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Katie Seaborn

Publications and source records attributed to Katie Seaborn.

At least 37 records · Page 2Linked to original sources

Kawaii Computing: Scoping Out the Japanese Notion of Cute in User Experiences with Interactive Systems

Kawaii computing is a new term for a steadily growing body of work on the Japanese notion of "cute" in human-computer interaction (HCI) research and practice. Kawaii is distinguished from general notions of cute by its experiential and culturally-sensitive nature. While it can be designed into the appearance and behaviour of interactive agents, interfaces, and systems, kawaii also refers to certain affective and cultural dimensions experienced by culturally Japanese users, i.e., kawaii user experiences (UX) and mental models of kawaii elicited by the socio-cultural context of Japan. In this scoping review, we map out the ways in which kawaii has been explored within HCI research and related fields as a factor of design and experience. We illuminate theoretical and methodological gaps and opportunities for future work on kawaii computing.

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Deceptive, Disruptive, No Big Deal: Japanese People React to Simulated Dark Commercial Patterns

Dark patterns and deceptive designs (DPs) are user interface elements that trick people into taking actions that benefit the purveyor. Such designs are widely deployed, with special varieties found in certain nations like Japan that can be traced to global power hierarchies and the local socio-linguistic context of use. In this breaking work, we report on the first user study involving Japanese people (n=30) experiencing a mock shopping website injected with simulated DPs. We found that Alphabet Soup and Misleading Reference Pricing were the most deceptive and least noticeable. Social Proofs, Sneaking in Items, and Untranslation were the least deceptive but Untranslation prevented most from cancelling their account. Mood significantly worsened after experiencing the website. We contribute the first empirical findings on a Japanese consumer base alongside a scalable approach to evaluating user attitudes, perceptions, and behaviours towards DPs in an interactive context. We urge for more human participant research and ideally collaborations with industry to assess real designs in the wild.

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Play Across Boundaries: Exploring Cross-Cultural Maldaimonic Game Experiences

Maldaimonic game experiences occur when people engage in personally fulfilling play through egocentric, destructive, and/or exploitative acts. Initial qualitative work verified this orientation and experiential construct for English-speaking Westerners. In this comparative mixed methods study, we explored whether and how maldaimonic game experiences and orientations play out in Japan, an Eastern gaming capital that may have cultural values incongruous with the Western philosophical basis underlying maldaimonia. We present findings anchored to the initial frameworks on maldaimonia in game experiences that show little divergence between the Japanese and US cohorts. We also extend the qualitative findings with quantitative measures on affect, player experience, and the related constructs of hedonia and eudaimonia. We confirm this novel construct for Japan and set the stage for scale development.

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Silver-Tongued and Sundry: Exploring Intersectional Pronouns with ChatGPT

ChatGPT is a conversational agent built on a large language model. Trained on a significant portion of human output, ChatGPT can mimic people to a degree. As such, we need to consider what social identities ChatGPT simulates (or can be designed to simulate). In this study, we explored the case of identity simulation through Japanese first-person pronouns, which are tightly connected to social identities in intersectional ways, i.e., intersectional pronouns. We conducted a controlled online experiment where people from two regions in Japan (Kanto and Kinki) witnessed interactions with ChatGPT using ten sets of first-person pronouns. We discovered that pronouns alone can evoke perceptions of social identities in ChatGPT at the intersections of gender, age, region, and formality, with caveats. This work highlights the importance of pronoun use for social identity simulation, provides a language-based methodology for culturally-sensitive persona development, and advances the potential of intersectional identities in intelligent agents.

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Qualitative Approaches to Voice UX

Voice is a natural mode of expression offered by modern computer-based systems. Qualitative perspectives on voice-based user experiences (voice UX) offer rich descriptions of complex interactions that numbers alone cannot fully represent. We conducted a systematic review of the literature on qualitative approaches to voice UX, capturing the nature of this body of work in a systematic map and offering a qualitative synthesis of findings. We highlight the benefits of qualitative methods for voice UX research, identify opportunities for increasing rigour in methods and outcomes, and distill patterns of experience across a diversity of devices and modes of qualitative praxis.

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Coimagining the Future of Voice Assistants with Cultural Sensitivity

Voice assistants (VAs) are becoming a feature of our everyday life. Yet, the user experience (UX) is often limited, leading to underuse, disengagement, and abandonment. Co-designing interactions for VAs with potential end-users can be useful. Crowdsourcing this process online and anonymously may add value. However, most work has been done in the English-speaking West on dialogue data sets. We must be sensitive to cultural differences in language, social interactions, and attitudes towards technology. Our aims were to explore the value of co-designing VAs in the non-Western context of Japan and demonstrate the necessity of cultural sensitivity. We conducted an online elicitation study (N = 135) where Americans (n = 64) and Japanese people (n = 71) imagined dialogues (N = 282) and activities (N = 73) with future VAs. We discuss the implications for coimagining interactions with future VAs, offer design guidelines for the Japanese and English-speaking US contexts, and suggest opportunities for cultural plurality in VA design and scholarship.

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Super Synthesis Pros., or why CHI PLAY needs research synthesis

Games user research is a-booming -- or maybe a-goomba-ing -- with a boundless parade of papers popping up from every nook and pipe. We may need a super power -- or super method -- from another world. I outline three motivations for jump-starting research synthesis in games user research. I argue that: research synthesis will validate this field of study and enrich primary research (meta-scholarship); we must level up both primary and secondary research (education); and we should reflect this epistemological stance in community structures and adopt established tools and protocols (standardization). I offer power-ups to get the toads rolling.

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Link, user-centred designer: Game characters as transcendent models

Games allow us to construct and explore identities and offer us role models, good and bad. Game characters are a reflection of us -- players and creators alike -- or could be. But do games also encode identities, values, and orientations that transcend diegetic categories and player self-insertion? I explore the notion of game characters as conduits of transcendent models through the case study of Link from the Legend of Zelda series. I propose that designers embed tacit, nondiegetic patterns of praxis and complex value models, such as user-centred design, when crafting the embodiment of characters in gameplay, even unawares.

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Meaningful play and malicious delight: Exploring maldaimonic game UX

Maldaimonia is a new experiential concept that refers to self-actualization and self-expression through egocentric, destructive, and/or exploitative activities. Still, it is unclear whether maldaimonia is an actual facet of real experience. As a subversive orientation, it may be rare or socially challenging to discuss openly. However, video games provide a space in which people can be expressive in different ways without the same repercussions as in real life. Indeed, game spaces may be one of the few contexts in which to study maldaimonic experiences. In this study, we examined whether and how maldaimonia exists as a feature of game user experiences by analyzing critical self-reports of gaming activities, confirming its existence. We contribute this new construct to work on "dark play" in games research.

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Kawaii Game Vocalics: A Preliminary Model

Kawaii is the Japanese concept of cute++, a global export with local characteristics. Recent work has explored kawaii as a feature of user experience (UX) with social robots, virtual characters, and voice assistants, i.e., kawaii vocalics. Games have a long history of incorporating characters that use voice as a means of expressing kawaii. Nevertheless, no work to date has evaluated kawaii game voices or mapped out a model of kawaii game vocalics. In this work, we explored whether and how a model of kawaii vocalics maps onto game character voices. We conducted an online perceptions study (N=157) using 18 voices from kawaii characters in Japanese games. We replicated the results for computer voice and discovered nuanced relationships between gender and age, especially youthfulness, agelessness, gender ambiguity, and gender neutrality. We provide our initial model and advocate for future work on character visuals and within play contexts.

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Linguistic Dead-Ends and Alphabet Soup: Finding Dark Patterns in Japanese Apps

Dark patterns are deceptive and malicious properties of user interfaces that lead the end-user to do something different from intended or expected. While now a key topic in critical computing, most work has been conducted in Western contexts. Japan, with its booming app market, is a relatively uncharted context that offers culturally- and linguistically-sensitive differences in design standards, contexts of use, values, and language, all of which could influence the presence and expression of dark patterns. In this work, we analyzed 200 popular mobile apps in the Japanese market. We found that most apps had dark patterns, with an average of 3.9 per app. We also identified a new class of dark pattern: "Linguistic Dead-Ends" in the forms of "Untranslation" and "Alphabet Soup." We outline the implications for design and research practice, especially for future cross-cultural research on dark patterns.

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Transcending the "Male Code": Implicit Masculine Biases in NLP Contexts

Critical scholarship has elevated the problem of gender bias in data sets used to train virtual assistants (VAs). Most work has focused on explicit biases in language, especially against women, girls, femme-identifying people, and genderqueer folk; implicit associations through word embeddings; and limited models of gender and masculinities, especially toxic masculinities, conflation of sex and gender, and a sex/gender binary framing of the masculine as diametric to the feminine. Yet, we must also interrogate how masculinities are "coded" into language and the assumption of "male" as the linguistic default: implicit masculine biases. To this end, we examined two natural language processing (NLP) data sets. We found that when gendered language was present, so were gender biases and especially masculine biases. Moreover, these biases related in nuanced ways to the NLP context. We offer a new dictionary called AVA that covers ambiguous associations between gendered language and the language of VAs.

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The Systematic Review-lution: A Manifesto to Promote Rigour and Inclusivity in Research Synthesis

The field of human-computer interaction (HCI) is maturing. Systematic reviews, a staple of many disciplines, play an important and often essential role in how each field contributes to human knowledge. On this prospect, we argue that our meta-level approach to research within HCI needs a revolution. First, we echo previous calls for greater rigour in primary research reporting with a view towards supporting knowledge synthesis in secondary research. Second, we must decide as a community how to carry out systematic review work in light of the many ways that knowledge is produced within HCI (rigour in secondary research methods and epistemological inclusivity). In short, our manifesto is this: we need to develop and make space for an inclusive but rigorous set of standards that supports systematic review work in HCI, through careful consideration of both primary and secondary research methods, expectations, and infrastructure. We call for any and all fellow systematic review-lutionaries to join us.

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Dis/Immersion in Mindfulness Meditation with a Wandering Voice Assistant

Mindfulness meditation is a validated means of helping people manage stress. Voice-based virtual assistants (VAs) in smart speakers, smartphones, and smart environments can assist people in carrying out mindfulness meditation through guided experiences. However, the common fixed location embodiment of VAs makes it difficult to provide intuitive support. In this work, we explored the novel embodiment of a "wandering voice" that is co-located with the user and "moves" with the task. We developed a multi-speaker VA embedded in a yoga mat that changes location along the body according to the meditation experience. We conducted a qualitative user study in two sessions, comparing a typical fixed smart speaker to the wandering VA embodiment. Thick descriptions from interviews with twelve people revealed sometimes simultaneous experiences of immersion and dis-immersion. We offer design implications for "wandering voices" and a new paradigm for VA embodiment that may extend to guidance tasks in other contexts.

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Can Voice Assistants Sound Cute? Towards a Model of Kawaii Vocalics

The Japanese notion of "kawaii" or expressions of cuteness, vulnerability, and/or charm is a global cultural export. Work has explored kawaii-ness as a design feature and factor of user experience in the visual appearance, nonverbal behaviour, and sound of robots and virtual characters. In this initial work, we consider whether voices can be kawaii by exploring the vocal qualities of voice assistant speech, i.e., kawaii vocalics. Drawing from an age-inclusive model of kawaii, we ran a user perceptions study on the kawaii-ness of younger- and older-sounding Japanese computer voices. We found that kawaii-ness intersected with perceptions of gender and age, i.e., gender ambiguous and girlish, as well as VA features, i.e., fluency and artificiality. We propose an initial model of kawaii vocalics to be validated through the identification and study of vocal qualities, cognitive appraisals, behavioural responses, and affective reports.

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"I'm" Lost in Translation: Pronoun Missteps in Crowdsourced Data Sets

As virtual assistants continue to be taken up globally, there is an ever-greater need for these speech-based systems to communicate naturally in a variety of languages. Crowdsourcing initiatives have focused on multilingual translation of big, open data sets for use in natural language processing (NLP). Yet, language translation is often not one-to-one, and biases can trickle in. In this late-breaking work, we focus on the case of pronouns translated between English and Japanese in the crowdsourced Tatoeba database. We found that masculine pronoun biases were present overall, even though plurality in language was accounted for in other ways. Importantly, we detected biases in the translation process that reflect nuanced reactions to the presence of feminine, neutral, and/or non-binary pronouns. We raise the issue of translation bias for pronouns and offer a practical solution to embed plurality in NLP data sets.

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Trust and Reliance in Consensus-Based Explanations from an Anti-Misinformation Agent

The illusion of consensus occurs when people believe there is consensus across multiple sources, but the sources are the same and thus there is no "true" consensus. We explore this phenomenon in the context of an AI-based intelligent agent designed to augment metacognition on social media. Misinformation, especially on platforms like Twitter, is a global problem for which there is currently no good solution. As an explainable AI (XAI) system, the agent provides explanations for its decisions on the misinformed nature of social media content. In this late-breaking study, we explored the roles of trust (attitude) and reliance (behaviour) as key elements of XAI user experience (UX) and whether these influenced the illusion of consensus. Findings show no effect of trust, but an effect of reliance on consensus-based explanations. This work may guide the design of anti-misinformation systems that use XAI, especially the user-centred design of explanations.

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Interacting with Masculinities: A Scoping Review

Gender is a hot topic in the field of human-computer interaction (HCI). Work has run the gamut, from assessing how we embed gender in our computational creations to correcting systemic sexism, online and off. While gender is often framed around women and femininities, we must recognize the genderful nature of humanity, acknowledge the evasiveness of men and masculinities, and avoid burdening women and genderful folk as the central actors and targets of change. Indeed, critical voices have called for a shift in focus to masculinities, not only in terms of privilege, power, and patriarchal harms, but also participation, plurality, and transformation. To this end, I present a 30-year history of masculinities in HCI work through a scoping review of 126 papers published to the ACM Human Factors in Computing Systems (CHI) conference proceedings. I offer a primer and agenda grounded in the CHI and extant literatures to direct future work.

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