arXiv subjects

Katie Seaborn

Publications and source records attributed to Katie Seaborn.

At least 19 recordsLinked to original sources

arXiv2026

Unease, Ambivalence, and Endured Disloyalty in Japanese Consumer Experiences with Dark Commercial Patterns

Dark commercial patterns and deceptive user interface (UI) designs (or DPs) trick consumers into actions that benefit the shareholders. The legal and ethical implications of DPs are shaped by the sociocultural context. Special types of DPs exist in Japan, but the impact of these DPs on consumer attitudes and behaviour remains underexplored. We report on the first comparative mixed methods user study with Japanese consumers (N = 84), half of whom (n = 40) experienced a range of DPs---including the Japanese varieties---in a simulated e-commerce website. We discovered that the Japanese DPs were among the least noticeable and caused the highest simulated financial harm, with Untranslation perceived as highly disruptive and Alphabet Soup highly deceptive. Comparative analyses with a group that experienced the DP-free version of the online store (N = 44) revealed a sharp negative difference in positive emotions and acceptance. Qualitative analyses surfaced cultural norms in consumer-business relationships, notably unease, ambivalence, and endured disloyalty (fuseijitsu). No evidence of sampling biases was found for the participants involved in a publicly broadcast programme on the study (n = 10), indicating true deception and unacceptability. Our findings suggest that while reactions toward and ability to recognize a given DP may vary across individuals, the mere presence of DPs tends to have negative effects on most Japanese consumers.

cs.HC↗

arXiv2026

Validating the Single Item Kawaii Measure

Kawaii is the Japanese instantiation of cuteness. As a multimodal percept theoretically derived from the notion of baby schema, kawaii can be a property of voice and sound, visual appearance and form factor, and movement and expression. However, measuring user perceptions of kawaii remains an open question. In the absence of a validated instrument, a one-item self-report measure has been used extensively, but has not been validated. Here, we report on three types of validity -- convergent, known groups, and cross-context -- and reliability for the single item measure across nine data sets featuring responses to video game character voices and visual appearances and computer-generated voice assistant voices from N=967 unique participants. Our results demonstrate initial evidence of the validity of the one-item measure for voice and visual kawaii perceptions. Further rigour can be pursued with novel stimuli, test-retest validation, and concurrent validity against the upcoming multi-item measure of kawaii.

cs.HC↗

arXiv2026

Operationalizing Perceptions of Agent Gender: Foundations and Guidelines

The "gender" of intelligent agents, virtual characters, social robots, and other agentic machines has emerged as a fundamental topic in studies of people's interactions with computers. Perceptions of agent gender can help explain user attitudes and behaviours -- from preferences to toxicity to stereotyping -- across a variety of systems and contexts of use. Yet, standards in capturing perceptions of agent gender do not exist. A scoping review was conducted to clarify how agent gender has been operationalized -- labelled, defined, and measured -- as a perceptual variable. One-third of studies manipulated but did not measure agent gender. Norms in operationalizations remain obscure, limiting comprehension of results, congruity in measurement, and comparability for meta-analyses. The dominance of the gender binary model and latent anthropocentrism have placed arbitrary limits on knowledge generation and reified the status quo. We contribute a systematically-developed and theory-driven meta-level framework that offers operational clarity and practical guidance for greater rigour and inclusivity.

cs.HC↗

arXiv2026

Radical Gender Neutrality: Agender Euphoria in Gaming and Play Experiences

Agender euphoria is a new term representing the powerful feelings of happiness, joy, and contentment derived from experiences in gender-free embodiments, spaces, and activities. People with and without agender and adjacent identities (e.g., genderless, gender-free, non-binary, gender-apathetic) may have such experiences under the right circumstances. Video games can offer gender minorities a safe haven for gender euphoric experiences. However, the possibility of agender euphoric experiences was unexplored. We considered this overlooked frame of self-actualization with 142 people who identified as having or desiring agender euphoric experiences. Using the critical incident technique (CIT), we uncovered how games and play experiences create (and inhibit) agender euphoria. We surface this experiential phenomenon and provide empirically-grounded criteria for the design of games to elicit agender euphoric experiences for everyone, but especially agender and agender adjacent players. This work adds to the growing critical literatures on marginalized experiences in games research and human-computer interaction.

cs.HC↗

arXiv2026

Access Over Deception: Fighting Deceptive Patterns through Accessibility

Deceptive patterns, dark patterns, and manipulative user interfaces (UI) are a widely used design strategy that manipulates users to act against their own interests in pursuit of shareholder aims. These patterns may particularly affect people with less education, visual impairments, and older adults. Yet, access is a critical feature of the user experience (UX), development standards, and law. We considered whether and how the Web Content Accessibility Guidelines (WCAG) and related legislation, like the European Accessibility Act (EAA), could act as a tool against deceptive patterns. We used heuristic evaluation to analyze whether and how deceptive patterns violate or conform to these guidelines and legal statutes. Although statistical analysis revealed no significant differences by pattern type, we identified three patterns implicated by the WCAG guidelines: Countdown Timer, Auto-Play, and Hidden Information. We offer this approach as one tool in the fight against UI-based deception and in support of inclusive design.

cs.HC↗

arXiv2025

Juicy Text: Onomatopoeia and Semantic Text Effects for Juicy Player Experiences

Juiciness is visual pizzazz used to improve player experience and engagement in games. Most research has focused on juicy particle effects. However, text effects are also commonly used in games, albeit not always juiced up. One type is onomatopoeia, a well-defined element of human language that has been translated to visual media, such as comic books and games. Another is semantic text, often used to provide performance feedback in games. In this work, we explored the relationship between juiciness and text effects, aiming to replicate juicy user experiences with text-based juice and combining particle and text juice. We show in a multi-phase within-subjects experiment that users rate juicy text effects similarly to particles effects, with comparable performance, and more reliable feedback. We also hint at potential improvement in user experience when both are combined, and how text stimuli may be perceived differently than other visual ones. We contribute empirical findings on the juicy-text connection in the context of visual effects for interactive media.

cs.HC↗

arXiv2025

First Contact with Dark Patterns and Deceptive Designs in Chinese and Japanese Free-to-Play Mobile Games

Mobile games have gained immense popularity due to their accessibility, allowing people to play anywhere, anytime. Dark patterns and deceptive designs (DPs) have been found in these and other gaming platforms within certain cultural contexts. Here, we explored DPs in the onboarding experiences of free-to-play mobile games from China and Japan. We identified several unique patterns and mapped their relative prevalence. We also found that game developers often employ combinations of DPs as a strategy ("DP Combos") and use elements that, while not inherently manipulative, can enhance the impact of known patterns ("DP Enhancers"). Guided by these findings, we then developed an enriched ontology for categorizing deceptive game design patterns into classes and subclasses. This research contributes to understanding deceptive game design patterns and offers insights for future studies on cultural dimensions and ethical game design in general.

cs.HC↗

arXiv2025

Social Identity in Human-Agent Interaction: A Primer

Social identity theory (SIT) and social categorization theory (SCT) are two facets of the social identity approach (SIA) to understanding social phenomena. SIT and SCT are models that describe and explain how people interact with one another socially, connecting the individual to the group through an understanding of underlying psychological mechanisms and intergroup behaviour. SIT, originally developed in the 1970s, and SCT, a later, more general offshoot, have been broadly applied to a range of social phenomena among people. The rise of increasingly social machines embedded in daily life has spurned efforts on understanding whether and how artificial agents can and do participate in SIA activities. As agents like social robots and chatbots powered by sophisticated large language models (LLMs) advance, understanding the real and potential roles of these technologies as social entities is crucial. Here, I provide a primer on SIA and extrapolate, through case studies and imagined examples, how SIT and SCT can apply to artificial social agents. I emphasize that not all human models and sub-theories will apply. I further argue that, given the emerging competence of these machines and our tendency to be taken in by them, we experts may need to don the hat of the uncanny killjoy, for our own good.

physics.soc-ph↗

arXiv2025

Inter(sectional) Alia(s): Ambiguity in Voice Agent Identity via Intersectional Japanese Self-Referents

Conversational agents that mimic people have raised questions about the ethics of anthropomorphizing machines with human social identity cues. Critics have also questioned assumptions of identity neutrality in humanlike agents. Recent work has revealed that intersectional Japanese pronouns can elicit complex and sometimes evasive impressions of agent identity. Yet, the role of other "neutral" non-pronominal self-referents (NPSR) and voice as a socially expressive medium remains unexplored. In a crowdsourcing study, Japanese participants (N = 204) evaluated three ChatGPT voices (Juniper, Breeze, and Ember) using seven self-referents. We found strong evidence of voice gendering alongside the potential of intersectional self-referents to evade gendering, i.e., ambiguity through neutrality and elusiveness. Notably, perceptions of age and formality intersected with gendering as per sociolinguistic theories, especially boku and watakushi. This work provides a nuanced take on agent identity perceptions and champions intersectional and culturally-sensitive work on voice agents.

cs.HC↗

arXiv2025

Super Kawaii Vocalics: Amplifying the "Cute" Factor in Computer Voice

"Kawaii" is the Japanese concept of cute, which carries sociocultural connotations related to social identities and emotional responses. Yet, virtually all work to date has focused on the visual side of kawaii, including in studies of computer agents and social robots. In pursuit of formalizing the new science of kawaii vocalics, we explored what elements of voice relate to kawaii and how they might be manipulated, manually and automatically. We conducted a four-phase study (grand N = 512) with two varieties of computer voices: text-to-speech (TTS) and game character voices. We found kawaii "sweet spots" through manipulation of fundamental and formant frequencies, but only for certain voices and to a certain extent. Findings also suggest a ceiling effect for the kawaii vocalics of certain voices. We offer empirical validation of the preliminary kawaii vocalics model and an elementary method for manipulating kawaii perceptions of computer voice.

cs.HC↗

arXiv2025

More-than-Human Storytelling: Designing Longitudinal Narrative Engagements with Generative AI

Longitudinal engagement with generative AI (GenAI) storytelling agents is a timely but less charted domain. We explored multi-generational experiences with "Dreamsmithy," a daily dream-crafting app, where participants (N = 28) co-created stories with AI narrator "Makoto" every day. Reflections and interactions were captured through a two-week diary study. Reflexive thematic analysis revealed themes likes "oscillating ambivalence" and "socio-chronological bonding," highlighting the complex dynamics that emerged between individuals and the AI narrator over time. Findings suggest that while people appreciated the personal notes, opportunities for reflection, and AI creativity, limitations in narrative coherence and control occasionally caused frustration. The results underscore the potential of GenAI for longitudinal storytelling, but also raise critical questions about user agency and ethics. We contribute initial empirical insights and design considerations for developing adaptive, more-than-human storytelling systems.

cs.HC↗

arXiv2025

ChatGPT and U(X): A Rapid Review on Measuring the User Experience

ChatGPT, powered by a large language model (LLM), has revolutionized everyday human-computer interaction (HCI) since its 2022 release. While now used by millions around the world, a coherent pathway for evaluating the user experience (UX) ChatGPT offers remains missing. In this rapid review (N = 58), I explored how ChatGPT UX has been approached quantitatively so far. I focused on the independent variables (IVs) manipulated, the dependent variables (DVs) measured, and the methods used for measurement. Findings reveal trends, gaps, and emerging consensus in UX assessments. This work offers a first step towards synthesizing existing approaches to measuring ChatGPT UX, urgent trajectories to advance standardization and breadth, and two preliminary frameworks aimed at guiding future research and tool development. I seek to elevate the field of ChatGPT UX by empowering researchers and practitioners in optimizing user interactions with ChatGPT and similar LLM-based systems.

cs.HC↗

arXiv2024

Bots against Bias: Critical Next Steps for Human-Robot Interaction

We humans are biased - and our robotic creations are biased, too. Bias is a natural phenomenon that drives our perceptions and behavior, including when it comes to socially expressive robots that have humanlike features. Recognizing that we embed bias, knowingly or not, within the design of such robots is crucial to studying its implications for people in modern societies. In this chapter, I consider the multifaceted question of bias in the context of humanoid, AI-enabled, and expressive social robots: Where does bias arise, what does it look like, and what can (or should) we do about it. I offer observations on human-robot interaction (HRI) along two parallel tracks: (1) robots designed in bias-conscious ways and (2) robots that may help us tackle bias in the human world. I outline a curated selection of cases for each track drawn from the latest HRI research and positioned against social, legal, and ethical factors. I also propose a set of critical next steps to tackle the challenges and opportunities on bias within HRI research and practice.

cs.RO↗

arXiv2024

Robotic Backchanneling in Online Conversation Facilitation: A Cross-Generational Study

Japan faces many challenges related to its aging society, including increasing rates of cognitive decline in the population and a shortage of caregivers. Efforts have begun to explore solutions using artificial intelligence (AI), especially socially embodied intelligent agents and robots that can communicate with people. Yet, there has been little research on the compatibility of these agents with older adults in various everyday situations. To this end, we conducted a user study to evaluate a robot that functions as a facilitator for a group conversation protocol designed to prevent cognitive decline. We modified the robot to use backchannelling, a natural human way of speaking, to increase receptiveness of the robot and enjoyment of the group conversation experience. We conducted a cross-generational study with young adults and older adults. Qualitative analyses indicated that younger adults perceived the backchannelling version of the robot as kinder, more trustworthy, and more acceptable than the non-backchannelling robot. Finally, we found that the robot's backchannelling elicited nonverbal backchanneling in older participants.

cs.RO↗

arXiv2024

From "Made In" to Mukokuseki: Exploring the Visual Perception of National Identity in Robots

People read human characteristics into the design of social robots, a visual process with socio-cultural implications. One factor may be nationality, a complex social characteristic that is linked to ethnicity, culture, and other factors of identity that can be embedded in the visual design of robots. Guided by social identity theory (SIT), we explored the notion of "mukokuseki," a visual design characteristic defined by the absence of visual cues to national and ethnic identity in Japanese cultural exports. In a two-phase categorization study (n=212), American (n=110) and Japanese (n=92) participants rated a random selection of nine robot stimuli from America and Japan, plus multinational Pepper. We found evidence of made-in and two kinds of mukokuseki effects. We offer suggestions for the visual design of mukokuseki robots that may interact with people from diverse backgrounds. Our findings have implications for robots and social identity, the viability of robotic exports, and the use of robots internationally.

cs.RO↗

arXiv2024

Cross-Cultural Validation of Partner Models for Voice User Interfaces

Recent research has begun to assess people's perceptions of voice user interfaces (VUIs) as dialogue partners, termed partner models. Current self-report measures are only available in English, limiting research to English-speaking users. To improve the diversity of user samples and contexts that inform partner modelling research, we translated, localized, and evaluated the Partner Modelling Questionnaire (PMQ) for non-English speaking Western (German, n=185) and East Asian (Japanese, n=198) cohorts where VUI use is popular. Through confirmatory factor analysis (CFA), we find that the scale produces equivalent levels of goodness-to-fit for both our German and Japanese translations, confirming its cross-cultural validity. Still, the structure of the communicative flexibility factor did not replicate directly across Western and East Asian cohorts. We discuss how our translations can open up critical research on cultural similarities and differences in partner model use and design, whilst highlighting the challenges for ensuring accurate translation across cultural contexts.

cs.HC↗

arXiv2024

No Joke: An Embodied Conversational Agent Greeting Older Adults with Humour or a Smile Unrelated to Initial Acceptance

Embodied conversation agents (ECAs) are increasingly being developed for older adults as assistants or companions. Older adults may not be familiar with ECAs, influencing uptake and acceptability. First impressions can correlate strongly with subsequent judgments, even of computer agents, and could influence acceptance. Using the circumplex model of affect, we developed three versions of an ECA -- laughing, smiling, and neutral in expression -- to evaluate how positive first impressions affect acceptance. Results from 249 older adults indicated no statistically significant effects except for general attitudes towards technology and intelligent agents. This questions the potential of laughter, jokes, puns, and smiles as a method of initial engagement for older adults.

cs.HC↗

arXiv2024

Theorizing Deception: A Scoping Review of Theory in Research on Dark Patterns and Deceptive Design

The issue of dark patterns and deceptive designs (DPs) in everyday interfaces and interactions continues to grow. DPs are manipulative and malicious elements within user interfaces that deceive users into making unintended choices. In parallel, research on DPs has significantly increased over the past two decades. As the field has matured, epistemological gaps have also become a salient and pressing concern. In this scoping review, we assessed the academic work so far -- 51 papers between 2014 to 2023 -- to identify the state of theory in DP research. We identified the key theories employed, examined how these theories have been referenced, and call for enhancing the incorporation of theory into DP research. We also propose broad theoretical foundations to establish a comprehensive and solid base for contextualizing and informing future DP research from a variety of theoretical scopes and lenses.

cs.HC↗