Computer Science

Growing up in an artificial intelligence-filled world, with Siri and Amazon Alexa often within arm's - or speech's - reach, could have significant impact on children. Conversational agents could influence how students anthropomorphize computer systems or develop a theory of mind. Previous research has explored how conversational agents are used and perceived by children within and outside of learning contexts. This study investigates how middle and high school students' perceptions of Alexa change through programming their own conversational agents in week-long AI education workshops. Specifically, we investigate the workshops' influence on student perceptions of Alexa's intelligence, friendliness, aliveness, safeness, trustworthiness, human-likeness, and feelings of closeness. We found that students felt Alexa was more intelligent and felt closer to Alexa after the workshops. We also found strong correlations between students' perceptions of Alexa's friendliness and trustworthiness, and safeness and trustworthiness. Finally, we explored how students tended to more frequently use computer science-related diction and ideas after the workshops. Based on our findings, we recommend designers carefully consider personification, transparency, playfulness and utility when designing CAs for learning contexts.

Artificial intelligence (AI) technology has been increasingly used in the implementation of advanced Clinical Decision Support Systems (CDSS). Research demonstrated the potential usefulness of AI-powered CDSS (AI-CDSS) in clinical decision making scenarios. However, post-adoption user perception and experience remain understudied, especially in developing countries. Through observations and interviews with 22 clinicians from 6 rural clinics in China, this paper reports the various tensions between the design of an AI-CDSS system ("Brilliant Doctor") and the rural clinical context, such as the misalignment with local context and workflow, the technical limitations and usability barriers, as well as issues related to transparency and trustworthiness of AI-CDSS. Despite these tensions, all participants expressed positive attitudes toward the future of AI-CDSS, especially acting as "a doctor's AI assistant" to realize a Human-AI Collaboration future in clinical settings. Finally we draw on our findings to discuss implications for designing AI-CDSS interventions for rural clinical contexts in developing countries.

Haptic feedback has become crucial to enhance the user experiences in Virtual Reality (VR). This justifies the sudden burst of novel haptic solutions proposed these past years in the HCI community. This article is a survey of Virtual Reality interactions, relying on haptic devices. We propose two dimensions to describe and compare the current haptic solutions: their degree of physicality, as well as their degree of actuation. We depict a compromise between the user and the designer, highlighting how the range of required or proposed stimulation in VR is opposed to the haptic interfaces flexibility and their deployment in real-life use-cases. This paper (1) outlines the variety of haptic solutions and provides a novel perspective for analysing their associated interactions, (2) highlights the limits of the current evaluation criteria regarding these interactions, and finally (3) reflects the interaction, operation and conception potentials of "encountered-type of haptic devices".

Social interaction across multiple online platforms is a challenge for gender and sexual minorities (GSM) due to the stigmatization they face, which increases the complexity of their self-presentation decisions. These online interactions and identity disclosures can be more complicated for GSM in non-Western contexts due to consequentially different audiences and perceived affordances by the users, and limited baseline understanding of the conflation of these two with local norms and the opportunities they practically represent. Using focus group discussions and semi-structured interviews, we engaged with 61 \textit{Hijra} individuals from Bangladesh, a severely stigmatized GSM from south Asia, to understand their overall online participation and disclosure behaviors through the lens of personal social media ecosystems. We find that along with platform audiences, affordances, and norms, participant skill/knowledge, and cultural influences also impact navigation through multiple platforms, resulting in differential benefits from privacy features. This impacts how Hijra perceive online spaces, and shape their self-presentation and disclosure behaviors over time. Content Warning: This paper discusses graphic contents (e.g. rape and sexual harassment) related to Hijra.

In this workshop paper, we use an empirical example from our ongoing fieldwork, to showcase the complexity and situatedness of the process of making sense of algorithmic results; i.e. how to evaluate, validate, and contextualize algorithmic outputs. So far, in our research work, we have focused on such sense-making processes in data analytic learning environments such as classrooms and training workshops. Multiple moments in our fieldwork suggest that meaning, in data analytics, is constructed through an iterative and reflexive dialogue between data, code, assumptions, prior knowledge, and algorithmic results. A data analytic result is nothing short of a sociotechnical accomplishment - one in which it is extremely difficult, if not at times impossible, to clearly distinguish between 'human' and 'technical' forms of data analytic work. We conclude this paper with a set of questions that we would like to explore further in this workshop.

While developments in 3D printing have opened up opportunities for improved access to graphical information for people who are blind or have low vision (BLV), they can provide only limited detailed and contextual information. Interactive 3D printed models (I3Ms) that provide audio labels and/or a conversational agent interface potentially overcome this limitation. We conducted a Wizard-of-Oz exploratory study to uncover the multi-modal interaction techniques that BLV people would like to use when exploring I3Ms, and investigated their attitudes towards different levels of model agency. These findings informed the creation of an I3M prototype of the solar system. A second user study with this model revealed a hierarchy of interaction, with BLV users preferring tactile exploration, followed by touch gestures to trigger audio labels, and then natural language to fill in knowledge gaps and confirm understanding.

Despite the potential benefits of assistive technologies (ATs) for people with various disabilities, only around 7% of Chinese with disabilities have had an opportunity to use ATs. Even for those who have used ATs, the abandonment rate was high. Although China has the world's largest population with disabilities, prior research exploring how ATs are used and perceived, and why ATs are abandoned have been conducted primarily in North America and Europe. In this paper, we present an interview study conducted in China with 26 people with various disabilities to understand their practices, challenges, perceptions, and misperceptions of using ATs. From the study, we learned about factors that influence AT adoption practices (e.g., misuse of accessible infrastructure, issues with replicating existing commercial ATs), challenges using ATs in social interactions (e.g., Chinese stigma), and misperceptions about ATs (e.g., ATs should overcome inaccessible social infrastructures). Informed by the findings, we derive a set of design considerations to bridge the existing gaps in AT design (e.g., manual vs. electronic ATs) and to improve ATs' social acceptability in China.

TikTok is a music-based video sharing social media app famous for users creating short meme and dance videos. TikTok videos are largely based on popular song snippets, which is why lip syncing and dance moves evolve as significant user performance practices in videos. User prosumption has not yet been studied regarding the characteristics of TikTok. This paper is based on social practice and performance theory, social media studies, and participatory online video culture. It uses the #distantdance challenge on TikTok to analyze production practices and strategies of users through qualitative video product analysis. 92 videos were coded and categorized regarding their visual content (who participated in which way) and paratextual elements (used tags and captions). The visual and (para-)textual elements were then analyzed regarding indicators that allow to draw conclusions on users' video creation strategies and performance practices in participating in the #distantdance challenge. The results show videos are mainly performed by single white female teenagers wearing casual outfits in their bedrooms. Users shared their experiences about learning and performing the dance in video captions. While users prepared settings and outfits for their performance, the majority of performances seems rather unplanned or spontaneous. This indicates most videos might be part of a series of user attempts to master the dance challenge resulting in posting the first successful video performance to TikTok. In addition to the dance moves, participants also added gestures as closing elements to their performances. This indicates their knowledge of using signals as part of an online community while at the same time manifesting their belongingness to the community. These first results of a qualitative product analysis illustrate some of users' motivations and effort to participate in TikTok dance challenges.

Loneliness threatens public mental wellbeing during COVID-19. In response, YouTube creators participated in the #StayHome #WithMe movement (SHWM) and made myriad videos for people experiencing loneliness or boredom at home. User-shared videos generate parasocial attachment and virtual connectedness. However, there is limited knowledge of how creators contributed videos during disasters to provide social provisions as disaster-relief. Grounded on Weiss's loneliness theory, this work analyzed 1488 SHWM videos to examine video sharing as a pathway to social provisions. Findings suggested that skill and knowledge sharing, entertaining arts, homelife activities, live chatting, and gameplay were the most popular video styles. YouTubers utilized parasocial relationships to form a space for staying away from the disaster. SHWM YouTubers provided friend-like, mentor-like, and family-like provisions through videos in different styles. Family-like provisions led to the highest overall viewer engagement. Based on the findings, design implications for supporting viewers' mental wellbeing in disasters are discussed.

With the rise of voice assistants and an increase in mobile search usage, natural language has become an important query language. So far, most of the current systems are not able to process these queries because of the vagueness and ambiguity in natural language. Users have adapted their query formulation to what they think the search engine is capable of, which adds to their cognitive burden. With our research, we contribute to the design of interactive search systems by investigating the genuine information need in a product search scenario. In a crowd-sourcing experiment, we collected 132 information needs in natural language. We examine the vagueness of the formulations and their match to retailer-generated content and user-generated product reviews. Our findings reveal high variance on the level of vagueness and the potential of user reviews as a source for supporting users with rather vague search intents.