AI systems are increasingly being positioned to assist people in decision-making. However, recent empirical studies show critical concerns that people over-rely on AI advice without analytically engaging with it. While HCI research explores how people rely on AI advice, we argue that it largely overlooks an important aspect: replicating realistic decision-making scenarios. Human-AI interaction factors influence people’s reliance on AI advice. To understand human-AI interaction factors and their interplay, we conducted an analytical review of recent studies in human-AI reliance literature. We analyzed the decision-making tasks in research and their validity in application-grounded contexts. Our findings show that user engagement is a precious commodity for relying on AI advice; however, it comes at a cost. We also discuss factors contributing to “appropriate reliance”, existing research gaps, and recommendations for intervention design for human-AI reliance. Our work contributes to the critical body of research on building appropriate reliance on AI advice.

An interactive vignette is a popular and immersive visual storytelling approach that invites viewers to role-play a character and influences the narrative in an interactive environment. However, it has not been widely used by everyday storytellers yet due to authoring complexity, which conflicts with the immediacy of everyday storytelling. We introduce DiaryPlay, an AI-assisted authoring system for interactive vignette creation in everyday storytelling. It takes a natural language story as input and extracts the three core elements of an interactive vignette (environment, characters, and events), enabling authors to focus on refining these elements instead of constructing them from scratch. Then, it automatically transforms the single-branch story input into a branch-and-bottleneck structure using an LLM-powered narrative planner, which enables flexible viewer interactions while freeing the author from multi-branching. A technical evaluation (N=16) shows that DiaryPlay-generated character activities are on par with human-authored ones regarding believability. A user study (N=16) shows that DiaryPlay effectively supports authors in creating interactive vignette elements, maintains authorial intent while reacting to viewer interactions, and provides engaging viewing experiences.

Location-based games (LBGs) merge digital play with physical environments, creating hybrid spaces that require players to navigate complex trust dynamics. Despite their global popularity, LBGs introduce unique challenges around fairness, safety, and privacy, spanning interactions among players, game systems, local communities, and non-players in shared public spaces. To examine how trust is perceived, built, and sustained in these environments, we conducted in-depth interviews with 26 players of four major LBGs: Pokémon GO, Monster Hunter Now, Ingress, and Pikmin Bloom. Using reflexive thematic analysis, we identified dynamics of trust across four trustor–trustee relationships: player–system, player–player, player–community, and player–non-player in five key aspects: fair play, location privacy, online vetting, hybrid interaction, and public play. Drawing on our findings, we propose a trust model for analyzing and designing trust in LBGs as hybrid spaces, and we outline design implications aimed at strengthening trust building and sustaining trustworthy interactions across the LBG ecology.

Emerging multimodal conversational search (MCS) tools (e.g., Gemini Live) allow users to search for spatiotemporal information through natural language dialogues as they move through urban space. Despite the growing popularity of these tools, there is limited understanding of how people engage with this technology. To address this gap, we developed UrbanSearch, an MCS technology probe designed to capture the user’s current geolocation, time, and visual surroundings. A contextual inquiry (N=23) revealed that MCS tools provide two core values: requiring low effort in forming queries while offering highly relevant responses, and functioning as a central information gateway. As a promising technology, MCS supports environmental learning, in-situ decision making, and personalized navigation. Participants also revealed unmet needs for spatial reasoning and transparent integration of multi-source information, along with concerns related to peripheral awareness, social context, and personal space. Drawing from the findings, we discuss design implications for future MCS tools in urban spaces.

Location-based media applications such as Google Maps, Strava and Pokémon GO together have more than a billion monthly active users, and popular social media such as Snapchat and Instagram now also feature map-based content. All these media products rely on user-generated content as a core element of their service, but there is a lack of synthesis on the users' motivations to contribute this data to the platform providers. In this study, we performed a literature review to uncover users' motivations to participate in location-based crowdsourcing and contribute shared content on these platforms. Among our findings, we show that spatial and temporal aspects, social effects, technical elements, motivational mechanisms, practical value offered to the contributors and individual differences need to be considered in motivating users to contribute shared content. We present recommendations for designers, suggest which terminology to use around this topic and propose an agenda for future research.

Tasks in augmented reality (AR), such as 3D interaction and instructional comprehension, are often designed for users with uniform sensory abilities. Such an approach, however, can overlook the more nuanced needs of Deaf and Hard of Hearing (DHH) users who might have reduced auditory perception. To better understand these challenges, our study utilized the single-player AR game Angry Birds AR as a probe to explore how 11 DHH participants and 15 hearing participants experienced AR interactions. Our findings highlight that DHH users prefer interaction based on context, effective haptic cues, audio cue substitutes, and clear instructional design. We, therefore, propose the following design recommendations to enhance the accessibility of AR for DHH users. This includes customizable UI options, modular feedback systems, and virtual avatars for sign language instructions.

Users often over-rely on AI-assisted decisions without analytically engaging with them, even in practical domains.In this work, we explore persuading users to analytically engage with AI assistance to reduce their over-reliance using a complex business case of customer classification.We explore the effect of persuasive cognitive engagement through explanations and communicating system uncertainty to examine the behavior of participants having diverse expertise.We leverage their feedback and objective behavior to understand their perception of the AI performance.Our findings show a contrast in participants' subjective and objective behavior, indicating inappropriate reliance on AI assistance with the perception of system performance.However, we observe the positives of interactive cognitive engagement and identify further directions to get deeper insights into expert domains with personalized AI assistance and behavioral persuasion.

Location-based games (LBG) impose virtual spaces on top of physical locations. Studies have explored LBG from various perspectives. In this paper, we leverage several of the most popular LBG (circa 2019) to identify the players of such games: their traits, gratifications, and links therein. To achieve our objective, we deployed surveys to 2390 active LBG players utilising Tondello et al.'s Player Traits Model and Scale of Game Playing Preferences and Hamari's scale of LBG gratifications. Our findings (1) illustrate an association between player satisfaction and social aspects of the studied games, (2) illustrate how the core loops of the studied games impact the expressed gratifications and the affine traits of players, and most centrally, (3) indicate a vital distinction between hardcore and casual players based on both traits and gratifications. Overall, our findings elucidate the players of LBG, their traits, and the gratifications they derive from playing LBGs.

Shared Augmented Reality (Shared AR) is an emerging technology that enables multiple users to interact synchronously within a collocated AR environment. Yet, there is limited research on the group interactions and dynamics in Shared AR, particularly in the context of gaming. To address this gap, we investigate Shared AR group interactions using a phone-based Shared AR mobile game called Urban Legends . Through in situ observations, focus groups, and one-on-one interviews with 22 participants, we examine how users collaborate and communicate within the game. Our findings reveal that while verbal communication predominates, non-verbal cues are often overlooked by collocated participants, and users initially struggle to recognize the expansive virtual space and the need for physical movement. Over time, users adapt to the hybrid environment, demonstrating increasing spatial awareness and more dynamic collaboration. Based on these insights, we present a suite of design recommendations for enhancing spatial awareness, supporting multi-modal communication, and fostering engaging group dynamics in future Shared AR applications.

Sensory-intensive and attention-demanding tasks like visual scanning, interacting with 3D objects, comprehending and following instructions, etc. are becoming more common in Augmented Reality (AR) environments as the technology expands through diverse fields. It is important to understand how these types of tasks are experienced by Deaf and Hard of Hearing (DHH) people, especially if those tasks involve any sound or compete with attention shifts (e.g., observing someone signing) in both real and virtual environments. Our current research specifically aims to identify the challenges that DHH users encounter when engaging in visual scanning in an AR environment. Using Angry Birds AR as a probe in our research, 11 DHH participants, with varying hearing abilities played seven rounds of the game, followed by a short structured interview and a long semi-structured interview. Our findings revealed that subtle audio cues and excessive visual indicators impacted participants’ performances negatively. Additionally, they positioned themselves strategically for maximum spatial awareness but faced challenges with AR visual cues due to the lighting conditions in the real environment. We further suggested design implications such as customizable, user-friendly haptic and textual feedback, and intelligent spatially aware mechanisms for AR.

Co-located collaborative shared augmented reality (CS-AR) environments have gained considerable research attention, mainly focusing on design, implementation, accuracy, and usability. Yet, a gap persists in our understanding regarding the accessibility and inclusivity of such environments for diverse user groups, such as deaf and Hard of Hearing (DHH) people. To investigate this domain, we used Urban Legends, a multiplayer game in a co-located CS-AR setting. We conducted a user study followed by one-on-one interviews with 17 DHH participants. Our findings revealed the usage of multimodal communication (verbal and non-verbal) before and during the game, impacting the amount of collaboration among participants and how their coordination with AR components, their surroundings, and other participants improved throughout the rounds. We utilize our data to propose design enhancements, including onscreen visuals and speech-to-text transcription, centered on participant perspectives and our analysis.

There are numerous benefits from regularly walking in nature, and today's mobile technologies have the potential to encourage people to do so. Past research has showed that gamified map-based apps and location-based games (LBGs) have the capability to incentivize people to go to nature areas in cities and beyond. In this study, we explored LBGs' potential to bring people to nature by conducting a field experiment with a new mechanic called Routes in the popular LBG Pokémon GO. Prior to the Route feature's launch, we created altogether 13 Routes of various lengths in both city and nature landscapes. We collected numerical in-game data of how many times each Route was walked and deployed a survey (n=67) for Pokémon GO players in the area where the Routes were made. The findings suggest that proximity to population concentrations and in-game rewards are key drivers of Route popularity. Players' motivators to choose nature Routes over urban Routes were limited to outside-the-game factors such as scenery, and overall in our experiment the urban Routes turned out to be more popular.

One of the most recent developments in augmented reality (AR) technology is co-located collaborative multiplayer AR environments, yet little research has been done to determine how communication and collaboration function in these settings. There is a gap in our understanding of whether these environments are currently accessible for Deaf and Hard of Hearing (DHH) people. Although technical aspects, such as design, implementation, accuracy, etc., of the technologies and users’ behavior with assistive AR technologies, have been covered in plenty of prior literature, very few studies have paid attention to how DHH people communicate and collaborate in co-located collaborative AR environments. As an initial step toward addressing the gap in current literature, our ongoing research focuses on how DHH people communicate and collaborate in a co-located collaborative multiplayer AR environment. As part of our study, we conducted gameplay experiments and one-on-one semi-structured interviews with 17 DHH participants. In this piece of work, among the prominent themes that stood out in our findings, we further discuss communication and collaboration, specifically multi-modal communication (verbal and non-verbal) among users and how multi-modal communication affected their collaboration in the environment.

With the expanding popularity of Location-Based Games and the rise of advertising therein, there exists a need to comprehend the impact of Location-Based Game Advertising (LGA). This paper seeks to identify what makes positively affective LGA, leveraging Pokémon GO as a probe. Researchers conducted twenty-seven (n=27) semi-structured interviews with Pokémon GO players to reveal lived experiences regarding LGA. Our findings highlight the following direct implications for LGA: (1) LGA act as a digital billboard, conveying qualitative alongside locative information, and (2) well-received LGA enhances the player’s agency. We additionally identify findings that have auxiliary implications to LGA: (3) positive memorability occurs when points of interest match physical reality, and (4) ludic engagement is a mediating factor in the memorability of locations. This research demonstrates that LGA in Location-Based Games is surprisingly well-received. However, developers must provide extra consideration to the player’s agency for such techniques to be effective.

Crowdsourcing in China is a thriving industry. Among its most interesting structures, we find crowdfarms, in which crowdworkers self-organize as small organizations to tackle macrotasks. Little, however, is known as to which practices these crowdfarms use to tackle the macrotasks, and this goes hand in hand with the current practice of the HCI research community to treat all forms of complex crowdsourcing work as practically the same. However, macrotasks differ substantially regarding structure and decomposability. Treating them under one umbrella term - macrotasking - can lead to an imprecise understanding of the workforce involved. We address this gap by examining the work practices of 31 Chinese crowdfarms on the four main macrotask types, namely: modular, interlaced, wicked, and container macrotasks. Our results confirm essential differences in how these nascent crowd organizations address different macrotasks and shed light on what platforms can do to improve the uptake of such work.

The overlaying of physical spaces with digital information produces hybrid spaces, redefining people’s experience of social interactions. Location-based games (LBGs) with social components are a good case. Yet, the impact LBGs have on sociability remains under-researched. In April 2020, the new in-person/remote raiding format in the LBG Pokémon GO provided a lens to explore people’s social interactions in hybrid spaces. We interviewed 41 Pokémon GO players to understand how players coordinate and collaborate for in-person/remote raids and other social patterns. Our findings demonstrate that new social dynamics occurred: participants’ social interactions highly rely on external social media groups bridging cyberspace and the physical world. In such external social media groups, spontaneously formed leadership roles and mentor-mentee relationships demonstrate autonomy among players in the hybrid space. However, we observed that the interoperability issue challenges people’s experience. Overall, this work sheds light on the social interactions in LBGs as hybrid spaces.

The continued development of smart cities is a recurring feature of urban living and does not appear to be slowing down. Today, our lives are both mediated and monitored by a range of digital techn...

Location-based multiplayer games such as Pokémon GO are tied to real-world locations. Past research has demonstrated that, consequently, these games influence where players move. In order to explore what dynamics in these games incentivize travel to specific places or areas, we engaged in interviews with active players. We discovered 11 unique game dynamics, which could be positioned under three overarching themes: (1) the playing field, as determined by the placement of points of interest, the players' habitat and their surroundings; (2) the player communities and real life relationships, which motivated and directed the playing; and (3) coincidental motivational support, which highlighted how location-based games offer multi-layered motivation for players to travel to, and engage with, specific real-world locations. Our study contributes to the fields of gamified human mobility and human-nature interaction by elucidating how playful technologies can influence where and when people move.

Since its creation, the Location-Based Game (LBG), Pokémon GO , has been embraced by a community of fans across the world. Due to its recency, the impact of COVID-19 on the community of Pokémon GO players is underexplored. We address how COVID-19 has impacted the players of Pokémon GO by building upon existing work focusing on player gratifications and impacts in Pokémon GO . Through semi-structured interviews, we provide a snapshot of the state of LBG play during unprecedented times. These player interviews demonstrate (1) the importance of in-person socialization to LBG, (2) additional ways players use the game as a coping mechanism, and (3) how intentionality mediates player perceptions of people-place relationships. Furthermore, we explore how Niantic influenced these behaviors through changes to how players interact with points of interest and engage with elder game mechanics such as raiding.

Crowdsourcing is a new value creation business model. Annual revenue of the Chinese market alone is hundreds of millions of dollars, yet few studies have focused on the practices of the Chinese crowdsourcing workforce, and those that do mainly focus on solo crowdworkers. We have extended our study of solo crowdworker practices to include crowdfarms, a relatively new entry to the gig economy: small companies that carry out crowdwork as a key part of their business. We report here on interviews of people who work in 53 crowdfarms. We describe how crowdfarms procure jobs, carry out macrotasks and microtasks, manage their reputation, and employ different management practices to motivate crowdworkers and customers.

Recent research highlights the potential of crowdsourcing in China. Yet very few studies explore the workplace context and experiences of Chinese crowdworkers. Those that do, focus mainly on the work experiences of solo crowdworkers but do not deal with issues pertaining to the substantial amount of people working in 'crowdfarms'. This article addresses this gap as one of its primary concerns. Drawing on a study that involves 48 participants, our research explores, compares and contrasts the work experiences of solo crowdworkers to those of crowdfarm workers. Our findings illustrate that the work experiences and context of the solo workers and crowdfarm workers are substantially different, with regards to their motivations, the ways they engage with crowdsourcing, the tasks they work on, and the crowdsourcing platforms they utilize. Overall, our study contributes to furthering the understandings on the work experiences of crowdworkers in China.

Smart cities are commonly described as ‘places where information technology is combined with infrastructure, architecture, everyday objects, and even our bodies to address social, economic, and env...

Despite the growing interest in crowdsourcing, this new labor model has recently received severe criticism. The most important point of this criticism is that crowdworkers are often underpaid and overworked. This severely affects job satisfaction and productivity. Although there is a growing body of evidence exploring the work experiences of crowdworkers in various countries, there have been a very limited number of studies to the best of our knowledge exploring the work experiences of Chinese crowdworkers. In this paper we aim to address this gap. Based on a framework of well-established approaches, namely the Job Demands-Resources model, the Work Design Questionnaire, the Oldenburg Burnout Inventory, the Utrecht Work Engagement Scale, and the Organizational Commitment Questionnaire, we systematically study the work experiences of 289 crowdworkers who work for ZBJ.com - the most popular Chinese crowdsourcing platform. Our study examines these crowdworker experiences along four dimensions: (1) crowdsourcing job demands, (2) job resources available to the workers, (3) crowdwork experiences, and (4) platform commitment. Our results indicate significant differences across the four dimensions based on crowdworkers' gender, education, income, job nature, and health condition. Further, they illustrate that different crowdworkers have different needs and threshold of demands and resources and that this plays a significant role in terms of moderating the crowdwork experience and platform commitment. Overall, our study sheds light to the work experiences of the Chinese crowdworkers and at the same time contributes to furthering understandings related to the work experiences of crowdworkers.

Expressions of territoriality have been positioned as one of the main reasons users alter their behaviors and perceptions of spatiality and sociality while engaging with location-based social networks (LBSN). Despite the potential for this interplay to further our understanding of LBSN usage in the context of identity, very little work has actually been done toward this. Addressing this gap in the literature is one of the chief aims of the article. Drawing on an original 6-week study with 42 participants utilizing a bespoke LBSN entitled “GeoMoments,” our research explores the following: (1) the way that territoriality is linked to self-identity; and (2) how this interplay affects the interactions between users as well as the environments they inhabit. Our findings suggest that participants affirmed their self-identity by selectively posting and claiming ownership of their neighborhood through the LBSN. Here, the locative decisions are made related to risk, hierarchies, and the users’ relationship to the area. This practice then led participants to discover and interact with the digital information overlaying their physical environments in a playful manner. These interactions demonstrate the perceived power structures that are facilitated by identity claims over a virtual area. In the main, our results reaffirm that territoriality is a central concept in understanding LBSN use, while also drawing attention to the temporality involved in user-to-user and user-to-place interactions pertaining to physical place mediated by LBSN.

This research explores the design and evaluation of visualization techniques of targets that reside outside of users' view and/or are occluded by other elements within a virtual reality environment (VE). We first compare four techniques (3DWedge, 3DArrow, 3DMinimap, and Radar) that use different types of visual elements to provide direction and distance information of targets. To give structure to their evaluation, we also develop a framework of four tasks (one for direction and three for distance) and their assessment criteria. The results of the first study show that 3DWedge is the best-performing and most usable technique. However, all techniques, including 3DWedge, have poor performance in dense scenarios with a large number of targets. To improve support in dense scenarios, a fifth technique, 3DWedge+, is developed by using 3DWedge as its foundation and including additional visual elements that are derived from the other three techniques which are shown to be useful. A second study is conducted to evaluate the performance of 3DWedge+ in relation to the other techniques. The results show that both 3DWedge and 3DWedge+ are significantly better in distinguishing user-to-target distance and that 3DWedge+ is particularly suitable for dense scenarios. Based on these results, we provide a set of recommendations for the design of visualization techniques of off-screen and occluded targets in 3D VE.

Interactive visualizations are external cognitive artifacts aimed at supporting users' exploratory and sense-making activities. In recent years, there has been an explosion of commercial virtual reality (VR) head-mounted displays (HMD). These VR devices are meant to offer high levels of engagement and improve users' analytical exploration of the displayed content. However, given their rapid market introduction, the possible influences and usefulness that VR could bring in terms of supporting users' exploration with interactive visualizations remain largely underexplored. We attempt to fill this gap and provide results of an empirical study of an interactive visualization tool that we have developed for a VR HMD system. This tool is aimed at facilitating exploratory and analytical reasoning activities with 3D shapes and their transformational processes. Overall, the results show that the tool is supportive of users' exploratory and analytical activities based on the significant improvement in their post-experiment test scores (when compared to their pre-experiment ones) and their engagement level measured via a user engagement questionnaire and participants' comments. The results shed a positive light on the use of visualizations in VR environments and can inform the design of these tools of domains beyond 3D transformational geometry.

Following successful crowd ideation contests, organizations in search of the "next big thing" are left with hundreds of ideas. Expert-based idea filtering is lengthy and costly; therefore, crowd-based strategies are often employed. Unfortunately, these strategies typically (1) do not separate the mediocre from the excellent, and (2) direct all the attention to certain idea concepts, while others starve. We introduce DBLemons - a crowd-based idea filtering strategy that addresses these issues by (1) asking voters to identify the worst rather than the best ideas using a "bag of lemons'' voting approach, and (2) by exposing voters to a wider idea spectrum, thanks to a dynamic diversity-based ranking system balancing idea quality and coverage. We compare DBLemons against two state-of-the-art idea filtering strategies in a real-world setting. Results show that DBLemons is more accurate, less time-consuming, and reduces the idea space in half while still retaining 94% of the top ideas.