigating Personal Disclosure and Boundary Management in Transformative FandomThe privacy practices of transformative fandom are of interest to HCI researchers both for the community's high proportion of queer members and for the community's sophisticated privacy norms and behaviors. We investigated fans' use of single-serving websites on Carrd.co ("Carrds") as personal profiles linked from Twitter accounts. We scraped Twitter to gather 5252 Carrds from fans in a variety of fandoms, which we analyzed using a combination of keyword searches and hand-coding. Fans' Carrds frequently disclose queer identity, and articulate a complex system of community values and boundary management. Inspired by how these findings aren't well-explained by individual theories of privacy, we articulate first steps towards a theory of collective privacy based in a communal process of values construction, trust building, and personal disclosure that we believe helps us to understand the sophisticated nature of fans' observed behaviors.2024KWKelly Wang et al.Northeastern UniversityOnline Identity & Self-PresentationParticipatory DesignCHI
Challenging but Connective: Large-Scale Characteristics of Synchronous Collaboration Across Time ZonesOrganizations are becoming increasingly distributed and many need to collaborate synchronously over great geographical distances. Despite a rich body of literature on spatially-distanced meetings, gaps remain in our understanding of temporally-distanced meetings. Here, we characterize cross time zone collaborations by analyzing 20 million meetings scheduled at a multinational corporation, Microsoft, supported by a survey on how 130 employees perceive their scheduling needs. We find that cross time zone meetings are closely associated with scheduling patterns around early morning and late evening hours, which are challenging and discordant with employees’ stated temporal preferences. Additionally, the burdens of meeting across time boundaries are asymmetrically distributed among workers at different levels of the organization and different geolocations. Nonetheless, we further observe evidence that cross time zone attendees are organizationally distant and diverse, suggesting that addressing these challenges by limiting meetings would disafford employees the opportunities to connect. We conclude by sharing opportunities for facilitating cross time zone meetings that foster healthier global collaborations.2023LMLillio Mok et al.University of TorontoRemote Work Tools & ExperienceDistributed Team CollaborationCHI
DataPilot: Utilizing Quality and Usage Information for Subset Selection during Visual Data PreparationSelecting relevant data subsets from large, unfamiliar datasets can be difficult. We address this challenge by modeling and visualizing two kinds of auxiliary information: (1) quality - the validity and appropriateness of data required to perform certain analytical tasks; and (2) usage - the historical utilization characteristics of data across multiple users. Through a design study with 14 data workers, we integrate this information into a visual data preparation and analysis tool, DataPilot. DataPilot presents visual cues about "the good, the bad, and the ugly" aspects of data and provides graphical user interface controls as interaction affordances, guiding users to perform subset selection. Through a study with 36 participants, we investigate how DataPilot helps users navigate a large, unfamiliar tabular dataset, prepare a relevant subset, and build a visualization dashboard. We find that users selected smaller, effective subsets with higher quality and usage, and with greater success and confidence.2023ANLillio Mok et al.Georgia Institute of TechnologyInteractive Data VisualizationVisualization Perception & CognitionCHI
Improving Humans' Ability to Interpret Deictic Gestures in Virtual RealityCollaborative Virtual Environments (CVEs) offer unique opportunities for human communication. Humans can interact with each other over a distance in any environment and visual embodiment they want. Although deictic gestures are especially important as they can guide other humans' attention, humans make systematic errors when using and interpreting them. Recent work suggests that the interpretation of vertical deictic gestures can be significantly improved by warping the pointing arm. In this paper, we extend previous work by showing that models enable to also improve the interpretation of deictic gestures at targets all around the user. Through a study with 28 participants in a CVE, we analyzed the errors users make when interpreting deictic gestures. We derived a model that rotates the arm of a pointing user's avatar to improve the observing users' accuracy. A second study with 24 participants shows that we can improve observers' accuracy by 22.9%. As our approach is not noticeable for users, it improves their accuracy without requiring them to learn a new interaction technique or distracting from the experience.2020SMSven Mayer et al.Carnegie Mellon University & University of StuttgartSocial & Collaborative VRImmersion & Presence ResearchCHI
Explaining Decision-Making Algorithms through UI: Strategies to Help Non-Expert StakeholdersIncreasingly, algorithms are used to make important decisions across society. However, these algorithms are usually poorly understood, which can reduce transparency and evoke negative emotions. In this research, we seek to learn design principles for explanation interfaces that communicate how decision-making algorithms work, in order to help organizations explain their decisions to stakeholders, or to support users' "right to explanation". We conducted an online experiment where 199 participants used different explanation interfaces to understand an algorithm for making university admissions decisions. We measured users' objective and self-reported understanding of the algorithm. Our results show that both interactive explanations and "white-box" explanations (i.e. that show the inner workings of an algorithm) can improve users' comprehension. Although the interactive approach is more effective at improving comprehension, it comes with a trade-off of taking more time. Surprisingly, we also find that users' trust in algorithmic decisions is not affected by the explanation interface or their level of comprehension of the algorithm.2019HCHao-Fei Cheng et al.University of MinnesotaExplainable AI (XAI)Algorithmic Transparency & AuditabilityCHI
Understanding the Impact of TVIs on Technology Use and Selection by Children with Visual ImpairmentsThe use of technology in educational settings is extremely common. For many visually impaired children, educational settings are the first place they are exposed to the assistive technology that they will need to access mainstream computing devices. Current laws provide support for students to receive training from Teachers of the Visually Impaired (TVIs) on these assistive devices. Therefore, TVIs play an important role in the selection and training of technology. Through our interviews with TVIs, we discovered the factors that impact which technologies they select, how they attempt to mitigate the stigma associated with certain technologies, and the challenges that students face in learning assistive technologies. Through this research, we identified three needs that future research on assistive technology should address: (1) increasing focus on built-in accessibility features, (2) providing support for independent learning and exploration, and (3) creating technologies that can support users with progressive vision loss.2019CBCatherine M. Baker et al.Creighton UniversityVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Cognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Special Education TechnologyCHI