huashen218/convxai-cia-dataset huggingface dataset:
Title: “I Don’t Want To Shoot The Android”: Players Translate Real-Life Moral Intuitions to In-Game Decisions in Detroit: Become Human
Authors: family: Arrambide
given: Karina; family: Yoon
given: John; family: MacArthur
given: Cayley; family: Rogers
given: Katja; family: Luz
given: Alessandra; family: Nacke
given: Lennart E.
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: choice, morality, moral foundations questionnaire, interactive story, moral foundations theory, interactive narrative, games, decision-making, thematic analysis

Abstract: In interactive story games, players make decisions that advance and modify the unfolding story. In many cases, these decisions have a moral component. Examining decision-making in these games illuminates whether players mobilize their real-life morality to make in-game decisions and what impact this has in both the game world and real life. Using mixed-methods consisting of semi-structured interviews and the Moral Foundations Questionnaire (MFQ30), we collected data from 19 participants who played the game Detroit: Become Human. We analyzed how participants applied their real-life morals toward in-game decisions using thematic analysis and statistical analysis of the MFQ30 results. Qualitative findings indicate that participants mobilize their moral intuitions to make in-game decisions and how much participants cared about their game characters influenced their choices. We contribute a better understanding of how players react to moral dilemmas in interactive story games for game designers to help them improve player experience.
Title: Emotional Exploration and the Eudaimonic Gameplay Experience: A Grounded Theory
Authors: family: Cole
given: Tom; family: Gillies
given: Marco
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: mixed affect, grounded theory, emotions, gameplay, eudaimonia, videogames

Abstract: Research on the emotional experience of playing videogames has increased in recent years, yet much of this work is focused on the hedonistic player experience (PX) commonly associated with the nebulous concept of ‘fun’ and positive affect. Researchers are increasingly paying more attention to the eudaimonic PX commonly associated with ‘appreciation’, mixed-affect and reflection. To further investigate eudaimonic PX we interviewed 24 games players about ‘significant or memorable emotional experiences’ from their games playing and used grounded theory to analyse their responses. This led to the construction of the concept of ‘emotional exploration’ which is used to help explain (i) why players would seek out a eudaimonic PX, (ii) how eudaimonic PX is constituted and (iii) how developers can design for a eudaimonic PX. We further make the case for the ‘eudaimonic gameplay experience’ to be realised as different and separate to pre-existing notions of eudaimonic entertainment.
Title: Do People Use Games to Compensate for Psychological Needs During Crises? A Mixed-Methods Study of Gaming During COVID-19 Lockdowns
Authors: family: Ballou
given: Nick; family: Deterding
given: Sebastian; family: Iacovides
given: Ioanna; family: Helsby
given: Laura
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: mixed methods, coping, Covid-19, compensation, basic needs, video games

Abstract: Do people use games to cope with adverse life events and crises? Research informed by self-determination theory proposes that people might compensate for thwarted basic psychological needs in daily life by seeking out games that satisfy those lacking needs. To test this, we conducted a preregistered mixed-method survey study (n = 285) on people’s gaming behaviours and need states during early stages of the COVID-19 pandemic (May 2020). We found qualitative evidence that gaming was an often actively sought out and successful means of replenishing particular needs, but one that could ‘backfire’ for some through an appraisal process discounting gaming as ‘unreal’. Meanwhile, contrary to our predictions, the quantitative data showed a “rich get richer, poor get poorer” pattern: need satisfaction in daily life positively correlated with need satisfaction in games. We derive methodological considerations and propose three potential explanations for this contradictory data pattern to pursue in future research.
Title: Designing for Noticeability: Understanding the Impact of Visual Importance on Desktop Notifications
Authors: family: Müller
given: Philipp; family: Staal
given: Sander; family: Bâce
given: Mihai; family: Bulling
given: Andreas
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: notifications, attention, graphical user interfaces, dual task performance

Abstract: Desktop notifications should be noticeable but are also subject to a number of design choices, e.g. concerning their size, placement, or opacity. It is currently unknown, however, how these choices interact with the desktop background and their influence on noticeability. To address this limitation, we introduce a software tool to automatically synthesize realistically looking desktop images for major operating systems and applications. Using these images, we present a user study (N=34) to investigate the noticeability of notifications during a primary task. We are first to show that visual importance of the background at the notification location significantly impacts whether users detect notifications. We analyse the utility of visual importance to compensate for suboptimal design choices with respect to noticeability, e.g. small notification size. Finally, we introduce noticeability maps - 2D maps encoding the predicted noticeability across the desktop and inform designers how to trade-off notification design and noticeability.
Title: Situational Recommender: Are You On the Spot, Refining Plans, or Just Bored?
Authors: family: Viswanathan
given: Sruthi; family: Boulard
given: Cecile; family: Bruyat
given: Adrien; family: Maria Grasso
given: Antonietta
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: POI Recommender System, CAI, Situation modelling, Situation Aware, User Studies, Mobile Devices, Prototyping, Interaction Design

Abstract: When people engage in urban exploration, the tool they are most likely to use today is a mobile phone. In this paper, we present observations of users’ “home” and “away” conducted to refine our understanding of situational Point-of-Interest (POI) needs. Our findings suggest three distinct categories of situations in which users seek POI information: On-the-spot, Refining plans, and Moments of boredom. Based on the similarities and differences of these three situations in five observed underlying constraints – distance of interest, engagement threshold, ambiguity of the search, profile matching, and other imperative constraints, we derive implications for designing and ranking POIs for a Situational Recommender. To further access our concept, we designed and prototyped Situational Recommender by providing an interactional representation of the situation, and ran a Wizard-of-Oz concept validation study. Our results suggest that participants understood the concept without much effort and appreciated its usefulness.
Title: Will AI Console Me when I Lose my Pet? Understanding Perceptions of AI-Mediated Email Writing
Authors: family: Liu
given: Yihe; family: Mittal
given: Anushk; family: Yang
given: Diyi; family: Bruckman
given: Amy
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Computer-Mediated Communication (CMC), Artificial Intelligence, Trust, Artificial Intelligence-Mediated Communication (AI-MC)

Abstract: Large language models are increasingly mediating, modifying, and even generating messages for users, but the receivers of these messages may not be aware of the involvement of AI. To examine this emerging direction of AI-Mediated Communication (AI-MC), we investigate people’s perceptions of AI written messages. We analyze how such perceptions change in accordance with the interpersonal emphasis of a given message. We conducted both large-scale surveys and in-depth interviews to investigate how a diverse set of factors influence people’s perceived trust in AI-mediated writing of emails. We found that people’s trust in email writers decreased when they were told that AI was involved in the writing process. Surprisingly trust increased when AI was used for writing more interpersonal emails (as opposed to more transactional ones). Our study provides insights regarding how people perceive AI-MC and has practical design implications on building AI-based products to aid human interlocutors in communication1.
Title: Nudging Behavior Change: Using In-Group and Out-Group Social Comparisons to Encourage Healthier Choices
Authors: family: M. DiCosola III
given: Blake; family: Neff
given: Gina
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: food, social influence, health, information design, Consumer behavior, intervention, choice, nudging, decision making, diet, digital shopping, online, nutrition, persuasive communication

Abstract: This paper revisits concepts of nudge in the context of helping consumers to make healthier food choices. We introduce a novel form of social influence nudge not yet investigated by HCI scholars, the out-group social comparison, and test whether this form of nudging works at the point of checkout rather than the more conventional point of product consideration. Across two online experiments, we measure the effectiveness of using nutritional information nudges with added in-group (people like you) and out-group (people not like you) social comparisons. Our preliminary findings suggest that out-group social comparison nudges can be effective in encouraging both normal weight and overweight adults to reduce calories, even when these adults indicate that they do not typically change their diet behaviors. This research has implications for digital information design, interactive marketing, and public health.
Title: Supporting Accessible Data Visualization Through Audio Data Narratives
Authors: family: Siu
given: Alexa; family: S-H Kim
given: Gene; family: O'Modhrain
given: Sile; family: Follmer
given: Sean
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: sonification, data narratives, accessibility, data visualization

Abstract: Online data visualizations play an important role in informing public opinion but are often inaccessible to screen reader users. To address the need for accessible data representations on the web that provide direct, multimodal, and up-to-date access to the data, we investigate audio data narratives –which combine textual descriptions and sonification (the mapping of data to non-speech sounds). We conduct two co-design workshops with screen reader users to define design principles that guide the structure, content, and duration of a data narrative. Based on these principles and relevant auditory processing characteristics, we propose a dynamic programming approach to automatically generate an audio data narrative from a given dataset. We evaluate our approach with 16 screen reader users. Findings show with audio narratives, users gain significantly more insights from the data. Users describe data narratives help them better extract and comprehend the information in both the sonification and description.
Title: Slide-Tone and Tilt-Tone: 1-DOF Haptic Techniques for Conveying Shape Characteristics of Graphs to Blind Users
Authors: family: Fan
given: Danyang; family: Siu
given: Alexa Fay; family: Law
given: Wing-Sum Adrienne; family: Zhen
given: Raymond Ruihong; family: O'Modhrain
given: Sile; family: Follmer
given: Sean
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: haptic data visualization, accessible data visualization, accessibility

Abstract: We increasingly rely on up-to-date, data-driven graphs to understand our environments and make informed decisions. However, many of the methods blind and visually impaired users (BVI) rely on to access data-driven information do not convey important shape-characteristics of graphs, are not refreshable, or are prohibitively expensive. To address these limitations, we introduce two refreshable, 1-DOF audio-haptic interfaces based on haptic cues fundamental to object shape perception. Slide-tone uses finger position with sonification, and Tilt-tone uses fingerpad contact inclination with sonification to provide shape feedback to users. Through formative design workshops (n = 3) and controlled evaluations (n = 8), we found that BVI participants appreciated the additional shape information, versatility, and reinforced understanding these interfaces provide; and that task accuracy was comparable to using interactive tactile graphics or sonification alone. Our research offers insight into the benefits, limitations, and considerations for adopting these haptic cues into a data visualization context.
Title: VoxLens: Making Online Data Visualizations Accessible with an Interactive JavaScript Plug-In
Authors: family: Sharif
given: Ather; family: Wang
given: Olivia H.; family: Muongchan
given: Alida T.; family: Reinecke
given: Katharina; family: Wobbrock
given: Jacob O.
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Visualizations, screen readers, low-vision., blind, accessibility, voice-based interaction

Abstract: JavaScript visualization libraries are widely used to create online data visualizations but provide limited access to their information for screen-reader users. Building on prior findings about the experiences of screen-reader users with online data visualizations, we present VoxLens, an open-source JavaScript plug-in that—with a single line of code—improves the accessibility of online data visualizations for screen-reader users using a multi-modal approach. Specifically, VoxLens enables screen-reader users to obtain a holistic summary of presented information, play sonified versions of the data, and interact with visualizations in a “drill-down” manner using voice-activated commands. Through task-based experiments with 21 screen-reader users, we show that VoxLens improves the accuracy of information extraction and interaction time by 122% and 36%, respectively, over existing conventional interaction with online data visualizations. Our interviews with screen-reader users suggest that VoxLens is a “game-changer” in making online data visualizations accessible to screen-reader users, saving them time and effort.
Title: Infosonics: Accessible Infographics for People who are Blind using Sonification and Voice
Authors: family: Holloway
given: Leona M; family: Goncu
given: Cagatay; family: Ilsar
given: Alon; family: Butler
given: Matthew; family: Marriott
given: Kim
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: sonification, low vision, Blind, information access, accessible graphics

Abstract: Data visualisations are increasingly used online to engage readers and enable independent analysis of the data underlying news stories. However, access to such infographics is problematic for readers who are blind or have low vision (BLV). Equitable access to information is a basic human right and essential for independence and inclusion. We introduce infosonics, the audio equivalent of infographics, as a new style of interactive sonification that uses a spoken introduction and annotation, non-speech audio and sound design elements to present data in an understandable and engaging way. A controlled user evaluation with 18 BLV adults found a COVID-19 infosonic enabled a clearer mental image than a traditional sonification. Further, infosonics prove complementary to text descriptions and facilitate independent understanding of the data. Based on our findings, we provide preliminary suggestions for infosonics design, which we hope will enable BLV people to gain equitable access to online news and information.
Title: Solving Separation-of-Concerns Problems in Collaborative Design of Human-AI Systems through Leaky Abstractions
Authors: family: Subramonyam
given: Hariharan; family: Im
given: Jane; family: Seifert
given: Colleen; family: Adar
given: Eytan
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: design processes, UX design, Industry practices, Human-AI systems, AI applications

Abstract: In conventional software development, user experience (UX) designers and engineers collaborate through separation of concerns (SoC): designers create human interface specifications, and engineers build to those specifications. However, we argue that Human-AI systems thwart SoC because human needs must shape the design of the AI interface, the underlying AI sub-components, and training data. How do designers and engineers currently collaborate on AI and UX design? To find out, we interviewed 21 industry professionals (UX researchers, AI engineers, data scientists, and managers) across 14 organizations about their collaborative work practices and associated challenges. We find that hidden information encapsulated by SoC challenges collaboration across design and engineering concerns. Practitioners describe inventing ad-hoc representations exposing low-level design and implementation details (which we characterize as leaky abstractions) to “puncture” SoC and share information across expertise boundaries. We identify how leaky abstractions are employed to collaborate at the AI-UX boundary and formalize a process of creating and using leaky abstractions.
Title: CO/DA: Live-Coding Movement-Sound Interactions for Dance Improvisation
Authors: family: Françoise
given: Jules; family: Fdili Alaoui
given: Sarah; family: Candau
given: Yves
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Improvisation, Live Coding, Movement, Design., Embodied Interaction, Dance

Abstract: We present a performance-led inquiry that involved a live coder programming movement-based interactive sound and two dance improvisers. During two years of collaboration, we developed a joint improvisation practice where the interactions between the dancers’ movement and the sound feedback are programmed on the fly through live coding and movement sensing. To that end, we designed a new live coding environment called CO/DA that facilitates the real-time manipulation of continuous streams of the dancers’ motion data for interactive sound synthesis. Through an autoethnographic inquiry, we describe our practice of sound and movement improvisation where live coding dynamically changes how the dancers’ movements generate sound, which in turn influences the dancers’ improvisation. We then discuss the value, potential and challenges of our dance/code improvisation practice, along with its implications as a design method.
Title: How Experienced Designers of Enterprise Applications Engage AI as a Design Material
Authors: family: Yildirim
given: Nur; family: Kass
given: Alex; family: Tung
given: Teresa; family: Upton
given: Connor; family: Costello
given: Donnacha; family: Giusti
given: Robert; family: Lacin
given: Sinem; family: Lovic
given: Sara; family: O'Neill
given: James M; family: Meehan
given: Rudi O'Reilly; family: Ó Loideáin
given: Eoin; family: Pini
given: Azzurra; family: Corcoran
given: Medb; family: Hayes
given: Jeremiah; family: Cahalane
given: Diarmuid J; family: Shivhare
given: Gaurav; family: Castoro
given: Luigi; family: Caruso
given: Giovanni; family: Oh
given: Changhoon; family: McCann
given: James; family: Forlizzi
given: Jodi; family: Zimmerman
given: John
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: User experience, artificial intelligence, design, machine learning

Abstract: HCI research has explored AI as a design material, suggesting that designers can envision AI’s design opportunities to improve UX. Recent research claimed that enterprise applications offer an opportunity for AI innovation at the user experience level. We conducted design workshops to explore the practices of experienced designers who work on cross-functional AI teams in the enterprise. We discussed how designers successfully work with and struggle with AI. Our findings revealed that designers can innovate at the system and service levels. We also discovered that making a case for an AI feature’s return on investment is a barrier for designers when they propose AI concepts and ideas. Our discussions produced novel insights on designers’ role on AI teams, and the boundary objects they used for collaborating with data scientists. We discuss the implications of these findings as opportunities for future research aiming to empower designers in working with data and AI.
Title: Six Facets of Facilitation: Participatory Design Facilitators’ Perspectives on Their Role and Its Realization
Authors: family: Dahl
given: Yngve; family: Sharma
given: Kshitij
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: role, Participation, facilitation, reflection

Abstract: Participatory design facilitators have a significant impact on participatory activities, processes, and outcomes. However, the facilitator role has not yet been thoroughly debated in existing design discourse, and support for role-related reflections is limited. As the first steps towards an enriched collective understanding of this specific role and its realization, we interviewed 14 respondents with an academic background in participatory design and extensive facilitation experience. Based on a content analysis of the interviews, we identified six facets of the role: (1) trust builder, (2) enabler, (3) inquirer, (4) direction setter, (5) value provider, and (6) users’ advocate. Each facet is presented as consisting of the respondents’ perceived associated responsibilities and corresponding strategies. Our results paint a complex picture of participatory design facilitation. We propose the multi-faceted understanding of the facilitator role emerging from this work as a basis for problematized reflection on the role and its realization.
Title: Critical-Playful Speculations with Cameras in the Home
Authors: family: H. Tan
given: Neilly; family: Kinnee
given: Brian; family: Langseth
given: Dana; family: A. Munson
given: Sean; family: Desjardins
given: Audrey
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: domestic technology, privacy, smart cameras, personal data, Internet of Things, home, Design research, speculative, enactments

Abstract: Smart home cameras present new challenges for understanding behaviors and relationships surrounding always-on, domestic recording systems. We designed a series of discursive activities involving 16 individuals from ten households for six weeks in their everyday settings. These activities functioned as speculative probes—prompting participants to reflect on themes of privacy and power through filming with cameras in their households. Our research design foregrounded critical-playful enactments that allowed participants to speculate potentials for relationships with cameras in the home beyond everyday use. We present four key dynamics with participants and home cameras by examining their relationships to: the camera's eye, filming, their data, and camera's societal contexts. We contribute discussions about the mundane, information privacy, and post-hoc reflection with one's camera footage. Overall, our findings reveal the camera as a strange, yet banal entity in the home—interrogating how participants compose and handle their own and others’ video data.