Technologies for older adults largely focus on monitoring, safety, and functional support, with less attention to everyday emotional meaning-making. Reflective practices can support emotional wellbeing in later life, yet reflective tools tailored to older adults, particularly in India, remain limited. Self-perceptions of aging (SPA) are strongly linked to emotional wellbeing, but SPA work largely relies on questionnaires and clinical formats rather than culturally grounded tools for reflection. This pictorial presents a research-through-design process leading to a culturally grounded reflection tool for older adults in India. It combines SPA-based reflection cards and prompts with non-diagnostic reflective guidance drawn from a curated corpus rooted in cultural understanding. The work co-designed SPA reflection cards grounded in older adults’ metaphors and narratives, and developed the guidance system with older adults and domain experts. It contributes design knowledge on operationalizing SPA in culturally attuned, technology-mediated reflective tools for older adults in urban India.

Formal regulation designed to protect workers is often opaque, with narrow definitions of injury. This means that even when workers report harm, regulators fail to intervene on cumulative, chronic, and collective experiences. Through interviews and co-design workshops with unionized cleaning workers, we explore alternative forms of documentation that support collective action rather than institutional proof. Our study illuminates four interlocking worker-led documentation practices: (1) Surfacing experiences of working conditions, (2) Collectively making sense of existing reporting avenues, (3) Negotiating with management and publics, and (4) Building trust and solidarity within the union. For each of these practices, we offer concrete design concepts developed in collaboration with workers. Finally, we contribute conceptual knowledge on how engaging in the process of documentation functions as an engine of solidarity-building, a prerequisite for addressing workplace harms beyond disparate data points.

Artificial intelligence (AI) technologies offer tremendous potential for product and service innovation, yet finding good use cases remains challenging. Currently, AI projects largely fail due to breakdowns in early stage ideation and problem formulation. Drawing on HCI research that used AI capabilities and examples to facilitate AI concept ideation, this paper investigates how these approaches might be operationalized in industry settings. We collaborated with cross-functional industry teams in insurance, accounting, and consultancy. We conducted a series of AI Design Sprints, where innovators simultaneously consider AI capabilities and human needs. All teams perceived the ideation method highly valuable both for rapidly exploring use cases and building AI literacy within teams. We detail our process, the challenges, and artifacts that proved effective. We share insights on how AI projects get initiated, and how innovation teams identify use cases. Reflecting on these case studies, we discuss opportunities for improving early stage AI innovation.

AI creates and exacerbates privacy risks, yet practitioners lack effective resources to identify and mitigate these risks. We present Privy, a tool that guides practitioners without privacy expertise through structured privacy impact assessments to: (i) identify relevant risks in novel AI product concepts, and (ii) propose appropriate mitigations. Privy was shaped by a formative study with 11 practitioners, which informed two versions — one LLM-powered, the other template-based. We evaluated these two versions of Privy through a between-subjects, controlled study with 24 separate practitioners, whose assessments were reviewed by 13 independent privacy experts. Results show that Privy helps practitioners produce privacy assessments that experts deemed high quality: practitioners identified relevant risks and proposed appropriate mitigation strategies. These effects were augmented in the LLM-powered version. Practitioners themselves rated Privy as being useful and usable, and their feedback illustrates how it helps overcome long-standing awareness, motivation, and ability barriers in privacy work.

The evolution of artist toolsets has created opportunities for new media and industrial growth. As these tools evolve, clear advantages of digital media emerge. Still, many digital toolsets grow further apart from their traditional predecessors, developing highly technical workflows and unfamiliar interfaces. With no standard language or classification system across artist toolsets, the measurement of these various paradigms becomes convoluted. Moreover, it is unclear how augmenting production pipelines affects the practitioner workflow within a professional studio. This paper presents a generalized approach to measuring artist tools through data collection, field studies, interviews, and an iterative refinement process. We define a broad category of creative practice known as the ‘sculptural process’ and introduce a taxonomy for a technical coding system. Our findings indicate an obstruction of artist processes for professionals in digital media, particularly 3D, exposing a significant gap between traditional and digital media. These measurements create a foundation to reinforce artist-driven design in human-computer interaction.

Designing Conversational AI systems to support older adults requires these systems to explain their behavior in ways that align with older adults’ preferences and context. While prior work has emphasized the importance of AI explainability in building user trust, relatively little is known about older adults’ requirements and perceptions of AI-generated explanations. To address this gap, we conducted an exploratory Speed Dating study with 23 older adults to understand their responses to contextually grounded AI explanations. Our findings reveal the highly context-dependent nature of explanations, shaped by conversational cues such as the content, tone, and framing of explanation. We also found that explanations are often interpreted as interactive, multi-turn conversational exchanges with the AI, and can be helpful in calibrating urgency, guiding actionability, and providing insights into older adults’ daily lives for their family members. We conclude by discussing implications for designing context-sensitive and personalized explanations in Conversational AI systems.

As populations age and technology becomes more pervasive, understanding the alignment between older adults’ values and technology design is paramount. More research is needed to understand how older adults’ living contexts shape their values and the use of technology. To address this, through a multi-context study, we explored how values differ for older adults and how their context of living might influence the adoption and use of technology. We conducted 22 semi-structured interviews with older adults in various residential contexts. We show that older adults tend to prioritize the same core values across living contexts, yet how they express values in each context differs. Technology can amplify or inhibit key values. We describe implications for context-responsive technology and design for continuity, to allow older adults to continually uphold important values through technology use.

Theory of Mind (ToM) -- the ability to infer what others are thinking (e.g., intentions) from observable cues -- is traditionally considered fundamental to human social interactions. This has sparked growing efforts in building and benchmarking AI's ToM capability, yet little is known about how such capability could translate into the design and experience of everyday user-facing AI products and services. We conducted 13 co-design sessions with 26 U.S.-based AI practitioners to envision, reflect, and distill design recommendations for ToM-enabled everyday AI products and services that are both future-looking and grounded in the realities of AI design and development practices. Analysis revealed three interrelated design recommendations: ToM-enabled AI should 1) be situated in the social context that shape users' mental states, 2) be responsive to the dynamic nature of mental states, and 3) be attuned to subjective individual differences. We surface design tensions within each recommendation that reveal a broader gap between practitioners' envisioned futures of ToM-enabled AI and the realities of current AI design and development practices. These findings point toward the need to move beyond static, inference-driven approach to ToM and toward designing ToM as a pervasive capability that supports continuous human-AI interaction loops.

The rise of Generative AI (GenAI) has demonstrated significant potential to improve productivity and foster creativity among content creators, social media influencers with large audiences on platforms such as Instagram, TikTok, and YouTube. However, as GenAI tools became increasingly integrated into creative workflows, significant concerns have emerged about potential risks and harms, including misinformation, social biases, and threats to authenticity. While prior research in HCI and CSCW has documented the pressures content creators face within algorithmic ecosystems, relatively little is known about how creators practically manage responsibility work when using GenAI tools. To address this gap, we conducted semi-structured interviews (N = 16) with content creators active on popular social media platforms such as YouTube, Instagram, and TikTok, examining their motivations, practices, and specific challenges related to responsible GenAI use. Our findings reveal that creators’ motivations for practicing responsible AI use span personal reputation management, audience trust-building, and broader social responsibility. However, they face persistent tensions, as integrating GenAI significantly intensifies conflicts between responsible AI practices and the pressures of visibility, engagement, and monetization imposed by platform algorithms. Content creators are required to perform extensive and often invisible responsibility work, which directly conflicts with the rapid production cycles and engagement demands of algorithm-driven platforms. Based on these insights, we propose concrete socio-technical design implications at the individual, community, and institutional levels, advocating solutions that shift responsibility beyond individual creators alone.

AI projects often fail due to financial, technical, ethical, or user acceptance challenges-failures frequently rooted in early-stage decisions.While HCI and Responsible AI (RAI) research emphasize this, practical approaches for identifying promising concepts early remain limited.Drawing on Research through Design, this paper investigates how early-stage AI concept sorting in commercial settings can reflect RAI principles.Through three design experiments-including a probe study with industry practitioners-we explored methods for evaluating risks and benefits using multidisciplinary collaboration.Participants demonstrated strong receptivity to addressing RAI concerns early in the process and effectively identified low-risk, high-benefit AI concepts.Our findings highlight the potential of a design-led approach to embed ethical and service design thinking at the front end of AI innovation.By examining how practitioners reason about AI concepts, our study invites HCI and RAI communities to see early-stage innovation as a critical space for engaging ethical and commercial considerations together.

In this submission, I present my research on the design of technological interventions to enhance self-perceptions of aging (SPA)and the well-being of older adults in India.My work focuses on aging experiences and technology opportunities for older adults in diverse living environments in urban India.These living environments include private homes (aging in place), assisted living townships (retirement homes), and old age institutions.Through interviews, the design of an Aging Reflection Probe Kit and field engagements, I highlight key aspects of SPA among older adults.These include social presence, self-efficacy, activities, age-related transitions, life satisfaction, agency, self-value, age associations, and emotional well-being.I propose a Research through Design (RtD) approach to explore how technological interventions can operationalize SPA theories in HCI and contribute to enhancing older adults' well-being.In addition, I will examine how older adults in diverse living environments adopt and adapt these technologies and how these interventions shape their aging experiences, environments, and social networks.

Innovators transform the world by understanding where services are successfully meeting customers' needs and then using this knowledge to identify failsafe opportunities for innovation. Pre-trained models have changed the AI innovation landscape, making it faster and easier to create new AI products and services. Understanding where pre-trained models are successful is critical for supporting AI innovation. Unfortunately, the hype cycle surrounding pre-trained models makes it hard to know where AI can really be successful. To address this, we investigated pre-trained model applications developed by HCI researchers as a proxy for commercially successful applications. The research applications demonstrate technical capabilities, address real user needs, and avoid ethical challenges. Using an artifact analysis approach, we categorized capabilities, opportunity domains, data types, and emerging interaction design patterns, uncovering some of the opportunity space for innovation with pre-trained models.

Algorithmic management is transforming traditional face-to-face service sectors like hospitality.To understand this phenomenon, we conducted an interview study in a unionized, mid-sized urban hotel on the West Coast of the USA.Through this work, we examine how an algorithmic management (AM) platform mediates work in a housekeeping department.Our analysis highlights the effects of AM on social processes, revealing that despite careful configuration, the tool's implementation still challenges traditional communication and coordination.This study contributes empirical evidence on AM impacts in a collaborative service environment, emphasizing the importance of organizational dynamics in AM design and implementation.We offer design opportunities for flexible workplace technologies that support, rather than frustrate, the relational aspects of service work.

As the population of older adults increases, there is a growing need for support for them to age in place. This is exacerbated by the growing number of individuals struggling with cognitive decline and shrinking number of youth who provide care for them. Artificially intelligent agents could provide cognitive support to older adults experiencing memory problems, and they could help informal caregivers with coordination tasks. To better understand this possible future, we conducted a speed dating with storyboards study to reveal invisible social boundaries that might keep older adults and their caregivers from accepting and using agents. We found that healthy older adults worry that accepting agents into their homes might increase their chances of developing dementia. At the same time, they want immediate access to agents that know them well if they should experience cognitive decline. Older adults in the early stages of cognitive decline expressed a desire for agents that can ease the burden they saw themselves becoming for their caregivers. They also speculated that an agent who really knew them well might be an effective advocate for their needs when they were less able to advocate for themselves. That is, the agent may need to transition from being unremarkable to remarkable. Based on these findings, we present design opportunities and considerations for agents and articulate directions of future research.

This paper draws on Michel de Certeau's notion of ''tactics'' to explore the use of data in labor organizing research in CSCW. Taking a historical view, we first analyze a set of cases from 20th century US labor history that offer three distinct lenses on the risks of data-based advocacy campaigns: wagers, compromises, and concessions. Across our cases, we frame reformers' use of data tactics as a rhetorical move, taken to advance incremental worker gains under conditions of precarity. However, by continuing to rely on certain data-based arguments in the short term, we argue that labor reformers may have limited the frame of debate for broader arguments necessary to improve conditions in the long-term. These tensions follow us into data-based advocacy research in the present, such as the emerging ''digital workerism'' movement. To ensure the continuation of responsible advocacy research in CSCW, we offer insights from social justice movements to suggest how members of the HCI and CSCW communities can work more intentionally alongside (or without) data methods to support worker-led direct action.

The population of older adults experiencing cognitive decline is growing faster than the number of workers who can care for them. Artificially intelligent (AI) agents could assist these older adults, keeping them in their homes longer. For this to happen, older adults must be willing to adopt and rely on agents. Would they trust an agent that might need to report their decline to others? We conducted a speed dating study exploring the impact of agent affiliation (i.e., who the agent should work for). Our healthy and declining participants reacted positively to the idea of agents supporting them. They particularly recognized how the agent would reduce the burden placed on their family caregivers. They viewed affiliation to be dynamic, shifting from the declining older adult and orienting more to their caregivers over the course of cognitive decline. They envisioned the agent modifying its decision-making process to be like their caregivers’.

Privacy is a key principle for developing ethical AI technologies, but how does including AI technologies in products and services change privacy risks? We constructed a taxonomy of AI privacy risks by analyzing 321 documented AI privacy incidents. We codified how the unique capabilities and requirements of AI technologies described in those incidents generated new privacy risks, exacerbated known ones, or otherwise did not meaningfully alter the risk. We present 12 high-level privacy risks that AI technologies either newly created (e.g., exposure risks from deepfake pornography) or exacerbated (e.g., surveillance risks from collecting training data). One upshot of our work is that incorporating AI technologies into a product can alter the privacy risks it entails. Yet, current approaches to privacy-preserving AI/ML (e.g., federated learning, differential privacy, checklists) only address a subset of the privacy risks arising from the capabilities and data requirements of AI.

When integrating robots into human daily life, persuasive power can be essential. However, there are often group dynamics which can complicate persuasion. This study focuses on how non-verbal cues, specifically gaze and hand gestures, affect the persuasiveness of a social robot. We have designed a protocol to include non-verbal cues in the social robot Vizzy (head and eye gaze, hand gestures) and test them in a series of experiments using the paradigm of the "Desert Survival Challenge". The goal of the robot is to persuade the participants of the game into changing their answers whilst avoiding negative feelings. It is hypothesized that the nonverbal cues will help avoid psychological reactance without diminishing compliance to the verbal requests issued by the robot. This phenomenon has been verified before for single person persuasion, but it is yet to be tested on groups. Thus, the goal of this project is to verify the effect of non-verbal cues in group persuasion by a robot and comparing it to single person persuasion. The results showed that the robot’s gestures increased compliance by the group and the gaze behaviour decreased psychological reactance.

This paper investigates how conversational agents that are embedded in smart environments should present themselves socially. In an online study, we simulate a future space habitat in which "astronauts" (participants) interact with one or more agents to complete several tasks related to science, maintenance, and inventory. We examine effects of agent affiliation (affiliation with a user, affiliation with a domain, or affiliation with all users and all domains) and narrative perspective (first-vs. third-person references to parts of the environment) on mental models of the smart environment as one or multiple entities, trust, performance, and social variables. Our findings suggest that in this type of setting, interacting with a single agent may increase mental demand, and that agents that speak about embodied interaction in third person are perceived as more trustworthy and competent than agents that speak in first person.

Labor shortages have shaped many industries over the past several years, with hospitality experiencing one of the largest rates of attrition. Workers are leaving their jobs for a variety of reasons, ranging from burnout and work intensification to a lack of meaningful employment. While some literature maintains that labor-replacing automation is poised to bridge the shortages, we argue there is an opportunity for technology design to instead improve job quality and retention. Drawing on interviews with unionized guest room attendants, we report on workers’ perceptions of a widely-used algorithmic room assignment system. We then present worker-generated design ideas that adapt this system toward supporting three key facets of wellbeing: self-efficacy, transparency, and workload. We argue for the need to consider these facets of wellbeing through design across the service landscape, particularly as HCI attends to the impacts of AI and automation on frontline work.

Advances in artificial intelligence have enabled unprecedented technical capabilities, yet making these advances useful in the real world remains challenging. We engaged in a Research through Design process to improve the ideation of AI products and services. We developed a design resource capturing AI capabilities based on 40 AI features commonly used across various domains. To probe its usefulness, we created a set of slides illustrating AI capabilities and asked designers to ideate AI-enabled user experiences. We also incorporated capabilities into our own design process to brainstorm concepts with domain experts and data scientists. Our research revealed that designers should focus on innovations where moderate AI performance creates value. We reflect on our process and discuss research implications for creating and assessing resources to systematically explore AI’s problem-solution space.

Virtual assistants, vacuum robots, security systems, and other smart home technologies are rapidly advancing, evolving, and gaining popularity. This raises questions of how people envision future interactions with smart home systems and how they imagine the future roles of such technologies in society. We deployed an online study that collected fictional short stories from 60 participants about smart home interactions. We identified themes regarding the roles of smart home technologies, social interactions with AI, and concerns about data privacy in the context of the home. We describe our method, discuss insights from the stories that explicitly reflect possible futures and implicitly reflect the present, and make design recommendations based on our findings.

Recent investments in automation and AI are reshaping the hospitality sector. Driven by social and economic forces affecting service delivery, these new technologies have transformed the labor that acts as the backbone to the industry-namely frontline service work performed by housekeepers, front desk staff, line cooks and others. We describe the context for recent technological adoption, with particular emphasis on algorithmic management applications. Through this work, we identify gaps in existing literature and highlight areas in need of further research in the domains of worker-centered technology development. Our analysis highlights how technologies such as algorithmic management shape roles and tasks in the high-touch service sector. We outline how harms produced through automation are often due to a lack of attention to non-management stakeholders. We then describe an opportunity space for researchers and practitioners to elicit worker participation at all stages of technology adoption, and offer methods for centering workers, increasing transparency, and accounting for the context of use through holistic implementation and training strategies.

From initial case-reporting at the crime scene to finishing legal procedures, survivors of sexual assault navigate numerous human and technological resources provided by various organizations. During the help-seeking process, survivors unavoidably interact with multiple professional stakeholders (e.g., legal authorities) and technologies (e.g., checking their case status on a court website). In the long and complex process, survivors experience interactional breakdowns with technology, and/or humans, but few studies have explored what types of breakdowns systematically occur and how to resolve them. Thus, for this study, we conducted in-depth interviews with survivors and professionals who reside in South Korea to identify what and how breakdowns occur. Moreover, participatory design sessions were conducted with sexual assault survivors and professionals to create designs that could resolve the breakdowns. Consequently, we discovered a total of eleven breakdowns and produced solutions centered on the stakeholders (i.e., survivor and professionals). Specifically, our participants wanted an integrated system that proactively informs survivors of the holistic procedures for help-seeking and legal action, manages their case, and even interacts with legal authorities on the survivor's behalf. Based on the findings, we provide an agenda of essential designs and features that could mitigate interactional breakdowns. Additionally, we call for the HCI community to approach and solve sexual violence problems through a broad, macroscopic perspective instead of focusing on one specific technology or (social or organizational) system.

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.

Designers of smart-home systems must make decisions about the perceived identities and interconnectedness of their various devices. To inform these decisions, we performed an online study to examine whether people perceive multiple devices in a smart home as different interfaces for the same system, devices that talk to each other, or independent devices. We manipulated the types of devices in the system (hetero-geneous!homogeneous), how the devices relayed commands to each other (implicit/explicit), and the task requested. Participants were flexible in how they interpreted the devices, presenting an opportunity for designers to select a suitable model.

With the infusion of computation into workplaces and homes, various service settings, and everyday objects, scholars in human–computer interaction (HCI) and related domains have begun to consider the research and design implications not only of smart “things,” but ofsmart environments. Much of the work on smart environments to date has focused on smart homes; related work in HCI explores user values for smart homes, means of interacting with computation in smart homes (e.g., interfaces and agents), how to balance the needs of multiple stakeholders, and how to preserve user trust and autonomy. However, the smart environments of the future will not always fit the smart home mold of a coalescence of products that exist to automate and ease everyday tasks for the end users. They will be both user-focused and goal-focused, public and private, large and small, and ephemeral and long-lasting. It will benefit the field to look atsmart environmentsas a unit of analysis—including what these different types of environments have in common and what they do not—from a systemic, user experience design-oriented view. In this survey article, we review prior research on smart environments and various related bodies of literature. Informed by our literature review, we articulate fivelensesthat distinguish different types of smart environments from one another. We then propose research directions for future work on this topic.

Social agents and robots are moving into front-line positions in brick and mortar services, taking on roles where they directly interact with customers. These agents could potentially recognize customers to personalize service. Will customers like this, or might they feel monitored and profiled? Robots could also re-embody (move their “personality” between one body and another) in order to take on multiple roles that are typically performed by different people. Will this make customers feel more taken care of, or will it raise concerns about the robot’s competence and expertise? Our work investigates when robots should and should not recognize customers and re-embody. Our online study used storyboards to present possible future interactions between robots and customers across several different service contexts. Our findings suggest that people generally accept robots identifying customers and taking on vastly different roles. However, in some contexts, these robot behaviors seem creepy and untrustworthy.

With the growing industry applications of Artificial Intelligence (AI) systems, pre-trained models and APIs have emerged and greatly lowered the barrier of building AI-powered products. However, novice AI application designers often struggle to recognize the inherent algorithmic trade-offs and evaluate model fairness before making informed design decisions. In this study, we examined the Objective Revision Evaluation System (ORES), a machine learning (ML) API in Wikipedia used by the community to build anti-vandalism tools. We designed an interactive visualization system to communicate model threshold trade-offs and fairness in ORES. We evaluated our system by conducting 10 in-depth interviews with potential ORES application designers. We found that our system helped application designers who have limited ML backgrounds learn about in-context ML knowledge, recognize inherent value trade-offs, and make design decisions that aligned with their goals. By demonstrating our system in a real-world domain, this paper presents a novel visualization approach to facilitate greater accessibility and human agency in AI application design.

How are people using current smart home technologies, and how do they conceptualize future ones that are more interconnected and more capable than those available today? We deployed an online survey study to 150 participants to investigate use of and opinions about smart speakers, home robots, virtual assistants, and other smart home devices. We also gauged how impressions of connected smart home devices are shaped by the way the devices interact with one another. Through a mixed-methods qualitative and quantitative approach, we found that people mostly use single devices for single functions, and have simple and brief interactions with virtual assistants. However, they imagine their future devices to have more control over the physical environment (i.e., interact with each other) and envision them interacting with people in more socially complex ways. These findings motivate design considerations and research directions for connected smart home technologies.

We explored different ways in which a multi-robot system might recover after one robot experiences a failure. We compared four recovery conditions: Update (a robot fixes its error and continues the task), Re-embody (a robot transfers its intelligence to a different body), Call (the failed robot summons a second robot to take its place), and Sense (a second robot detects the failure and proactively takes the place of the first robot). We found that trust in the system and perceived competence of the system were higher when a single robot recovered from a failure on its own (by updating or re-embodying) than when a second robot took over the task. We also found evidence that two robots that used the same socially interactive intelligence were perceived more similarly than two robots with different intelligences. Finally, our study revealed a relationship between how people perceive the agency of a robot and how they perceive the performance of the system.

In the not-so-distant future, people in service experiences are likely to interact with more than a single intelligent system, often sequentially, including different robots and devices. However, there has been sparse work exploring the characteristics of transferring people from one intelligent system to another. This paper aims to create a context-independent taxonomy to differentiate and categorize the transfer of users across robots, devices, and human staff in service interactions. We conducted two sets of design workshops where participants generated scenarios of human-multi-robot interactions and existing person transfers. Using the outcomes of both workshops, we analyzed scenarios and constructed a taxonomy for person transfers with 4-dimensions: Rationale, Type, Design, and Information Shared. We showcase different ways to utilize the taxonomy, and, through it, we discuss the trade-offs and design considerations in the implementation of person transfers.

By leveraging approaches from other disciplines, designers can expand the boundaries of interaction design to tackle complex socio-technical problems. To address the challenges of networked social justice movements, we developed a workshop for designers and social justice activists based in Viewpoints and Composition, a philosophy and set of techniques for the theatre. Building on other experience prototyping and somatic methods, the workshop leads participants through the design of a hypothetical internet-enabled social justice campaign, encouraging them to imagine the felt-experience of networked social justice movement building in a socio-spatial context. We conclude with insights from the workshop and plans to further develop these techniques.

As we design increasingly complex systems, we run up against fundamental limitations of human imagination. To support practice, it becomes essential to use authentic data and algorithms as design materials to augment designers' intuitions. Recent work has explored some dimensions of using data as a design material, suggesting the contours of a new space of design and prototyping methods. In this paper, we present Replay Enactments (REs, an extension of the User Enactments methods that uses data replay as a boundary object, making complex system behavior tangible to designers and stakeholders. We reflect on a set of case studies that have instantiated REs in diverse ways and discuss trade-offs between different ways of using data replays in design. We conclude by highlighting opportunities and challenges for future work.

Agents that support spoken interaction (e.g., Amazon Echo) are designed for social spaces like the home, yet designers know little about how they should respond to social activity around them. We set out to reconsider current one-on-one interactions with agents, and explore the design space of future socially sophisticated agents. To do so, we use an iterative co-design process with designers and theatre experts to devise an immersive performance, "Robotic Futures." Theatre is a form of knowing through doing-by examining the interactions that persisted in the devising process and those that fell through, we conclude with a proposition for design considerations for future agents. Based on emerging research in this space, we focus on the characteristics of personally-owned agents in comparison to shared agents, and consider the roles and functions each introduce in their integration in the home.

Artificial intelligence algorithms have been used to enhance a wide variety of products and services, including assisting human decision making in high-stake contexts. However, these algorithms are complex and have trade-offs, notably between prediction accuracy and fairness to population subgroups. This makes it hard for designers to understand algorithms and design products or services in a way that respects users' goals, values, and needs. We proposed a method to help designers and users explore algorithms, visualize their trade-offs, and select algorithms with trade-offs consistent with their goals and needs. We evaluated our method on the problem of predicting criminal defendants' likelihood to re-offend through (i) a large-scale Amazon Mechanical Turk experiment, and (ii) in-depth interviews with domain experts. Our evaluations show that our method can help designers and users of these systems better understand and navigate algorithmic trade-offs. This paper contributes a new way of providing designers the ability to understand and control the outcomes of algorithmic systems they are creating.

The presence of voice activated personal assistants (VAPAs) in people's homes rises each year [31]. Industry efforts are invested in making interactions with VAPAs more personal by leveraging information from messages and calendars, and by accessing user accounts for 3rd party services. However, the use of personal data becomes more complicated in interpersonal spaces, such as people's homes. Should a shared agent access the information of many users? If it does, how should it navigate issues of privacy and control? Designers currently lack guidelines to help them design appropriate agent behaviors. We used Speed Dating to explore inchoate social mores around agent actions within a home, including issues of proactivity, interpersonal conflict, and agent prevarication. Findings offer new insights on how more socially sophisticated agents might sense, make judgements about, and navigate social roles and individuals. We discuss how our findings might impact future research and future agent behaviors.

Service robots often perform their main functions in public settings, interacting with more than one person at a time. How these robots should handle the affairs of individual users while also behaving appropriately when others are present is an open question. One option is to design for flexible agent embodiment: letting agents take control of different robots as people move between contexts. Through structured User Enactments, we explored how agents embodied within a single robot might interact with multiple people. Participants interacted with a robot embodied by a singular service agent, agents that re-embody in different robots and devices, and agents that co-embody within the same robot. Findings reveal key insights about the promise of re-embodiment and co-embodiment as design paradigms as well as what people value during interactions with service robots that use personalization.

The intersection between social, technical, and economic factors biases new product development to focus on utilitarian value. However, objects that serve alternative goals, behaviors and emotions have accompanied humankind for millennia. This article speculates about robotic objects for one non-utilitarian behavior and its implications: destruction. Robots and objects for destruction have a shared history of embodiment and heavily rely on their embodiment for interaction. Yet the topic of destruction is not very common in the field of human-robot interaction (HRI). Thus, we (1) present a survey of ethnographic investigations that show modes of HRI related to destruction, and (2) develop speculative concepts of interaction that demonstrate these ideas in HRI. By exemplifying a broad range of speculative uses of destruction in HRI and grounding it in literature, we hope this theoretical and conceptual article will bring a fresh perspective on alternative interactions with robots.

Interactions with multiple conversational agents and social robots are becoming increasingly common. This raises new design challenges: Should agents and robots be modeled after humans, presenting their entity (i.e., social presence) as bound to a single body, or should they take advantage of non-human capabilities, such as moving their social presence from body to body across service touchpoints and contexts? We conducted a User Enactments study in which participants interacted with agents that had one social presence per body, that could re-embody (move their social presence from body to body), and that could co-embody (move their social presence into a body that already contains another). Reactions showed that participants felt comfortable with re-embodying agents, who created more seamless and efficient experiences. Yet situations that required expertise or concentration raised concerns about non-human behaviors. We report on our insights regarding collaboration and coordination with several agents in multi-step interactions.

Interactions with social robots in public and private spaces are becoming more and more common and varied. As this trend continues, it is important to understand how a robot's embodiment influences its ability to calibrate trust and comfort with its users and behave in accordance with social norms. This is especially true when one social intelligence embodies multiple physical robots (re-embodiment). We have conducted two studies-one quantitative and and one qualitative-which shed light on the way robots should be embodied and re-embodied by intelligences during different types of social interactions. This paper outlines our previous work on elucidating the role of embodiment in social interactions and experimenting with re-embodiment as a design paradigm, and it describes the directions in which we plan to take this research in the near future.

This is an interesting era for design in terms of the diverse ways that designers need to work. The advent of cloud computing and the sensors in the mobile phones we carry means that there is a vast amount of data collected about what people do. There is a vast opportunity for designers to leverage this data to create products, services and systems that are tailored to individual needs. At the same time, designers at Google are designing products and services that millions of people use every day. This sets up an interesting dichotomy for today's designers, who need to take into account both personal and adaptive and global and scaled in how they think, design, and take action.

In-home, place-based, conversational agents have exploded in popularity over the past three years. In particular, Amazon's conversational agent, Alexa, now dominates the market and is in millions of homes. This paper presents two complementary studies investigating the experience of households living with a conversational agent over an extended period of time. First, we gathered the history logs of 75 Alexa participants and quantitatively analyzed over 278,000 commands. Second, we performed seven in-home, contextual interviews of Alexa owners focusing on how their household interacts with Alexa. Our findings give the first glimpse of how households integrate Alexa into their lives. We found interesting behaviors around purchasing and acclimating to Alexa, in the number and physical placement of devices, and in daily use patterns. Participants also uniformly described interactions between children and Alexa. We conclude with suggestions for future improvement for intelligent conversational agents.

Machine learning (ML) plays an increasingly important role in improving a user's experience. However, most UX practitioners face challenges in understanding ML's capabilities or envisioning what it might be. We interviewed 13 designers who had many years of experience designing the UX of ML-enhanced products and services. We probed them to characterize their practices. They shared they do not view themselves as ML experts, nor do they think learning more about ML would make them better designers. Instead, our participants appeared to be the most successful when they engaged in ongoing collaboration with data scientists to help envision what to make and when they embraced a data-centric culture. We discuss the implications of these findings in terms of UX education and as opportunities for additional design research in support of UX designers working with ML.

Autonomous vehicles have been in development for nearly thirty years and recently have begun to operate in real-world, uncontrolled settings. With such advances, more widespread research and evaluation of human interaction with autonomous vehicles (AV) is necessary. Here, we present an interview study of 32 pedestrians who have interacted with Uber AVs. Our findings are focused on understanding and trust of AVs, perceptions of AVs and artificial intelligence, and how the perception of a brand affects these constructs. We found an inherent relationship between favorable perceptions of technology and feelings of trust toward AVs. Trust in AVs was also influenced by a favorable interpretation of the company's brand and facilitated by knowledge about what AV technology is and how it might fit into everyday life. To our knowledge, this paper is the first to surface AV-related interview data from pedestrians in a natural, real-world setting.

Engagement with social robots is influenced by their appearance and shape. While robots are designed with various features, almost all designs have some form of eyes. In this paper, we evaluate eye design variations for tabletop robots in a lab study, with the goal of learning how they influence participants' perception of the robots' personality and functionality. This evaluation is conducted with non-working “paper prototypes”, a common design methodology which enables quick evaluation of a variety of designs. By comparing sixteen eye designs we found: (1) The more lifelike the design of the eyes was, the higher the robot was rated on personable qualities, and the more suitable it was perceived to be for the home; (2) Eye design did not affect how professional and how suitable for the office the robot was perceived to be. We suggest that designers can use paper prototypes as a design methodology to quickly evaluate variations of a particular feature for social robots.

Human collaborators coordinate effectively their actions through both verbal and non-verbal communication. We believe that the the same should hold for human-robot teams. We propose a formalism that enables a robot to decide optimally between taking a physical action toward task completion and issuing an utterance to the human teammate. We focus on two types of utterances: verbal commands, where the robot asks the human to take a physical action, and state-conveying actions, where the robot informs the human about its internal state, which captures the information that the robot uses in its decision making. Human subject experiments show that enabling the robot to issue verbal commands is the most effective form of communicating objectives, while retaining user trust in the robot. Communicating information about the robot’s state should be done judiciously, since many participants questioned the truthfulness of the robot statements when the robot did not provide sufficient explanation about its actions.

As people generate large quantities of heterogeneous data across their lifetimes, there is an opportunity to consider how we might build digital systems that leverage this information to help people communicate aspects of their life for which they would like to be remembered without the need to directly assign or pass on this information to another person. We present a study that leverages existing research and the use of an online design probe to explore how people think about how they'll be remembered, and how digital systems and information might help shape how people look back on and interpret people's lives after they've passed away. Findings from this work articulate specific challenges and opportunities for building systems to support people's ability to engage with experiences and memories through their digital materials.

Machine learning (ML) is now a fairly established technology, and user experience (UX) designers appear regularly to integrate ML services in new apps, devices, and systems. Interestingly, this technology has not experienced a wealth of design innovation that other technologies have, and this might be because it is a new and difficult design material. To better understand why we have witnessed little design innovation, we conducted a survey of current UX practitioners with regards to how new ML services are envisioned and developed in UX practice. Our survey probed on how ML may or may not have been a part of their UX design education, on how they work to create new things with developers, and on the challenges they have faced working with this material. We use the findings from this survey and our review of related literature to present a series of challenges for UX and interaction design research and education. Finally, we discuss areas where new research and new curriculum might help our community unlock the power of design thinking to re-imagine what ML might be and might do.

Many game designers aim to optimize difficulty to make games that are "not too hard, not too easy." However, recent experiments have shown that even moderate difficulty can reduce player engagement. The present work investigates other design factors that may account for the purported benefits of difficulty, such as choice, novelty and suspense. These factors were manipulated in three design experiments involving over 20,000 play sessions of an online educational game.

We conducted a 2x2 between-subjects experiment to examine the effects of two orientation and two gaze behaviors during group conversations for a mobile, low degree-of-freedom robot. For this experiment, we designed a novel protocol to induce changes in the robot's group and study different social contexts. In addition, we implemented a perception system to track participants and control the robot's orientation and gaze with little human intervention. The results showed that the gaze behaviors under consideration affected the participants' perception of the robot's motion and that its motion affected human perception of its gaze. This mutual dependency implies that robot gaze and body motion must be designed and controlled jointly, rather than independently of each other. Moreover, the orientation behaviors that we studied led to similar feelings of inclusion and sense of belonging to the robot's group, suggesting that both can be primitives for more complex orientation behaviors.

Over the last decade, the idea of a “quantified self” has become increasingly well-known (Swan, 2013). The main premise is to collect and reflect on data about oneself in order to gain new insights...

Personal informatics systems are becoming increasingly prevalent as their price, form, and ease of use improves. Though these systems offer great potential value to users, many systems are hampered by issues that limit their ability to foster engagement, and people often abandon use of these systems without garnering meaningful outcomes. While continued use of these systems is not necessary for all people, there is an opportunity to better support people working towards achievement-based goals.

Death is an inevitable part of life, but digital systems have been slow to address the complex issues that arise when a person passes away. As digital systems have become an increasingly important part people's lives, so too have these systems begun to play a role in a number of practices related to death, such as legacy-making, bereavement, and remembrance. In this paper, we conduct a survey of seventy-five digital systems designed to support these practices. Building on prior work, we analyzed these systems to derive findings that articulate how digital technologies reflect how people think about and engage with death. Based on these findings, we generated strategies designed to help system designers grapple with the complex needs that result from navigating death online.

Teens' financial literacy, their ability to understand financial concepts and make effective decisions, is an important topic in the US. Educational programs targeted at teens have had little impact. Our study investigated if parents should play a role in teaching their teens. We conducted a literature review on teenage financial literacy and a competitive analysis of current tools. We interviewed parents and teens, probing on what teens know and how they learned these concepts. We conducted speed dating sessions, exposing parents and teens to provocative services meant to trigger conversations about financial values. These included a system where parents gave loans and charged interest and a game where teens guessed the prices of family expenses. Results showed a strong interest for tools that allow parents to educate their teens. Concepts worked best when they addressed teens' current needs and when they allowed parents to influence spending based on values.

"Multi-armed bandits" offer a new paradigm for the AI-assisted design of user interfaces. To help designers understand the potential, we present the results of two experimental comparisons between bandit algorithms and random assignment. Our studies are intended to show designers how bandits algorithms are able to rapidly explore an experimental design space and automatically select the optimal design configuration. Our present focus is on the optimization of a game design space. The results of our experiments show that bandits can make data-driven design more efficient and accessible to interface designers, but that human participation is essential to ensure that AI systems optimize for the right metric. Based on our results, we introduce several design lessons that help keep human design judgment in the loop. We also consider the future of human-technology teamwork in AI-assisted design and scientific inquiry. Finally, as bandits deploy fewer low-performing conditions than typical experiments, we discuss ethical implications for bandits in large-scale experiments in education.

In three studies we found further evidence for a previously discovered Human-Robot (HR) asymmetry in moral judgments: that people blame robots more for inaction than action in a moral dilemma but blame humans more for action than inaction in the identical dilemma (where inaction allows four persons to die and action sacrifices one to save the four). Importantly, we found that people's representation of the “robot” making these moral decisions appears to be one of a mechanical robot. For when we manipulated the pictorial display of a verbally described robot, people showed the HR asymmetry only when making judgments about a mechanical-looking robot, not a humanoid robot. This is the first demonstration that robot appearance affects people's moral judgments about robots.

Human-robot collaboration will increasingly take place in human social settings, including contexts where ethical and honest behavior is paramount. How might these robots affect human honesty? In this paper, we present first evidence of how a robot's presence affects people's ethical behavior in a controlled field study. We observed people passing by a food plate marked as “reserved”, comparing three conditions: no observer, a human observer, and a robot observer. We found that a human observer elicits less attention than a robot, but evokes more of a socially normative presence causing people to act honestly. Conversely, we found that a robot observer elicits more attention, engagement, and a monitoring presence. But even though people were suspicious that they were being monitored, they still behaved dishonestly in the robot observer condition.

This paper presents the constructive design research (CDR) of smart domestic environments comprised of smart home infrastructure, smart domestic artifacts and digital services. CDR is an approach that focuses on imagining futures and learning through the making and testing of prototypes to construct new knowledge about how people engage with the world. While the body of research on smart domestic environments includes a wealth of human-centered research, the use of CDR is marginal. Our work demonstrates how such a process engages residents in activities to imagine why people might value smart domestic environments and how they might want to interact with them. Through goal setting activities, paper prototyping, and field-testing of resident designed technology probes, we present use cases, design principles and experiential insights. After sharing these findings, we introduce the emergence of smart domestic environments as possessing persuasive, personified and artful qualities.

As people increasingly turn to digital channels to share, store, and reflect on their lives and experiences, the processes by which they manage the diverse collection of information generated over the course of their lives are changing. These processes, once a matter of hands-on curation and personal meaning making, are now deeply rooted in interactions with digital systems. In this work, we drew from prior research from personalization, memory, and information management to create four interactive, provocative systems. Through sessions with 12 adults from Pittsburgh, PA we used a combination of these systems and interviews to examine how systems might play a role in the near and long term resurfacing of personal and familial digital information. Findings point to an opportunity to create systems that can openly mediate the curation and transmission of digital content, and ways to draw meaning from the differences between how systems and people recall and represent their experiences.

Websites can record individual users' activities and display them in a variety of ways. There is a tradeoff between detail and abstraction in visualization, especially when the amount of content increases and becomes more difficult to process. We conducted an experiment on Mechanical Turk varying the quality, detail, and visual presentation of information about an individual's past work to see how these design features affected perceptions of the worker. We found that providing detail in the display through text increased processing time and led to less positive evaluations. Visually abstract displays required less processing time but decreased confidence in evaluation. This suggests that different design parameters may engender differing psychological processes that influence reactions towards an unknown person.

Eye tracking is a compelling tool for revealing people's spatial-temporal distribution of visual attention. But quality eye tracking hardware is expensive and can only be used with one person at a time. Further, webcam eye tracking systems have significant limitations on head movement and lighting conditions that result in significant data loss and inaccuracies. To address these drawbacks, we introduce a new approach that harnesses the crowd to understand allocation of visual attention. In our approach, crowdsourcing participants use mouse clicks to self-report the positions and trajectory for the following valuable eye tracking measures: first gaze, last gaze and all gazes. We validate our crowdsourcing approach with a user study, which demonstrated good accuracy when compared to a real eye tracker. We then deployed our prototype, GazeCrowd, in a crowdsourcing setting, and showed that it accurately generated gaze heatmaps and trajectory maps. Such an approach will allow designers to evaluate and refine their visual design without requiring the use of limited/expensive eye trackers.

Online collaboration tools enable developers of interactive systems to quickly reach potential users for usability testing. Can these technologies serve designers who seek feedback on user needs during the earliest stages of design? Online needfinding may help designers create products and services that can target a more diverse user population. To explore this, we conducted a feasibility study to compare face-to-face methods with online needfinding sessions. We found that video can sufficiently capture nuanced reactions to preliminary concept storyboards, but that feedback providers need guidance and structure. We then introduce a tool for collecting early-stage design feedback from online participants and conduct a case study with a professional design team. The team conducted needfinding activities with local participants, as well as a cost-equivalent number of online participants The case study demonstrates that combining online crowdsourcing with a video survey tool provides a simple and cost-efficient way to collect early-stage feedback.

In the future, we envision domestic robots to play a large role in our everyday lives. This requires robots able to anticipate our needs and preferences and adapt their behavior. Since current robotics research takes place primarily in laboratory settings, it fails to take into account real users. In this work, we explore how organization occurs in the kitchen through a home study. Our analysis includes qualitative insights towards robot behavior during kitchen organization, an open source dataset of real life kitchens, and a proof-of-concept application of this dataset to the problem of object return.

Most motion in robotics is purely functional, planned to achieve the goal and avoid collisions. Such motion is great in isolation, but collaboration affords a human who is watching the motion and making inferences about it, trying to coordinate with the robot to achieve the task. This paper analyzes the benefit of planning motion that explicitly enables the collaborator's inferences on the success of physical collaboration, as measured by both objective and subjective metrics. Results suggest that legible motion, planned to clearly express the robot's intent, leads to more fluent collaborations than predictable motion, planned to match the collaborator's expectations. Furthermore, purely functional motion can harm coordination, which negatively affects both task efficiency, as well as the participants' perception of the collaboration.

Robots are predicted to serve in environments in which human honesty is important, such as the workplace, schools, and public institutions. Can the presence of a robot facilitate honest behavior? In this paper, we describe an experimental study evaluating the effects of robot social presence on people's honesty. Participants completed a perceptual task, which is structured so as to allow them to earn more money by not complying with the experiment instructions. We compare three conditions between subjects: Completing the task alone in a room; completing it with a non-monitoring human present; and completing it with a non-monitoring robot present. The robot is a new expressive social head capable of 4-DoF head movement and screen-based eye animation, specifically designed and built for this research. It was designed to convey social presence, but not monitoring. We find that people cheat in all three conditions, but cheat equally less when there is a human or a robot in the room, compared to when they are alone. We did not find differences in the perceived authority of the human and the robot, but did find that people felt significantly less guilty after cheating in the presence of a robot as compared to a human. This has implications for the use of robots in monitoring and supervising tasks in environments in which honesty is key.

Current approaches to personalization either presuppose people's needs and automatically tailor services or provide formulaic options for people to customize. We propose a complementary approach to personalization: a reflective strategy that helps people realize what matters to them and enables them to better personalize services themselves. To design this strategy, we first studied the practices of eight personal health service providers. We then tested the strategy's efficacy by building a Fitbit Plan website that encouraged Fitbit users to customize a plan or accept an automatically tailored plan. For one group of users, the website used the reflective strategy to assist in the plan setup process. A two-week between-subjects field experiment showed that the reflective strategy helped motivate users to carry out their plans, increasing their average daily steps by 2,425 steps. Without the reflective strategy, users either set easy goals or failed to carry out system-created plans, ultimately showing no change in their average daily steps. This work suggests that helping people reflect on and connect with their own goals in using a personalized service could advance the effectiveness of the service.

This work presents a method for assisting people in getting out of chairs with a dynamically stable mobile robot. A user study is described in which force profiles and joint trajectories were recorded for a human-human sit-to-stand experiment. These data were used to develop an impedance-based controller designed to allow the ballbot to help people out of chairs. The control strategy is experimentally verified on the ballbot, a balancing mobile robot, exhibiting lean angles of over 15° and applying more than 120 N of assistive force. To our knowledge, this is the first mobile robot to assist people in standing.

Recently drivers have greatly benefited from new vehicular technologies such as in-car navigation systems, but at the same time they can be easily distracted from those technologies. Consequently, creating displays that balance the communication of information with the attentional demand imposed on the driver is of increasing importance. A set of research has been conducted to minimize the driver’s attentional cost toward the navigational displays while driving. However, accurate evaluation methods to assess the effects of these displays in realistic environments are not yet available. This article introduces the backseat driving technique for high-fidelity, safe, and inexpensive evaluation of interaction with in-car displays. This technique makes use of a real vehicle driving on a real road. As a result it allows for the exploration of some types of research questions using audio, visual, and kinesthetic stimulus at least equal in fidelity to very high-end driving simulators, without requiring such a specialized and expensive facility. Further, it allows for the employment of detailed and fine-grained measures of attentional demand, which cannot be safely used with subjects who are actually driving. Although the backseat driving technique can address only some types of questions and so is not a full replacement for high-realism driving simulators, it may offer a new approach, which augments laboratory, simulator, and real driving for many studies. As a part of the work presented here, the backseat driving technique is used to evaluate a previously developed in-car navigation display—the MOVE system. The technique allowed for new questions to be asked, which were not able to be considered in previous laboratory studies, and for the use of study measures that were only previously able to be used in the laboratory due to driving safety concerns. Specifically, the display was shown to work well when real-world stimulus are used to navigate along a real route, reducing the navigation error rate nearly threefold, and up to sixfold when compared to displays providing more or less contextual information. In addition the display was shown to cut total display fixation time (which is time spent looking away from the road) almost in half in both cases.

The creation of a personal legacy is a process through which information, values, and memories are passed down to future generations. This process is inherently subjective, both as a curated collection of the elements of one's life, and as an evolving form of remembrance that is subject to the interpretations of those to whom it is left. Based on directed storytelling sessions with 14 adults from a large Midwestern city in the USA, we explore users' perceptions of how their use of digital systems and information will impact how their lives are interpreted and reflected upon by their families and by future generations. Our findings describe nuances regarding how shifting notions about technological systems and the long-term accessibility of digital information impact the ways in which we share, and subsequently manage, information online. This work, explored here in the context of legacy, exposes opportunities to help users engage with their digital information through the curation of meaningful records, the dispossession of digital debris, and a reexamination of how digital systems and services influence the accessibility and lifespan of digital information.

People worldwide are increasingly acquiring virtual possessions. While virtual possessions have become ubiquitous, little work exists on how people value them, and how their experiences of them differ from material possessions. In this paper, we reflect on and synthesize findings from five studies we conducted over the past five years that investigated people's perceptions of and practices with virtual possessions. Through the higher-level perspective we adopt, we propose three thematic qualities that help characterize people's experiences with virtual possessions, as compared to their material things: placelessness, spacelessness, and formlessness. We draw on these proposed qualities as lenses to help frame future research and practice opportunities for better supporting value construction activities with virtual possessions.

We have developed User Enactments to help support design teams in more successfully investigating radical alterations to technologies' roles, forms and behaviors in uncharted design spaces. To date, no work exists that explicitly unpacks the practical development of a cohesive set of user enactments. Interest is growing in the method with its recent inclusion in a popular design method handbook for practitioners and also as it becomes integrated into graduate-level university curriculum in interaction design. The contribution of this Pictorial is to unpack the thinking and making behind a set of user enactments through visual documentation and annotations.

We describe the design, implementation and deployment of Photobox, a domestic technology that prints four or five randomly selected photos from the owner's Flickr collection at random intervals each month. We deployed Photobox in three homes for fourteen months, to explore how the slow pace at which it operates could support experiences of anticipation and re-visitation of the past. Findings reveal changes in attitude toward the device, from frustration to eventual acceptance. Participants drew on the photos to reflect on past life events and reactions indicated a renewed interest for their Flickr collection. Photobox also provoked reflection on technology in and around the home. These findings suggest several opportunities, such as designing for anticipation, better supporting reflection on the past, and, more generally, expanding the slow technology research program within the HCI community.

A central tenet of HCI is that technology should be user-centric, with designs being based around social science findings about users. Nevertheless a repeated but critical challenge in design is translating empirical findings into actionable ideas that inform design, or generating implications for design. Despite various design methods aiming to bridge this gap, knowledge informing design is still seen as problematic. However there has been little empirical exploration into what design researchers understand by such design knowledge, the functions and principles behind their creation. We report on interviews with twelve expert HCI design researchers probing the roles and types of design implications, and the process of generating and evaluating them. We synthesize different types of design implications into a framework to guide their generation. Our findings identify a broader range than previously described, additional sources and heuristics supporting their development as well some important evaluation criteria. We discuss the value of these findings for interaction design research.

The smart home is here. One area where smart home devices promise to deliver great benefits is in the control of home heating, ventilation, and cooling (HVAC) systems. In this paper, we seek to inform the design of future heating and cooling systems by investigating users' experiences with the Nest Learning Thermostat, a commercially available smart home device. We conducted a qualitative study where we compared people's interactions with conventional thermostats with interactions with the Nest. A key finding was that the Nest impacted users' pattern of HVAC control, but only for a while, and caused new problems in unrealized energy savings. In leveraging these findings, we create a set of design implications for Eco-Interaction, the design of features and human-system interactions with the goal of saving energy.

No abstract available.

In this study, we explored the impact of a co-located sidekick on child-robot interaction. We examined child behaviors while interacting with an expressive furniture robot and his robot lamp sidekick. The results showed that the presence of a sidekick did not alter child proximity, but did increase attention to spoken elements of the interaction. This suggests the addition of a co-located sidekick has potential to increase engagement but may not alter subtle physical interactions associated with personal space and group spatial arrangements. The findings also reinforce existing research by the community on proxemics and anthropomorphism.

Welcome to the Journal of Human-Robot Interaction's first special issue on design! We strongly believe that design is integral to the continued development of the field of HRI, and we have created this special issue to highlight the many ways in which the field of robotics research is influenced by design---and vice versa.

Legacy is the meaningful and complex way in which information, values, and possessions are passed on to others. As digital systems and information become meaningfully parts of people's everyday and social relationships, it is essential to develop new insights about how technology intersects with legacy and inheritance practices. We designed three interactive systems to investigate how digital materials might be passed down in the future. We conducted in-home interviews with ten parents using the systems to provoke discussion about how technology might support or complicate their existing practices. Sessions revealed parents desired to treat their digital information in ways not fully supported by technology. Findings are interpreted to describe design considerations for future work in this emerging space.

One consequence of rapid advances in computer technology is the obsolescence of hundreds of millions of computers each year. This paper explores strategies for increasing the reuse of outdated computers through an investigation of an 8-bit home computer that is still popular in developing countries. We observed the use of the computers in 16 households in Ahmedabad and Bangalore, India in order to gain insight into the contextual factors that support the continued popularity of the device. While most computers become obsolete in less than a decade, this 30-year-old computer technology remains useful because it provides exciting, multi-user family entertainment. While having minimal processing power and virtually no connectivity, the 8-bit computer supports input and output channels that are especially suited for co-located social game play. In contrast, PCs are primarily designed for individual use. Therefore, we offer low-cost design recommendations that would enable outdated PCs to support greater shared use and increased utility within the constrained material context of low-income households. These simple interventions, if adopted by computer refurbishment industries, have the potential to significantly extend the useful lifespan of PCs.

Online games can serve as research instruments to explore the effects of game design elements on motivation and learning. In our research, we manipulated the design of an online math game to investigate the effect of challenge on player motivation and learning. To test the \'1cInverted-U Hypothesis\'1d, which predicts that maximum game engagement will occur with moderate challenge, we produced two large-scale (10K and 70K subjects), multi-factor (2x3 and 2x9x8x4x25) online experiments. We found that, in almost all cases, subjects were more engaged and played longer when the game was easier, which seems to contradict the generality of the Inverted-U Hypothesis. Troublingly, we also found that the most engaging design conditions produced the slowest rates of learning. Based on our findings, we describe several design implications that may increase challenge-seeking in games, such as providing feedforward about the anticipated degree of challenge.

People worldwide are increasingly acquiring collections of virtual possessions. While virtual possessions have become ubiquitous, little work exists on how people value and form attachments to these things. To investigate, we conducted a study with 48 young adults from South Korea, Spain and the United States. The study probed on participants' perceived value of their virtual possessions as compared to their material things, and the comparative similarities and differences across cultures. Findings show that young adults live in unfinished spaces and that they often experience a sense of fragmentation when trying to integrate their virtual possessions into their lives. These findings point to several design opportunities, such as tools for life story-oriented archiving, and insights on better forms of Cloud storage.

A handover is a complex collaboration, where actors coordinate in time and space to transfer control of an object. This coordination comprises two processes: the physical process of moving to get close enough to transfer the object, and the cognitive process of exchanging information to guide the transfer. Despite this complexity, we humans are capable of performing handovers seamlessly in a wide variety of situations, even when unexpected. This suggests a common procedure that guides all handover interactions. Our goal is to codify that procedure.

Constructive design research is a form of research where design activity is a central research activity. One type of constructive design research is critical design, which seeks to disrupt or transgress social and cultural norms. Critical design's advocates have turned to critical theory as an intellectual resource to support their approach. Interestingly, critical design processes remain under-articulated in the growing design research literature. In this paper, we first explain why critical design is so hard to describe as a design practice or process. We then describe two critical design case studies we undertook and the effects we observed them having when place in the field. After sharing our breakdowns and breakthroughs along the way, we offer reflections on designing for provocativeness, the value of deep relationships between researchers and research participants, and the need to plan for and go with a fluid and emergent research plan --- with the goal of helping clarify critical design as an approach.

Designing radically new technology systems that people will want to use is complex. Design teams must draw on knowledge related to people's current values and desires to envision a preferred yet plausible future. However, the introduction of new technology can shape people's values and practices, and what-we-know-now about them does not always translate to an effective guess of what the future could, or should, be. New products and systems typically exist outside of current understandings of technology and use paradigms; they often have few interaction and social conventions to guide the design process, making efforts to pursue them complex and risky. User Enactments (UEs) have been developed as a design approach that aids design teams in more successfully investigate radical alterations to technologies' roles, forms, and behaviors in uncharted design spaces. In this paper, we reflect on our repeated use of UE over the past five years to unpack lessons learned and further specify how and when to use it. We conclude with a reflection on how UE can function as a boundary object and implications for future work.

Barriers to physical activity prevent older adults from meeting recommended physical activity levels necessary for maintaining quality of life. As technology becomes more advanced, we have the opportunity and the responsibility to address concerns faced by the aging population. We seek opportunities for technology to empower older adults to overcome barriers on their own by interviewing and learning from older adults who have successfully overcome these barriers. In this paper, we present a set of needs that technology can address, and considerations for designing technology interventions that support physical activity by older adults.

Prior research has investigated the effect of interactive social agents presented on computer screens or embodied in robots. Much of this research has been pursued in labs and brief field studies. Comparatively little is known about social agents embedded in the workplace, where employees have repeated interactions with the agent, alone and with others. We designed a social robot snack delivery service for a workplace, and evaluated the service over four months allowing each employee to use it for two months. We report on how employees responded to the robot and the service over repeated encounters. Employees attached different social roles to the robot beyond a delivery person as they incorporated the robot's visit into their workplace routines. Beyond one-on-one interaction, the robot created a ripple effect in the workplace, triggering new behaviors among employees, including politeness, protection of the robot, mimicry, social comparison, and even jealousy. We discuss the implications of these ripple effects for designing services incorporating social agents.

Over the past several years, people have acquired more and more virtual possessions. While virtual possessions have become ubiquitous, little work exists to inform designers on how these growing collections should be displayed and how they should behave. We generated four design concepts that changed the form and behavior of these digital things, making them more present within a teen bedroom. We then conducted speed dating sessions to investigate how these new forms and behaviors influence perceptions of value. Sessions revealed how new technologies might better support self-exploration and reflection, as well as how they could complicate identity construction processes. Findings are interpreted to detail opportunities and tensions that can guide future research and practice in this emerging space.

Creating and sustaining rapport between robots and people is critical for successful robotic services. As a first step towards this goal, we explored a personalization strategy with a snack delivery robot. We designed a social robotic snack delivery service, and, for half of the participants, personalized the service based on participants' service usage and interactions with the robot. The service ran for each participant for two months. We evaluated this strategy during a 4-month field experiment. The results show that, as compared with the social service alone, adding personalized service improved rapport, cooperation, and engagement with the robot during service encounters.

The use of autonomous robots in organizations is expected to increase steadily over the next few decades. Although some empirical work exists that examines how people collaborate with robots, little is known about how to best design interfaces to support operators in understanding aspects of the task or tasks at hand. This paper presents a design investigation to understand how interfaces should be designed to support multi-user, multi-robot teams. Through contextual inquiry, concept generation, and concept evaluation, we determine what operators should see, and with what salience different types of information should be presented. We present our findings through a series of design questions that development teams can use to help define interaction and design interfaces for these systems.

In this note, we describe Spark, an informative art display that visualizes physical activity using abstract art. We present results from five deployments, lasting two to three weeks, that suggest that while graph visualizations are useful for information seeking, abstract visualizations are preferred for display purposes. Our results show that informative art is an appropriate way to visualize physical activity, and can be used in addition to graphs to increase enjoyment and engagement with physical activity displays.

When performing physical collaboration tasks, like packing a picnic basket together, humans communicate strongly and often subtly via multiple channels like gaze, speech, gestures, movement and posture. Understanding and participating in this communication enables us to predict a physical action rather than react to it, producing seamless collaboration. In this paper, we automatically learn key discriminative features that predict the intent to handover an object using machine learning techniques. We train and test our algorithm on multi-channel vision and pose data collected from an extensive user study in an instrumented kitchen. Our algorithm outputs a tree of possibilities, automatically encoding various types of pre-handover communication. A surprising outcome is that mutual gaze and inter-personal distance, often cited as being key for interaction, were not key discriminative features. Finally, we discuss the immediate and future impact of this work for human-robot interaction.

During conversations, speakers employ a number of verbal and nonverbal mechanisms to establish who participates in the conversation, when, and in what capacity. Gaze cues and mechanisms are particularly instrumental in establishing the participant roles of interlocutors, managing speaker turns, and signaling discourse structure. If humanlike robots are to have fluent conversations with people, they will need to use these gaze mechanisms effectively. The current work investigates people's use of key conversational gaze mechanisms, how they might be designed for and implemented in humanlike robots, and whether these signals effectively shape human-robot conversations. We focus particularly on whether humanlike gaze mechanisms might help robots signal different participant roles, manage turn-exchanges, and shape how interlocutors perceive the robot and the conversation. The evaluation of these mechanisms involved 36 trials of three-party human-robot conversations. In these trials, the robot used gaze mechanisms to signal to its conversational partners their roles either of two addressees, an addressee and a bystander, or an addressee and a nonparticipant. Results showed that participants conformed to these intended roles 97% of the time. Their conversational roles affected their rapport with the robot, feelings of groupness with their conversational partners, and attention to the task.

There are many physical activity awareness systems available in today's market. These systems show physical activity information (e.g., step counts, energy expenditure, heart rate) which is sufficient for many self-knowledge needs, but information about the factors that affect physical activity may be needed for deeper self-reflection and increased self-knowledge. We explored the use of contextual information, such as events, places, and people, to support reflection on the factors that affect physical activity. We present three findings from our studies. First, users make associations between physical activity and contextual information that help them become aware of factors that affect their physical activity. Second, reflecting on physical activity and context can increase people's awareness of opportunities for physical activity. Lastly, automated tracking of physical activity and contextual information benefits long-term reflection, but may have detrimental effects on immediate awareness.

Icons in graphical user interfaces convey information in a mostly universal fashion that allows users to immediately interact with new applications, systems and devices. In this paper, we define Kineticons - an iconographic scheme based on motion. By motion, we mean geometric manipulations applied to a graphical element over time (e.g., scale, rotation, deformation). In contrast to static graphical icons and icons with animated graphics, kineticons do not alter the visual content or "pixel-space" of an element. Although kineticons are not new - indeed, they are seen in several popular systems - we formalize their scope and utility. One powerful quality is their ability to be applied to GUI elements of varying size and shape from a something as small as a close button, to something as large as dialog box or even the entire desktop. This allows a suite of system-wide kinetic behaviors to be reused for a variety of uses. Part of our contribution is an initial kineticon vocabulary, which we evaluated in a 200 participant study. We conclude with discussion of our results and design recommendations.

The elder population is rising worldwide; in the US, no longer being able to drive is a significant marker of loss of independence. One of the approaches to helping elders drive more safely is to investigate the use of automotive user interface technology, and specifically, to explore the instrument panel (IP) display design to help attract and manage attention and make information easier to interpret.

Influence through information and feedback has been one of the main approaches of persuasive technology. We propose another approach based on behavioral economics research on decision-making. This approach involves designing the presentation and timing of choices to encourage people to make self-beneficial decisions. We applied three behavioral economics persuasion techniques - the default option strategy, the planning strategy, and the asymmetric choice strategy - to promote healthy snacking in the workplace. We tested the strategies in three experimental case studies using a human snack deliverer, a robot, and a snack ordering website. The default and the planning strategies were effective, but they worked differently depending on whether the participants had healthy dietary lifestyles or not. We discuss designs for persuasive technologies that apply behavioral economics.

Over the past several years, people have increasingly acquired virtual possessions. We consider these things to include artifacts that are increasingly becoming immaterial (e.g. books, photos, music, movies) and things that have never traditionally had a lasting material form (e.g. SMS archives, social networking profiles, personal behavior logs). To date, little research exists about how people value and form attachments to virtual possessions. To investigate, we conducted a study with 21 teenagers exploring the perceived value of their virtual possessions, and the comparative similarities and differences with their material things. Findings are interpreted to detail design and research opportunities and issues in this emerging space.

For robots to get integrated in daily tasks assisting humans, robot-human interactions will need to reach a level of fluency close to that of human-human interactions. In this paper we address the fluency of robot-human hand-overs. From an observational study with our robot HERB, we identify the key problems with a baseline hand-over action. We find that the failure to convey the intention of handing over causes delays in the transfer, while the lack of an intuitive signal to indicate timing of the hand-over causes early, unsuccessful attempts to take the object. We propose to address these problems with the use of spatial contrast, in the form of distinct hand-over poses, and temporal contrast, in the form of unambiguous transitions to the hand-over pose. We conduct a survey to identify distinct hand-over poses, and determine variables of the pose that have most communicative potential for the intent of handing over. We present an experiment that analyzes the effect of the two types of contrast on the fluency of hand-overs. We find that temporal contrast is particularly useful in improving fluency by eliminating early attempts of the human.

One goal of assistive robotics is to design interactive robots that can help disabled people with tasks such as fetching objects. When people do this task, they coordinate their movements closely with receivers. We investigated how a robot should fetch and give household objects to a person. To develop a model for the robot, we first studied trained dogs and person-to-person handoffs. Our findings suggest two models of handoff that differ in their predictability and adaptivity.

Previous research has shown that design features that support privacy are essential for new technologies looking to gain widespread adoption. As such, privacy-sensitive design will be important for the adoption of social robots, as they could introduce new types of privacy risks to users. In this paper, we report findings from our preliminary study on users' perceptions and attitudes toward privacy in human-robot interaction, based on interviews that we conducted about a workplace social robot.

We live in a world where many kinds of data about us can be collected and more will be collected as Ubicomp technologies mature. People reflect on this data using different tools for personal informatics. However, current tools do not have sufficient understanding of users' self-reflection needs to appropriately leverage Ubicomp technologies. To design tools that effectively assist self-reflection, we need to comprehensively understand what kinds of questions people have about their data, why they ask these questions, how they answer them with current tools, and what kinds of problems they encounter. To explore this, we conducted interviews with people who use various kinds of tools for personal informatics. We found six kinds of questions that people asked about their data. We also found that certain kinds of questions are more important at certain times, which we call phases. We identified two phases of reflection: Discovery and Maintenance. We discuss the kinds of questions and the phases in detail and identify features that should be supported in personal informatics tools for which Ubicomp technologies can play an important role.

Handing over objects to humans is an essential capability for assistive robots. While there are infinite ways to hand an object, robots should be able to choose the one that is best for the human. In this paper we focus on choosing the robot and object configuration at which the transfer of the object occurs, i.e. the hand-over configuration. We advocate the incorporation of user preferences in choosing hand-over configurations. We present a user study in which we collect data on human preferences and a human-robot interaction experiment in which we compare hand-over configurations learned from human examples against configurations planned using a kinematic model of the human. We find that the learned configurations are preferred in terms of several criteria, however planned configurations provide better reachability. Additionally, we find that humans prefer hand-overs with default orientations of objects and we identify several latent variables about the robot's arm that capture significant human preferences. These findings point towards planners that can generate not only optimal but also preferable hand-over configurations for novel objects.

We present a new tongue input device, the tongue joystick, for use by an actor inside an articulated-head character costume. Using our device, the actor can maneuver through a dialogue tree, selecting clips of prerecorded audio to hold a conversation in the voice of the character. The device is constructed of silicone sewn with conductive thread, a unique method for creating rugged, soft, low-actuation force devices. This method has application for entertainment and assistive technology. We compare our device against other portable mouth input devices, showing it to be the fastest and most accurate in tasks mimicking our target application. Finally, we show early results of an actor inside an articulated-head costume using the tongue joystick to interact with a child.

While the HCI community has long investigated issues of designing for family and the home, very little attention has focused on the lives of divorced families and the ways in which interactive systems might be better designed to address the very real and growing issues they face. In this paper we present an overview of related research on divorce and families. We then report field evidence from 13 in depth interviews conducted with families of parents and children in joint custody situations, and unpack key emergent problems and tensions. We conclude with a discussion of the design implications and opportunities that give shape to how the HCI community may be able to have a positive effect on this set of potential users. The overarching goal of this research is to better understand how the HCI community might begin to approach designing for this alternative family.

For more than forty years, researchers have detailed how people develop attachments to their material possessions as they create and evolve a sense of self. Over the past several years people have increasingly acquired virtual possessions. These include both possessions that are losing their material integrity (books, photos, music, movies) as well as things that have never had material form (e.g. email archives, social networking profiles, personal behavior logs). However, little is known about how people perceive, value, and form attachments to their virtual possessions. To investigate, we conducted a study with teens exploring their virtual possessions. Preliminary findings reveal three key themes and suggest emerging interaction design opportunities for new forms for people's virtual things.

The field of HCI is experiencing a growing interest in Research through Design (RtD), a research approach that employs methods and processes from design practice as a legitimate method of inquiry. We are interested in expanding and formalizing this research approach, and understanding how knowledge, or theory, is generated from this type of design research. We conducted interviews with 12 leading HCI design researchers, asking them about design research, design theory, and RtD specifically. They were easily able to identify different types of design research and design theory from contemporary and historical design research efforts, and believed that RtD might be one of the most important contributions of design researchers to the larger research community. We further examined three historical RtD projects that were repeatedly mentioned in the interviews, and performed a critique of current RtD practices within the HCI research and interaction design communities. While our critique summarizes the problems, it also shows possible directions for further developments and refinements of the approach.

The design of in-vehicle navigation systems fails to take into account the social nature of driving and automobile navigation. In this paper, we consider navigation as a social activity among drivers and navigators to improve design of such systems. We explore the implications of moving from a map-centered, individually-focused design paradigm to one based upon collaborative human interaction during the navigation task. We conducted a qualitative interaction design study of navigation among three types of teams: parents and their teenage children, couples, and unacquainted individuals. We found that collaboration varied among these different teams, and was influenced by social role, as well as the task role of driver or navigator. We also found that patterns of prompts, maneuvers, and confirmations varied among the three teams. We identify overarching practices that differ greatly from the literature on individual navigation. From these discoveries, we present design implications that can be used to inform future navigation systems.

People strive to obtain self-knowledge. A class of systems called personal informatics is appearing that help people collect and reflect on personal information. However, there is no comprehensive list of problems that users experience using these systems, and no guidance for making these systems more effective. To address this, we conducted surveys and interviews with people who collect and reflect on personal information. We derived a stage-based model of personal informatics systems composed of five stages (preparation, collection, integration, reflection, and action) and identified barriers in each of the stages. These stages have four essential properties: barriers cascade to later stages; they are iterative; they are user-driven and/or system-driven; and they are uni-faceted or multi-faceted. From these properties, we recommend that personal informatics systems should 1) be designed in a holistic manner across the stages; 2) allow iteration between stages; 3) apply an appropriate balance of automated technology and user control within each stage to facilitate the user experience; and 4) explore support for associating multiple facets of people's lives to enrich the value of systems.

The mental structures that people apply towards other people have been shown to influence the way people cooperate with others. These mental structures or schemas evoke behavioral scripts. In this paper, we explore two different scripts, receptionist and information kiosk, that we propose channeled visitors' interactions with an interactive robot. We analyzed visitors' typed verbal responses to a receptionist robot in a university building. Half of the visitors greeted the robot (e.g., "hello") prior to interacting with it. Greeting the robot significantly predicted a more social script: more relational conversational strategies such as sociable interaction and politeness, attention to the robot's narrated stories, self-disclosure, and less negative/rude behaviors. The findings suggest people's first words in interaction can predict their schematic orientation to an agent, making it possible to design agents that adapt to individuals during interaction. We propose designs for interactive computational agents that can elicit people's cooperation.

Robots that operate in the real world will make mistakes. Thus, those who design and build systems will need to understand how best to provide ways for robots to mitigate those mistakes. Building on diverse research literatures, we consider how to mitigate breakdowns in services provided by robots. Expectancy-setting strategies forewarn people of a robot's limitations so people will expect mistakes. Recovery strategies, including apologies, compensation, and options for the user, aim to reduce the negative consequence of breakdowns. We tested these strategies in an online scenario study with 317 participants. A breakdown in robotic service had severe impact on evaluations of the service and the robot, but forewarning and recovery strategies reduced the negative impact of the breakdown. People's orientation toward services influenced which recovery strategy worked best. Those with a relational orientation responded best to an apology; those with a utilitarian orientation responded best to compensation. We discuss robotic service design to mitigate service problems.

With a focus on presenting information at the right time, the ubicomp community can benefit greatly from learning the most salient human measures of cognitive load. Cognitive load can be used as a metric to determine when or whether to interrupt a user. In this paper, we collected data from multiple sensors and compared their ability to assess cognitive load. Our focus is on visual perception and cognitive speed-focused tasks that leverage cognitive abilities common in ubicomp applications. We found that across all participants, the electrocardiogram median absolute deviation and median heat flux measurements were the most accurate at distinguishing between low and high levels of cognitive load, providing a classification accuracy of over 80% when used together. Our contribution is a real-time, objective, and generalizable method for assessing cognitive load in cognitive tasks commonly found in ubicomp systems and situations of divided attention.

A wealth of studies in the field of user experience have tried to conceptualize new measures of product quality and inquire into how the overall goodness of a product is formed on the basis of product quality perceptions. An interesting question relates to how the perception as well as the relative dominance of different product qualities evolve across different phases in the adoption of a product. However, temporality of experience poses substantial challenges to traditional reductive evaluation approaches. In this paper we present an alternative methodological approach for studying how users’ experiences with interactive products develop over time. The approach lies in the elicitation of rich qualitative insights in the form of experience narratives, combined with content-analytical approaches for the aggregation of idiosyncratic insights into generalized knowledge. We describe a tool designed for eliciting rich experience narratives retrospectively, and illustrate this tool by means of a study that inquired into how users’ experiences with mobile phones change over the first 6 months of use. We use the insights of the study to validate and extend a framework of temporality proposed by Karapanos et al. (2009b).

One of the problems with empathic research methods in interaction design is that the leap between findings about people and design is often left undocumented. In this paper, we describe a microsketching, a method for producing rapid concept sketches that emphasizes creative exploration of the aesthetic and interactive possibilities of the individual elements of a technology, rather than seeking to develop a complete product. We discuss the use of microsketching within the design process, and provide a case study of its use with an experienced designer and in a design studio course. We discuss how microsketching can be used to scaffold the leap between data collection and design, to quickly introduce designers outside of the research team to the elements of the design problem, and to teach novice interaction designers how to design the interface and interaction for complex products and systems.

A recent trend in Human-Computer Interaction (HCI) research addresses human needs that go beyond the instrumental, resulting in an increasing body of knowledge about how users form overall evaluative judgments on the quality of interactive products. An aspect largely neglected so far is that of temporality, i.e. how the quality of users' experience develops over time. This paper presents an in-depth, five-week ethnographic study that followed 6 individuals during an actual purchase of the Apple iPhone". We found prolonged use to be motivated by different qualities than the ones that provided positive initial experiences. Overall, while early experiences seemed to relate mostly to hedonic aspects of product use, prolonged experiences became increasingly more tied to aspects reflecting how the product becomes meaningful in one's life. Based on the findings, we promote three directions for CHI practice: designing for meaningful mediation, designing for daily rituals, and designing for the self.

We present the design of the Snackbot, a robot that will deliver snacks in our university buildings. The robot is intended to provide a useful, continuing service and to serve as a research platform for long-term Human-Robot Interaction. Our design process, which occurred over 24 months, is documented as a contribution for others in HRI who may be developing social robots that offer services. We describe the phases of the design project, and the design decisions and tradeoffs that led to the current version of the robot.

This paper presents a method for improving the runtime of an optimal heuristic path planner (A*) so that it can run repeatedly, in real-time, in a dynamic environment. This is necessary for mobile robots navigating in dynamic environments that have moving obstacles with associated costs, such as personal space around people or buffer zones around dangerous vehicles. Our approach is to modify the search space used by the A* algorithm, increasing the size of grid cells further from the robot. This approach relies on the notion that only the area closest to the robot needs to be searched carefully; areas further from the robot can be searched more coarsely. Because the planner is assumed to run repeatedly as the robot moves, the robot will always have a fine-grained path defined for its next action. We have experimentally verified in simulation that this algorithm can be run in real-time and produces paths that are comparable to full-resolution planning.

This paper introduces the COMPANION framework: a constraint-optimizing method for person-acceptable navigation. In this framework, human social conventions, such as personal space and tending to one side of hallways, are represented as constraints on the robot's navigation. These constraints are accounted for at the global planning level. In this paper, we present the rationale for, and implementation of, this framework, and we describe the experiments we have run in simulation to verify that the method produces human-like behavior in a mobile robot. Our approach is novel in that it can express an arbitrary number of social conventions and explicitly accounts for these conventions in the planning phase.

Robots are becoming increasingly integrated into the workplace, impacting organizational structures and processes, and affecting products and services created by these organizations. While robots promise significant benefits to organizations, their introduction poses a variety of design challenges. In this paper, we use ethnographic data collected at a hospital using an autonomous delivery robot to examine how organizational factors affect the way its members respond to robots and the changes engendered by their use. Our analysis uncovered dramatic differences between the medical and post-partum units in how people integrated the robot into their workflow and their perceptions of and interactions with it. Different patient profiles in these units led to differences in workflow, goals, social dynamics, and the use of the physical environment. In medical units, low tolerance for interruptions, a discrepancy between the perceived cost and benefits of using the robot, and breakdowns due to high traffic and clutter in the robot's path caused the robot to have a negative impact on the workflow and staff resistance. On the contrary, post-partum units integrated the robot into their workflow and social context. Based on our findings, we provide design guidelines for the development of robots for organizations.

Experience sampling method (or ESM) is a common data collection method to understand user behavior and to evaluate ubiquitous computing technologies. However, ESM studies often demand too much time and commitment from participants, which leads to attrition and low compliance among participants. We introduce a new approach called experience sampling with feedback or ES+feedback that improves compliance by giving feedback to participants through various visualizations. Providing feedback to users makes the information personally relevant and increases the value of the study to participants, which increases their compliance. Our exploratory study shows that ES+feedback increases the compliance rate by 23%.

For years the HCI community has struggled to integrate design in research and practice. While design has gained a strong foothold in practice, it has had much less impact on the HCI research community. In this paper we propose a new model for interaction design research within HCI. Following a research through design approach, designers produce novel integrations of HCI research in an attempt to make the right thing: a product that transforms the world from its current state to a preferred state. This model allows interaction designers to make research contributions based on their strength in addressing under-constrained problems. To formalize this model, we provide a set of four lenses for evaluating the research contribution and a set of three examples to illustrate the benefits of this type of research.

Robots that work with people foster social relationships between people and systems. The home is an interesting place to study the adoption and use of these systems. The home provides challenges from both technical and interaction perspectives. In addition, the home is a seat for many specialized human behaviors and needs, and has a long history of what is collected and used to functionally, aesthetically, and symbolically fit the home. To understand the social impact of robotic technologies, this paper presents an ethnographic study of consumer robots in the home. Six families' experience of floor cleaning after receiving a new vacuum (a Roomba robotic vacuum or the Flair, a handheld upright) was studied. While the Flair had little impact, the Roomba changed people, cleaning activities, and other product use. In addition, people described the Roomba in aesthetic and social terms. The results of this study, while initial, generate implications for how robots should be designed for the home.

We are developing robots with socially appropriate spatial skills not only to travel around or near people, but also to accompany people side-by-side. As a step toward this goal, we are investigating the social perceptions of a robot's movement as it follows behind a person. This paper discusses our laser-based person-tracking method and two different approaches to person-following: direction-following and path-following. While both algorithms have similar characteristics in terms of tracking performance and following distances, participants in a pilot study rated the direction-following behavior as significantly more human-like and natural than the path-following behavior. We argue that the path-following method may still be more appropriate in some situations, and we propose that the ideal person-following behavior may be a hybrid approach, with the robot automatically selecting which method to use.

This talk will focus on design as a means to discover and understand the how to best design future robotic products. One important consideration is how to understand the human experience of use of these systems. Robotic products are a class of social products, artifacts, services, and systems that have social meaning and implications for people's social behavior and relationships. In this talk, I will begin with historic examples of products that inspired surprising and unintended social behaviors. I will then focus on robotic products specifically, showing how our research seeks to understand how simple social attributes in robotic products and systems makes them easier to adopt and less stigmatizing. In specific, I will discuss a set of particular design cues — gaze, motion, and speech and sound, and the concept of personality derived collectively from these primitives — discuss how alone and in combination, they might foster the adoption and use of robotic products and systems.

In this paper, we present a methodology for recognizing seated postures using data from pressure sensors installed on a chair. Information about seated postures could be used to help avoid adverse effects of sitting for long periods of time, or to predict a user’s activities as input to a humancomputer interface. Our approach to posture recognition avoids the use of expensive hardware and complex prediction algorithms while providing recognition for users, for whom the classifier is not trained, using a near-optimal sensor placement strategy. We evaluated the performance of our technology in a series of empirical evaluations including (1) cross-validation experiments (classification accuracy of 87% for ten postures), and (2) a physical deployment of our system (78% classification accuracy).

Text-based interpersonal communication tools such as instant messenger are widely used today. These tools often feature emoticons that people use to express emotion to some degree. However, emoticons still lack the ability to communicate the details of an emotional response, such as the speaker's tone of voice or intensity of emotion. In this paper, we hypothesize that kinetic typography - text that moves or changes over time - can address some of this problem by enhancing emotional qualities of text communication using its dynamic and expressive properties.This paper presents a study showing that a small sample of designers can create kinetic effects that end-users could employ to consistently convey emotion. In the study, three designers prepared 24 kinetic examples expressing four different emotions. We found that the examples were rated quite consistently by 66 participants. These findings provide a preliminary indication that designers can create predefined kinetic effects which can be applied to a variety of textual messages, and that these effects will reliably convey a particular emotional intent. The findings from this study inform design guidelines for designing an instant messaging client that uses kinetic typography presentation.

In this paper, we explore how dynamic visual cues can be used to create accessible and meaningful social interfaces without raising expectations beyond what is achievable with current technology. Our approach is inspired by research in perceptual causality, which suggests that simple displays in motion can evoke high-level social and emotional content. For our exploration, we iteratively designed and implemented a public social interface using abstraction and motion as design elements. Our interface communicated simple social and emotional content such as displaying happiness when there is high social interaction in the environment. Our qualitative evaluations showed that people frequently and repeatedly interacted with the interface while they tried to make sense of the underlying social content. They also shared their models with others, which led to more social interaction in the environment.

Domestic service robots have long been a staple of science fiction and commercial visions of the future. Until recently, we have only been able to speculate about what the experience of using such a device might be. Current domestic service robots, introduced as consumer products, allow us to make this vision a reality.This paper presents ethnographic research on the actual use of these products, to provide a grounded understanding of how design can influence human-robot interaction in the home. We used an ecological approach to broadly explore the use of this technology in this context, and to determine how an autonomous, mobile robot might "fit" into such a space. We offer initial implications for the design of these products: first, the way the technology is introduced is critical; second, the use of the technology becomes social; and third, that ideally, homes and domestic service robots must adapt to each other.

This paper reports on the results of a long-term experiment in which a social robot's facial expressions were changed to reflect different moods. While the facial changes in each condition were not extremely different, they still altered how people interacted with the robot. On days when many visitors were present, average interactions with the robot were longer when the robot displayed either a "happy" or a "sad" expression instead of a neutral face, but the opposite was true for low-visitor days. The implications of these findings for human-robot social interaction are discussed.

Recent developments in humanoid robotics have made possible a vision of robots in everyday use in the home and workplace. However, little is known about how we should design social interactions with humanoid robots. We explored how co-operation versus competition in a game shaped people's perceptions of ASIMO. We found that in the co-operative interaction, people found the robot more sociable and more intellectual than in the competitive interaction while people felt more positive and were more involved in the task in the competitive condition than in the co-operative condition. Our poster presents these findings with the supporting theoretical background.

Humans use expressions of emotion in a very social manner, to convey messages such as "I'm happy to see you" or "I want to be comforted," and people's long-term relationships depend heavily on shared emotional experiences. We believe that for robots to interact naturally with humans in social situations they should also be able to express emotions in both short-term and long-term relationships. To this end, we have developed an affective model for social robots. This generative model attempts to create natural, human-like affect and includes distinctions between immediate emotional responses, the overall mood of the robot, and long-term attitudes toward each visitor to the robot. This paper presents the general affect model as well as particular details of our implementation of the model on one robot, the Roboceptionist

Recent developments in humanoid robotics have made possible technologically advanced robots and a vision for their everyday use as assistants in the home and workplace. Nonetheless, little is known about how we should design interactions with humanoid robots. In this paper, we argue that adaptation for user attributes (in particular gender) and task structure (in particular a competitive vs. a cooperative structure) are key design elements. We experimentally demonstrate how these two elements affect the user's social perceptions of ASIMO after playing an interactive video game with him

In-vehicle navigation has changed substantially in recent years, due to the advent of computer generated maps and directions. However, these maps are still problematic, due to a mismatch between the complexity of the maps and the attentional demands of driving. In response to this problem, we are developing the MOVE (Maps Optimized for Vehicular Environments) system. This system will provide situationally appropriate map information by presenting information that uses appropriate amounts of the driver's attention. In this paper, we describe our findings of studies to help shape the design of the MOVE system, including studies on map reading and in-vehicle navigation, and studies on the effectiveness of a variety of contextually optimized route map visualizations in a simulated driving context.Results show that contextually optimized displays designed for the MOVE system should significantly reduce perceptual load in the context of driving. In our laboratory experiment there was a six-fold decrease in the total map display fixation time and nearly threefold decrease in the number of glances needed to interpret the contextually optimized display compared to a static display.

Valerie the roboceptionist is the most recent addition to Carnegie Mellon's social robots project. A permanent installation in the entranceway to Newell-Simon hall, the robot combines useful functionality - giving directions, looking up weather forecasts, etc. - with an interesting and compelling character. We are using Valerie to investigate human-robot social interaction, especially long-term human-robot "relationships". Over a nine-month period, we have found that many visitors continue to interact with the robot on a daily basis, but that few of the individual interactions last for more than 30 seconds. Our analysis of the data has indicated several design decisions that should facilitate more natural human-robot interactions.

A person seeking another person's attention is normally able to quickly assess how interruptible the other person currently is. Such assessments allow behavior that we consider natural, socially appropriate, or simply polite. This is in sharp contrast to current computer and communication systems, which are largely unaware of the social situations surrounding their usage and the impact that their actions have on these situations. If systems could model human interruptibility, they could use this information to negotiate interruptions at appropriate times, thus improving human computer interaction.This article presents a series of studies that quantitatively demonstrate that simple sensors can support the construction of models that estimate human interruptibility as well as people do. These models can be constructed without using complex sensors, such as vision-based techniques, and therefore their use in everyday office environments is both practical and affordable. Although currently based on a demographically limited sample, our results indicate a substantial opportunity for future research to validate these results over larger groups of office workers. Our results also motivate the development of systems that use these models to negotiate interruptions at socially appropriate times.

Understanding experience is a critical issue for a variety of professions, especially design. To understand experience and the user experience that results from interacting with products, designers conduct situated research activities focused on the interactions between people and products, and the experience that results. This paper attempts to clarify experience in interactive systems. We characterize current approaches to experience from a number of disciplines, and present a framework for designing experience for interactive system. We show how the framework can be applied by members of a multidisciplinary team to understand and generate the kinds of interactions and experiences new product and system designs might offer.

Designers often borrow from the natural world to achieve pleasing, unobtrusive designs. We have extended this practice by combining living plants with sensors and lights in an interactive display, and by creating a robotic analogue that mimics phototropic behavior. In this paper, we document our design process and report the results of a 2-week field study. We put our living plant display, and its robotic counterpart, in a cafeteria between pairs of trash and recycling containers. Contributions of recyclables or trash triggered directional bursts of light that gradually induced the plant displays to lean toward the more active container. In interviews, people offered explanations for the displays and spoke of caring for the plants. A marginally significant increase in recycling behavior (p=.08) occurred at the display with living plants. Apparent increases also occurred at the robotic display and a unit with only lights. Our findings indicate value in exploring the use of living material and biomimetic forms in displays, and in using lightweight robotics to deliver simple rewards.

Toolkits and other tools have dramatically reduced the time and technical expertise needed to design and implement graphical user interfaces (GUIs) allowing high-quality, iterative, user-centered design to become a common practice. Unfortunately the generation of functioning prototypes for physical interactive devices as not had similar support -- it still requires substantial time and effort by individuals with highly specialized skills and tools. This creates a divide between a designers' ability to explore form and interactivity of product designs and the ability to iterate on the basis of high fidelity interactive experiences with a functioning prototype. To help overcome this difficulty we have developed the Calder hardware toolkit. Calder is a development environment for rapidly exploring and prototyping functional physical interactive devices. Calder provides a set of reusable small input and output components, and integration into existing interface prototyping environments. These components communicate with a computer using wired and wireless connections. Calder is a tool targeted toward product and interaction designers to aid them in their early design process. In this paper we describe the process of gaining an understanding of the needs and workflow habits of our target users to generate a collection of requirements for such a toolkit. We describe technical challenges imposed by these needs, and the specifics of design and implementation of the toolkit to meet these challenges.

Kinetic (dynamic) typography has demonstrated the ability to add significant emotive content and appeal to expressive text, allowing some of the qualities normally found in film and the spoken word to be added to static text. Kinetic typography has been widely and successfully used in film title sequences as well as television and computer-based advertising. However, its communicative abilities have not been widely studied, and its potential has rarely been exploited outside these areas. This is partly due to the difficulty in creating kinetic typography with current tools, often requiring hours of work to animate a single sentence.In this paper, we present the Kinedit system, a basic authoring tool that takes initial steps toward remedying this situation and hence promoting exploration of the communicative potential of kinetic typography for personal communication. Kinedit is informed by systematic study and characterization of a corpus of examples, and iterative involvement and validation by designers throughout the development process. We describe the tool and its underlying technology, usage experiences, lessons learned, and next steps.

A person seeking someone else's attention is normally able to quickly assess how interruptible they are. This assessment allows for behavior we perceive as natural, socially appropriate, or simply polite. On the other hand, today's computer systems are almost entirely oblivious to the human world they operate in, and typically have no way to take into account the interruptibility of the user. This paper presents a Wizard of Oz study exploring whether, and how, robust sensor-based predictions of interruptibility might be constructed, which sensors might be most useful to such predictions, and how simple such sensors might be.The study simulates a range of possible sensors through human coding of audio and video recordings. Experience sampling is used to simultaneously collect randomly distributed self-reports of interruptibility. Based on these simulated sensors, we construct statistical models predicting human interruptibility and compare their predictions with the collected self-report data. The results of these models, although covering a demographically limited sample, are very promising, with the overall accuracy of several models reaching about 78%. Additionally, a model tuned to avoiding unwanted interruptions does so for 90% of its predictions, while retaining 75% overall accuracy.

In order to create and use rich custom appearances, designers are often forced to introduce an unnatural gap into the design process. For example, a designer creating a skin for a music player must separately specify the appearance of the elements in the music player skin and the mapping between these visual elements and the functionality provided by the music player. This gap between appearance and semantic meaning creates a number of problems. We present a set of techniques that allows designers to use their preferred drawing tool to specify both appearance and semantic meaning. We demonstrate our techniques in an unmodified version of Adobe Photoshop®, but our techniques are general and adaptable to nearly any layered drawing package.

Kinetic typography --- text that uses movement or other temporal change --- has recently emerged as a new form of communication. As we hope to illustrate in this paper, kinetic typography can be seen as bringing some of the expressive power of film --- such as its ability to convey emotion, portray compelling characters, and visually direct attention --- to the strong communicative properties of text. Although kinetic typography offers substantial promise for expressive communications, it has not been widely exploited outside a few limited application areas (most notably in TV advertising). One of the reasons for this has been the lack of tools directly supporting it, and the accompanying difficulty in creating dynamic text. This paper presents a first step in remedying this situation --- an extensible and robust system for animating text in a wide variety of forms. By supporting an appropriate set of carefully factored abstractions, this engine provides a relatively small set of components that can be plugged together to create a wide range of different expressions. It provides new techniques for automating effects used in traditional cartoon animation, and provides specific support for typographic manipulations.

The proliferation of wireless handheld devices is placing the World Wide Web in the palms of users, but this convenience comes at a high interactive cost. The Web that came of age on the desktop is ill-suited for use on the small displays of handhelds. Today, handheld browsing often feels like browsing on a PC with a shrunken desktop. Overreliance on scrolling is a big problem in current handheld browsing. Users confined to viewing a small portion of each page often lack a sense of the overall context --- they may feel lost in a large page and be forced to remember the locations of items as those items scroll out of view. In this paper, we present a synthesis of interaction techniques to address these problems. We implemented these techniques in a prototype, WebThumb, that can browse the live Web.

Normally, the primary purpose of an information display is to convey information. If information displays can be aesthetically interesting, that might be an added bonus. This paper considers an experiment in reversing this imperative. It describes the Kandinsky system which is designed to create displays which are first aesthetically interesting, and then as an added bonus, able to convey information. The Kandinsky system works on the basis of aesthetic properties specified by an artist (in a visual form). It then explores a space of collages composed from information bearing images, using an optimization technique to find compositions which best maintain the properties of the artist's aesthetic expression.

This study examined the readabiity.andsubjective preferences of a set of fonts designed for screen display.Two new binary bitmap fonts performed well, suggesting that designers should consider incorporating similar attributes into default fonts for online type.