Beyond Clinical Risk: An Experimental Study of Cybersecurity Informed Consent and Patient Choice for Connected Medical DevicesInternet-connected medical devices introduce complex cybersecurity risks that challenge the established practice of informed consent. It remains unclear how patients weigh these abstract, dynamic threats against concrete clinical benefits. We present findings from a large-scale (N=2,666) vignette-based experiment designed to uncover the factors driving patient decision-making. Participants chose whether to adopt a connected pacemaker, weighing its enhanced clinical outcomes against potential vulnerabilities. We systematically varied communication factors, including the source of risk information (e.g., clinician, FDA), risk framing, and the details of a subsequent vulnerability disclosure. Our results reveal patient choice hinges on pre-existing physician trust and risk framing. We did not observe any effect from the information's source. We also find initial choices act as powerful anchors, and that detailed disclosures increase security confidence. Our work provides crucial empirical evidence on this trade-off, offering actionable guidance to better support informed consent for life-critical connected technologies.2026RTRonald E. Thompson et al.Tufts UniversityPrivacy Perception & Decision-MakingTelemedicine & Remote Patient MonitoringPrivacy by Design & User ControlCHI
I Can SE Clearly Now: Investigating the Effectiveness of GUI-based Symbolic Execution for Software Vulnerability DiscoveryWhile symbolic execution (SE) can discover software vulnerabilities, it has received limited practical adoption. A key barrier is that SE requires human expertise to understand the program’s state and prioritize paths to analyze. Traditionally, users controlled SE through programmatic API calls, but recent tooling now implements graphical user interfaces (GUI). However, it is unclear how these new features affect human-SE performance. To understand this impact, we conducted a controlled experiment where 24 vulnerability discovery experts were tasked with analyzing a binary using an SE tool with either API or GUI-based features. From this study, we identify (1) experts' SE process, and (2) the impact of GUI-based features on human-SE performance. Then we propose recommendations to improve SE tool design.2026YLYi Jou Li et al.Arizona State UniversityComputational Methods in HCIUser Research Methods (Interviews, Surveys, Observation)Prototyping & User TestingCHI
Outfoxed: Design and Evaluation of a Modular Interactive Puzzle for Cognitive Enrichment of Zoo AnimalsCognitively stimulating experiences are fundamental to supporting the welfare of zoo-housed animals. Puzzle-feeders are often initially engaging, but require frequent human intervention and often lack adaptability to support animals’ sustained cognitive engagement. We developed a modular adaptive puzzle-feeder designed to support user agency, independence, and multisensory feedback. The system was deployed over four weeks with an Arctic fox (\textit{Vulpes lagopus}) across progressive difficulty levels and piloted with two coatis (\textit{Nasua narica}). Combining HCI and animal science methodologies, we assessed (1) multisensory engagement, (2) changes in behavioral diversity and habitat utilization, (3) adaptation to puzzle complexity, and (4) impact on human stakeholders. Results show strong sustained engagement (46.5\% time-budget), increased behavioral diversity, habitat exploration, strategic problem-solving, and positive keeper and visitor reactions. This work highlights how technology can support animal welfare and visitor experience, and how mixed HCI and ethological methods enable holistic evaluation of enrichment and animal usership.2026VMVatsal Mehta et al.Northeastern UniversityDigital Art Installations & Interactive PerformancePhysical-Digital Hybrid InteractionMultisensory Fusion ExperienceCHI
Towards Fair and Equitable Incentives to Motivate Paid and Unpaid Crowd ContributionsResearchers commonly rely on contributions from either unpaid contributors or work done by paid crowdworkers. Rarely are the motivations of these workers and the accuracy of their contributions studied simultaneously in the wild over time. We maintain a public system where anyone can edit an evolving tabular dataset of Computer Science faculty profiles useful for the field of CS, and in this work, we analyze both the accuracy of contributions and the motivations of paid crowdworkers and unpaid contributors, combining data from real-world edit histories and a discrete choice experiment. The accuracy of edits made by unpaid contributors was 1.9 times higher than that of paid crowdworkers for difficult-to-find data and 1.5 times greater for data requiring domain-specific expertise. \actwo{Our discrete choice experiment reveals that while both groups are motivated by common attributes describing a contribution task: pay level, estimated completion time, interest, and the ability to help others, they make different trade-offs between these attributes when choosing crowd contribution tasks.} We provide recommendations to build hybrid data systems that mix extrinsic and intrinsic motivators to motivate highly accurate contributors, whether paid or unpaid.2025SWShaun Wallace et al.University of Rhode Island, Computer Science and StatisticsCrowdsourcing Task Design & Quality ControlCitizen Science & Crowdsourced DataCHI
An Investigation of Interaction and Information Needs for Protocol Reverse Engineering AutomationProtocol reverse engineering (ProtocolREing) consists of taking streams of network data and inferring the communication protocol. ProtocolREing is critical task in malware and system security analysis. Several ProtocolREing automation tools have been developed, however, in practice, they are not used because they offer limited interaction. Instead, reverse engineers (ProtocolREs) perform this task manually or use less complex visualization tools. To give ProtocolREs the power of more complex automation, we must first understand ProtocolREs processes and information and interaction needs to design better interfaces. We interviewed 16 ProtocolREs, presenting a paper prototype ProtocolREing automation interface, and ask them to discuss their approach to ProtocolREing while using the tool and suggest missing information and interactions. We designed our prototype based on existing ProtocolREing tool features and prior reverse engineering research's usability guidelines. We found ProtocolREs follow a flexible, hypothesis-driven process and identified multiple information and interaction needs when validating the automation's inferences. We provide suggestions for future interaction design.2025SKSamantha Katcher et al.Tufts University, Department of Computer Science; MITRE CorporationExplainable AI (XAI)AI-Assisted Decision-Making & AutomationAlgorithmic Transparency & AuditabilityCHI
AI on My Shoulder: Supporting Emotional Labor in Front-Office Roles with an LLM-based Empathetic CoworkerClient-Service Representatives (CSRs) are vital to organizations. Frequent interactions with disgruntled clients, however, disrupt their mental well-being. To help CSRs regulate their emotions while interacting with uncivil clients, we designed Care-Pilot, an LLM-powered assistant, and evaluated its efficacy, perception, and use. Our comparative analyses between 665 human and Care-Pilot-generated support messages highlight Care-Pilot’s ability to adapt to and demonstrate empathy in various incivility incidents. Additionally, 143 CSRs assessed Care-Pilot’s empathy as more sincere and actionable than human messages. Finally, we interviewed 20 CSRs who interacted with Care-Pilot in a simulation exercise. They reported that Care-Pilot helped them avoid negative thinking, recenter thoughts, and humanize clients; showing potential for bridging gaps in coworker support. Yet, they also noted deployment challenges and emphasized the indispensability of shared experiences. We discuss future designs and societal implications of AI-mediated emotional labor, underscoring empathy as a critical function for AI assistants for worker mental health.2025VSVedant Das Swain et al.Northeastern University, Khoury College of Computer ScienceHuman-LLM CollaborationMental Health Apps & Online Support CommunitiesCHI
BPCoach: Exploring Hero Drafting in Professional MOBA Tournaments via Visual AnalyticsHero drafting for multiplayer online arena (MOBA) games is crucial because drafting directly affects the outcome of a match. Both sides take turns to "ban"/"pick" a hero from a roster of approximately 100 heroes to assemble their drafting. In professional tournaments, the process becomes more complex as teams are not allowed to pick heroes used in the previous rounds with the "best-of-N" rule. Additionally, human factors including the team's familiarity with drafting and play styles are overlooked by previous studies. Meanwhile, the huge impact of patch iteration on drafting strengths in the professional tournament is of concern. To this end, we propose a visual analytics system, BPCoach, to facilitate hero drafting planning by comparing various drafting through recommendations and predictions and distilling relevant human and in-game factors. Two case studies, expert feedback, and a user study suggest that BPCoach helps determine hero drafting in a rounded and efficient manner.2024SLShiyi Liu et al.Session 4f: Multiplayer Gaming and CommunicationCSCW
Attention is All They Need: Exploring the Media Archaeology of the Computer Vision Research PaperResearch papers, in addition to textual documents, are a designed interface through which researchers communicate. Recently, rapid growth has transformed that interface in many fields of computing. In this work, we examine the effects of this growth from a media archaeology perspective, through the changes to figures and tables in research papers. Specifically, we study these changes in computer vision over the past decade, as the deep learning revolution has driven unprecedented growth in the discipline. We ground our investigation through interviews with veteran researchers spanning computer vision, graphics and visualization. Our analysis focuses on the research attention economy: how research paper elements contribute towards advertising, measuring and disseminating an increasingly commodified ``contribution.'' Through this work, we seek to motivate future discussion surrounding the design of both the research paper itself as well as the larger sociotechnical research publishing system, including tools for finding, reading and writing research papers.2024SGSamuel Goree et al.Session 2f: UX, Visual Communication and DesignCSCW
Empower Real-World BCIs with NIRS-X: An Adaptive Learning Framework that Harnesses Unlabeled Brain SignalsBrain-Computer Interfaces (BCIs) using functional near-infrared spectroscopy (fNIRS) hold promise for future interactive user interfaces due to their ease of deployment and declining cost. However, they typically require a separate calibration process for each user and task, which can be burdensome. Machine learning helps, but faces a data scarcity problem. Due to inherent inter-user variations in physiological data, it has been typical to create a new annotated training dataset for every new task and user. To reduce dependence on such extensive data collection and labeling, we present an adaptive learning framework, NIRS-X, to harness more easily accessible unlabeled fNIRS data. NIRS-X includes two key components: NIRSiam and NIRSformer. We use the NIRSiam algorithm to extract generalized brain activity representations from unlabeled fNIRS data obtained from previous users and tasks, and then transfer that knowledge to new users and tasks. In conjunction, we design a neural network, NIRSformer, tailored for capturing both local and global, spatial and temporal relationships in multi-channel fNIRS brain input signals. By using unlabeled data from both a previously released fNIRS2MW visual $n$-back dataset and a newly collected fNIRS2MW audio $n$-back dataset, NIRS-X demonstrates its strong adaptation capability to new users and tasks. Results show comparable or superior performance to supervised methods, making NIRS-X promising for real-world fNIRS-based BCIs.2024LWLiang Wang et al.Human Pose & Activity RecognitionBrain-Computer Interface (BCI) & NeurofeedbackUIST
Designing Visual Signals to Support Situation Awareness Recovery in Conditional Automated DrivingConditionally automated driving systems face two main safety challenges: the inability to autonomously handle all situations the vehicle encounters, and the allowed inattention of drivers during these critical moments. Our study focuses on enhancing drivers’ situation awareness at such times by embedding information about system status and the road environment in the visual signals displayed when control is transferred from the automated driving system. Six visual signals, each including different levels of situation awareness information, were compared to examine how they influence drivers’ levels of situation awareness in a simulated environment. The results show that signals incorporating higher levels of situation awareness information about the environment significantly facilitate the recovery of situation awareness after engaging in non-driving related tasks. This research provides insights into how visual cues can be optimized to facilitate quicker recovery of situation awareness for drivers transitioning from non-driving tasks in conditionally automated vehicles.2024OLOkkeun Lee et al.Automated Driving Interface & Takeover DesignHead-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)AutoUI
An Investigation of US Universities' Implementation of FERPA Student Directory Policies and Student Privacy PreferencesThe Family Education Rights and Privacy Act (FERPA) is intended to protect student privacy, but has not adapted well to current technology. We consider a special class of student data: directory information. Unlike other FERPA-controlled data, directory information (e.g., student names, contact information, university affiliation) can be shared publicly online or by request without explicit permission. To understand this policy's impact, we investigated 100 top-ranked US universities' directory information sharing practices, finding they publish student contact information online, and provide PII offline by request to many parties, including data brokers. Universities provide limited opt out choices, and focus on negative effects when advising students about opting out. Lastly, we evaluate student preferences regarding the identified directory practices through a survey of 991 US university students. Based on these results, we provide recommendations to align directory practices with student privacy preferences.2024SRSarah Radway et al.Harvard UniversityPrivacy by Design & User ControlPrivacy Perception & Decision-MakingCHI
Intentional User Adaptation to Shared Control AssistanceShared control approaches to robot assistance typically assume that user behavior remains the same despite the addition of the the assistance and rely upon this assumption to infer user goals. However, HRI research consistently shows that users are highly sensitive to changes in robot performance, which contradicts this assumption. In this paper, we show that users, in fact, change their control behavior in the presence of assistance and describe these changes as intentional adaptations to the new system dynamics. We present two user studies in which participants controlled robots with various levels of assistance. In a computer-based study, participants report changing their strategies as the assistance changes, and the amount of change in the direction of their control significantly differs between assistance conditions. In an in-the-wild robot study, participants teleoperated a robot to pick up a cup despite the presence of "assistance" that drives the system towards nonexistent goals and away from the true goals of the task. The ability of participants to overcome the assistance and still achieve the goal further demonstrates that users can change their behavior to account for the novel dynamics. These results motivate further research in user-centered design and evaluation of assistive systems that treat the user as intentional.2024RAReuben M Aronson et al.Human-Robot Collaboration (HRC)HRI
Modeling Variation in Human Feedback with User Inputs: An Exploratory MethodologyTo expedite the development process of interactive reinforcement learning (IntRL) algorithms, prior work often uses perfect oracles as simulated human teachers to furnish feedback signals. Those oracles typically derive from ground-truth knowledge or optimal policies, and provide dense and error-free feedback to a robot learner without delay. However, this machine-like feedback behavior fails to accurately represent the diverse patterns observed in human feedback, which may lead to unstable or unexpected algorithm performance in real-world human-robot interaction. To alleviate this limitation of oracles in oversimplifying user behavior, we propose a method for modeling variation in human feedback that can be applied to a standard oracle. We present a 5-dimensional model with 5 dimensions of feedback variation identified in prior work. This model enables the modification of feedback output from perfect oracles to introduce more human-like features. We demonstrate how each model attribute can impact on the learning performance of an IntRL algorithm through a simulation experiment. We also conduct a proof-of-concept study to illustrate how our model can be populated from people in two ways. The modeling results intuitively present the feedback variation among participants and help to explain the mismatch between oracles and human teachers. Overall, our method is a promising step towards refining simulated oracles by incorporating insights from real users.2024JHJindan Huang et al.AI-Assisted Decision-Making & AutomationMental Health Apps & Online Support CommunitiesHRI
Online Behavior Modification for Expressive User Control of RL-Trained RobotsReinforcement Learning (RL) is an effective method for robots to learn tasks. However, in typical RL, end-users have little to no control over how the robot does the task after the robot has been deployed. To address this, we introduce the idea of online behavior modification, a paradigm in which users have control over behavior features of a robot in real-time as it autonomously completes a task using an RL-trained policy. To show the value of this user-centered formulation for human-robot interaction, we present a behavior-diversity–based algorithm, Adjustable Control Of RL Dynamics (ACORD), and demonstrate its applicability to online behavior modification in simulation and a user study. In the study (n=23), users adjust the style of paintings as a robot traces a shape autonomously. We compare ACORD to RL and Shared Autonomy (SA), and show ACORD affords user-preferred levels of control and expression, comparable to SA, but with the potential for autonomous execution and robustness of RL. The code for this paper is available at anon.url2024ISIsaac S Sheidlower et al.AI-Assisted Decision-Making & AutomationHuman-Robot Collaboration (HRC)HRI
Computer-Mediated Sharing Circles for Intersectional Peer Support with Home Care WorkersHome care workers (HCWs) provide essential care in patients' homes but are often underappreciated and work in stressful and isolated environments with diverse and intersecting support needs. This paper describes a computer-mediated peer support program that centers around sharing circles: spaces for personal, narrative storytelling to encourage HCWs to collaboratively reflect on their home care experiences and build rapport and shared identity with their peers. We describe the design of this program and a 12-week deployment that we conducted to evaluate the program with 42 HCWs in New York City. Our findings show that participants engaged in multiple types of peer support including emotional validation, learning how to navigate the workplace and patient care, defining and enabling good home care praxis, and building understanding around purpose and identity as HCWs. We discuss how these findings inform the design of technology and use of holistic pedagogies, such as storytelling, to enable this support in computer-mediated peer support programs. Such programs can help researchers and practitioners interested in addressing diverse needs that occur in intersectional contexts, such as that of HCWs and other marginalized populations.2023APAnthony Poon et al.Health SupportCSCW
Designing for Peer-Led Critical Pedagogies in Computer-Mediated Support Groups for Home Care WorkersHome care workers (HCWs) deliver essential health services within patients’ homes and are an important part of the US healthcare system. Yet, they are a marginalized workforce, whose physical isolation and lack of access to support structures make them vulnerable to exploitation. Computer-mediated support programs may help bridge this gap and, through critical and liberatory pedagogies, foster material social change. However, such pedagogies typically assume the involvement of a professional facilitator when, in practice, support programs are often led by peers with little to no facilitation training. Based on a three-month study with HCWs, this paper explores how peers can perform critical and liberatory facilitation practice in an online support program. We illustrate the challenges peers faced learning this practice and performing this role in an online environment. Our findings can improve the design of computer-mediated support programs and how to prepare peer leadership, particularly for addressing the needs of marginalized populations.2023APAnthony Poon et al.Cornell UniversityAugmentative & Alternative Communication (AAC)Participatory DesignCHI
Identifying Cognitive and Creative Support Needs for Remote Scientific Collaboration using VR: Practices, Affordances, and Design ImplicationsRemote scientific collaborations have been pivotal in generating scientific discoveries and breakthroughs that accelerate research in many fields. Emerging VR applications for remote work, which utilize commercially available head-mounted displays (HMDs), offer the promise to enhance collaboration, through spatial and embodied experiences. However, there is little evidence on how professionals in general, and scientists in particular, could use existing commercial VR applications to support their cognitive and creative collaborative processes while exploring real-world data as part of day-to-day collaborative work. In this paper, we present findings from an empirical study with 14 coral reef scientists, examining how they chose to utilize available resources in existing virtual environments for their ongoing data-driven collaborative research. We shed light on scientists' data organization practices, identify affordances unique to VR for supporting cognition in a collaborative setting, and highlight design requirements for supporting cognitive and creative collaboration processes in future tools.2022MOMonsurat Olaosebikan et al.Social & Collaborative VRContext-Aware ComputingKnowledge Worker Tools & WorkflowsC&C
How Ready is Your Ready? Assessing the Usability of Incident Response Playbook FrameworksIncident response playbooks provide step-by-step guidelines to help security operations personnel quickly respond to specific threat scenarios. Although playbooks are common in the security industry, they have not been empirically evaluated for effectiveness. This paper takes a first step toward measuring playbooks and the frameworks used to design them, using two studies conducted in an enterprise environment. In the first study, twelve security professionals created two playbooks each, using two standard playbook design frameworks; the resulting playbooks were evaluated by experts for accuracy. In the second, we observed five personnel using the created playbooks in no-notice threat exercises within a live security-operations center. We find that playbooks can help simplify and support incident response efforts. However, playbooks designed using the frameworks we examined often lack sufficient detail for real-world use, particularly for more junior technicians. We provide recommendations for improving playbooks, playbook frameworks, and organizational processes surrounding playbook use.2022RSRock Stevens et al.University of MarylandPrivacy by Design & User ControlPrivacy Perception & Decision-MakingCybersecurity Training & AwarenessCHI
Understanding How Programmers Can Use Annotations on DocumentationModern software development requires developers to find and effectively utilize new APIs and their documentation, but documentation has many well-known issues. Despite this, developers eventually overcome these issues but have no way of sharing what they learned. We investigate sharing this documentation-specific information through annotations, which have advantages over developer forums as the information is contextualized, not disruptive, and is short, thus easy to author. Developers can also author annotations to support their own comprehension. In order to support the documentation usage behaviors we found, we built the Adamite annotation tool, which provides features such as multiple anchors, annotation types, and pinning. In our user study, we found that developers are able to create annotations that are useful to themselves and are able to utilize annotations created by other developers when learning a new API, with readers of the annotations completing 67% more of the task, on average, than the baseline.2022AHAmber Horvath et al.Carnegie Mellon University, Carnegie Mellon UniversityProgramming Education & Computational ThinkingKnowledge Worker Tools & WorkflowsCHI
Computer-Mediated Peer Support Needs of Home Care Workers: Emotional Labor & the Politics of ProfessionalismHome care workers (HCWs) are increasingly central to post-acute and long-term health services in the United States. \update{Despite being a critical component of day-to-day care of home-dwelling adults, these workers often feel underappreciated and isolated on the job} and come from low-income and marginalized backgrounds. Leveraging the support of peers is one potential way to empower HCWs, but peer support encompasses a broad range of activities and aspects. Traditional conceptions of peer support may not be appropriate to the home care context, as HCWs are a distributed workforce who have few opportunities to interact with each other. In this study, we explore how HCWs value and conceptualize peer support. Our findings demonstrate the importance of peer support in performing the emotional labor of home care work and ongoing attempts to strategically frame the home care profession as essential and medical in nature. Our results ground design implications for technology-enabled peer support based on the power dynamics of our participants’ context and allow us to engage with issues where technology design for empowerment intersects with exploitation in distributed or crowd work, emotional labor, and tacit knowledge.2021APAnthony Poon et al.Care and CaregivingCSCW