Abstract Taking an action research approach, we engaged in fieldwork with school-based behavioral health care teams to: observe record keeping practices, design and deploy a prototype system addressing key challenges, and reflect on its use. We describe the challenges of capturing behavioral data using both paper and electronic records. Creating records of behaviors requires direct observation, and as a result the record keeping responsibility is challenging to distribute across a care team. Behavioral data on paper must be transferred and prepared for reporting, both inside the organization and to stakeholders outside of the organization. In prototyping a computerized working record, we targeted user needs for capturing details of a behavioral incident in the moment. Challenges persisted through the transition from paper to our prototype, and based on these empirical findings over two years of fieldwork, we present five tensions in representing behavioral data in an electronic health record. These tensions reflect the differences between entering behavioral data into the record for intraorganizational use versus interorganizational use.

The tendency to believe and act on others' misinformation is documented in much prior work. This paper focuses on inaccuracy blindness, the tendency to take a collaborator's poor information at face value, which reduces problem-solving success. We draw on social psychological research from the 1970s showing that evaluative rating scales can prompt a change in perspective. In a series of studies, we prototyped and tested an evaluation prompt meant to encourage skepticism in participant detectives trying to identify a serial killer. In tests of the prototype, the prompt was partially successful in inducing skepticism (Exp. 1), but a larger study (Exp. 2) showed that, despite the evaluation prompt, participants' inaccuracy blindness persisted. This work, and the literature more generally, shows that the tendency to be misled by collaborators' inaccurate information remains a strong phenomenon that is hard to counteract and remains a significant challenge for the CHI community.

Researchers in the field of human-robot interaction (HRI) are celebrating the transition to an official ACM Transactions journal.It is a significant achievement for HRI.This field has faced many challenges, including scarce resources for conducting HRI research, the difficulty of conducting the research itself-integrating hardware and software; building robots that can interact with people; piecing together the intricacies of seeing, thinking, and acting when a person encounters a robot; understanding and shaping ethical norms and standards; and stepping behind the mythologies that have long governed cultural attitudes for and against robots.HRI are presented here.Even as HRI becomes more mature, the core disciplines of the field face many controversies and subtleties that complicate our research questions and activities.Here's an example: It was long thought that human beings can discriminate only the seven so-called universal emotions of surprise, happiness, sadness, anger, disgust, fear, and contempt in others' faces and, therefore, that modeling this ability in a robot would be soon possible.But now, psychologists have reported that people can make much finer-grained emotional distinctions, raising the bar for designing a robot.Advances in technology, machine learning, and data science also present higher standards for what a robot can do with, and for, people.What Do We Need to Learn About Humans?At its core, the science of HRI is a science of interaction, but we cannot assume that the state of being human is a known entity that does not change.We still need to learn more about the following:• the causes and manifestations of people's intentions, so that robots can ascertain them • trust, and what it takes in different cultures to develop and destroy trust

When health services involve long-term treatment over months or years, providers have the ability, not present in acute emergency care, to collaboratively reflect on clients' changing health data and adjust interventions. In this paper, we discuss temporality as a factor in the design of health information technology. We define a temporal spectrum ranging from time-critical services that benefit from standardization to long-term services that require more flexibility. We provide empirical evidence from fieldwork that we performed in organizations providing long-term behavioral and mental health services for children. Our fieldwork in this context complements and provides contrasts to previous CSCW studies performed in time-critical hospital settings. Current literature shows a bias toward standardized records and routines in the implementation of health information technology, a policy that may not be appropriate for long-term health services. We discuss how the design of information systems should vary based on temporal factors.

Animated characters are expected to fulfill a variety of social roles across different domains. To be successful and effective, these characters must display a wide range of personalities. Designers and animators create characters with appropriate personalities by using their intuition and artistic expertise. Our goal is to provide evidence-based principles for creating social characters. In this article, we describe the results of two experiments that show how exaggerated and damped facial motion magnitude influence impressions of cartoon and more realistic animated characters. In our first experiment, participants watched animated characters that varied in rendering style and facial motion magnitude. The participants then rated the different animated characters on extroversion, warmth, and competence, which are social traits that are relevant for characters used in entertainment, therapy, and education. We found that facial motion magnitude affected these social traits in cartoon and realistic characters differently. Facial motion magnitude affected ratings of cartoon characters’ extroversion and competence more than their warmth. In contrast, facial motion magnitude affected ratings of realistic characters’ extroversion but not their competence nor warmth. We ran a second experiment to extend the results of the first. In the second experiment, we added emotional valence as a variable. We also asked participants to rate the characters on more specific aspects of warmth, such as respectfulness, calmness, and attentiveness. Although the characters’ emotional valence did not affect ratings, we found that facial motion magnitude influenced ratings of the characters’ respectfulness and calmness but not attentiveness. These findings provide a basis for how animators can fine-tune facial motion to control perceptions of animated characters’ personalities.

Research indicates that the facial expressions of animated characters and agents can influence people's perceptions and interactions with these entities. We designed an experiment to examine how an interactive animated avatar's facial expressiveness influences dyadic conversations between adults and the avatar. We animated the avatar in realtime using the tracked facial motion of a confederate. To adjust facial expressiveness, we damped and exaggerated the avatar's facial motion. We found that ratings of the avatar's extroversion were positively related to its expressiveness. However, impressions of the avatar's realism and naturalness worsened with increased expressiveness. We also found that the confederate was more influential when she appeared as the damped or exaggerated avatar. Adjusting the expressiveness of interactive animated avatars may be a simple way to influence people's social judgments and willingness to collaborate with animated avatars. These results have implications for using avatar facial expressiveness to improve the effectiveness of avatars in various contexts. Adjusting the expressiveness of interactive animated avatars may be a simple way to influence people's social judgments and willingness to collaborate with animated avatars.

Increasingly, the advice people receive on the Internet is socially transparent in the sense that it displays contextual information about the advice-givers or their actions. We hypothesize that activity transparency -seeing an advice giver's process while creating his or her recommendations - will increase advice taking. We report three experiments testing the effect of activity transparency on taking mediocre advice. We found that the presence of a web history increased the likelihood of following a financial advisor's advice and reduced participant earnings (Exp. 1), especially when the web history implied greater task focus (Exp. 2, 3). CSCW research usually emphasizes how to increase information sharing; this work suggests when shared information may be inappropriate. We suggest ways to counter activity transparency's potential downsides.

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.

Animated characters appear in applications for entertainment, education, and therapy. When these characters display appropriate emotions for their context, they can be particularly effective. Characters can display emotions by accurately mimicking the facial expressions and vocal cues that people display or by damping or exaggerating the emotionality of the expressions. In this work, we explored which of these strategies would be most effective for animated characters. We investigated the effects of altering the auditory and facial levels of expressiveness on emotion recognition accuracy and ratings of perceived emotional intensity and naturalness. We ran an experiment with emotion (angry, happy, sad), auditory emotion level (low, high), and facial motion magnitude (damped, unaltered, exaggerated) as within-subjects factors. Participants evaluated animations of a character whose facial motion matched that of an actress we tracked using an active appearance model. This method of tracking and animation can capture subtle facial motions in real-time, a necessity for many interactive animated characters. We manipulated auditory emotion level by asking the actress to speak sentences at varying levels, and we manipulated facial motion magnitude by exaggerating and damping the actress's spatial motion. We found that the magnitude of auditory expressiveness was positively related to emotion recognition accuracy and ratings of emotional intensity. The magnitude of facial motion was positively related to ratings of emotional intensity but negatively related to ratings of naturalness.

Various mechanisms exist to secure users' passwords, yet users continue to struggle with the complexity of multiple password management. We explore the effectiveness of a feedback loop to improve users' password management. We introduce YourPassword, a web-based application that uses feedback to inform users about the security of their password behavior. YourPassword has two main components: a password behavior checker that converts password strengths into numerical scores and a dashboard interface that visualizes users' overall password behavior and provides visual feedback in real time. YourPassword not only provides a total score on all passwords, but also visualizes when passwords are too similar to each other. To test the efficacy of YourPassword, we conducted a between-subjects experiment and think-aloud test with 48 participants. Participants either had access to YourPassword, an existing commercial password checker, or no password tool (control condition). YourPassword helped participants improve their password behavior as compared with the commercial tool or no tool.

Physical therapists could make better treatment decisions if they had accurate patient home exercise data but today this information is only available from patient self-report. A more accurate source of data could be gained from wearable computing designed for physical therapy exercise support. Existing systems have been tested in the lab but we have little information about issues they may face in home settings. We designed a technology probe, SenseCap, and deployed it for seven days in ten physical therapy patients' homes. SenseCap is a wearable physical therapy support system that gathers patient exercise compliance and performance data and summarizes the data in charts on an iPad Dashboard for physical therapists to view when patients return to the clinic. In this paper, we present the results of our deployment, show in-home patient exercise data gathered by the probe, and make design recommendations based on patient and physical therapist responses.

Interactive animated characters have the potential to engage and educate children, but there is little research on children's interactions with animated characters and real people. We conducted an experiment with 69 children between the ages of 4 and 10 years to investigate how they might engage in conversation differently if their interactive partner appeared as a cartoon character or as a person. A subset of the participants interacted with characters that displayed exaggerated and damped facial motion. The children completed two conversations with an adult confederate who appeared once as herself through video and once as a cartoon character. We measured how much the children spoke and compared their gaze and gesture patterns. We asked them to rate their conversations and indicate their preferred partner. There was no difference in children's conversation behavior with the cartoon character and the person on video, even among those who preferred the person and when the cartoon exhibited altered motion. These results suggest that children will interact with animated characters as they would another person.

Asynchronous collaborative analysis is important in many fields, but information sharing can be a bottleneck. Tools for annotating, organizing, and summarizing information can help, but their value will likely depend on the accuracy of teammates' information. To document this claim, two experiments examined participants' performance on a complex detective task when they asynchronously received information from a teammate in a collaboration tool or received no such information. We found that receiving a progress report containing accurate information was associated with improved performance (vs. no information shared in a tool) but worse performance when the information was inaccurate. Teammates were evaluated as helpful even when they were not. Our findings point to a phenomenon of teammate inaccuracy blindness that arises when teammates provide inaccurate information. We propose some strategies for helping collaborators avoid or lessen this effect.

In this research we set out to discover why and how people seek anonymity in their online interactions. Our goal is to inform policy and the design of future Internet architecture and applications. We interviewed 44 people from America, Asia, Europe, and Africa who had sought anonymity and asked them about their experiences. A key finding of our research is the very large variation in interviewees' past experiences and life situations leading them to seek anonymity, and how they tried to achieve it. Our results suggest implications for the design of online communities, challenges for policy, and ways to improve anonymity tools and educate users about the different routes and threats to anonymity on the Internet.

Autism education programs for children collect and use large amounts of behavioral data on each student. Staff use paper almost exclusively to collect these data, despite significant problems they face in tracking student data in situ, filling out data sheets and graphs on a daily basis, and using the sheets in collaborative decision making. We conducted fieldwork to understand data collection and use in the domain of autism education to explain why current technology had not met staff needs. We found that data needs are complex and unstandardized, immediate demands of the job interfere with staff ability to collect in situ data, and existing technology for data collection is inadequate. We also identified opportunities for technology to improve sharing and use of data. We found that data sheets are idiosyncratic and not useful without human mediation; improved communication with parents could benefit children's development; and staff are willing, and even eager, to incorporate technology. These factors explain the continued dependence on paper for data collection in this environment, and reveal opportunities for technology to support data collection and improve use of collected data.

Workers in microtask work environments such as Mechanical Turk typically do not know if or how they fit into a workflow. The research question we posed here was whether displaying information about the number of other workers doing the same task would motivate better or poorer work quality. In experiment 1, we varied the information about co-workers presented to the worker and the number of his or her co-workers: "you" or "you alone" are doing a task, or "you" plus 5, 15, or 50 co-workers. We compared these conditions with a no-social information control. In experiment 2, we crossed the number of co-workers (5 vs. 50) with the type of incentive (individual or group). Results show that visual presentations of co-workers changed workers' perceptions of co-workers, and that the more co-workers participants perceived, the lower their work quality. We suggest future work to determine the kinds of co-worker information that will reduce or increase work quality in microtask settings.

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.

An emerging Internet trend is greater social transparency, such as the use of real names in social networking sites, feeds of friends' activities, traces of others' re-use of content, and visualizations of team interactions. Researchers lack a systematic way to conceptualize and evaluate social transparency. The purpose of this paper is to develop a framework for thinking about social transparency. This framework builds upon multiple streams of research, including prior work in CSCW on social translucence, awareness, and visual analytics, to describe three dimensions of online behavior that can be made transparent. Based on the framework, we consider the social inferences transparency supports and introduce a set of research questions about social transparency's implications for computer-supported collaborative work and information exchange.

Interdependent tasks in Mechanical Turk (MTurk) can be managed efficiently with a workflow, a sequence of tasks through which work passes to its completion. We ask if workers should be informed about the workflow, which we call workflow transparency. Transparency could motivate workers or induce social loafing. We describe three experiments to determine the effects of workflow transparency in MTurk. We compared a text description of the workflow, a visualization of the workflow, and the combination of text and visualization with a control condition giving no workflow information. Workflow transparency marginally increased volunteerism on a charity identification task (experiment 1) and significantly increased volunteerism and quality on a business identification task (experiment 2). Results were weaker with a less experienced worker sample (experiment 3). We suggest further research on the design of workflow information to increase workers' motivation.

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.

Recorded images of children's activities can be useful to caregivers and clinicians who need behavioral evidence to support children with autism. However, image capture systems for autism are typically complex and provide only a top-down, outsider's view. In this work, we assessed the use of cameras worn by children to record the context of their activities and interactions from their perspective. We used a technology probe to explore how this simple, parent-driven system could be designed for families to adopt in their homes. We present the results of a five-week field study with five families. The system helped parents to (1) see the world from their child's eyes, (2) increase their understanding of their child's needs when their child is uncommunicative, and (3) help them encourage their child's social engagement. We discuss how these systems can be designed and used to their full potential.

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.

People with chronic health problems use online resources to understand and manage their condition, but many such resources can present competing and confusing viewpoints. We surveyed and interviewed with people experiencing prolonged symptoms after a Lyme disease diagnosis. We explore how competing viewpoints in online content affect participants' understanding of their disease. Our results illustrate how chronically ill people search for information and support, and work to help others over time. Participant identity and beliefs about their illness evolved, and this led many to take on new roles, creating content and advising others who were sick. What we learned about online content creation suggests a need for designs that support this journey and engage with complex issues surrounding online health resources.

The CHI community has led efforts to support teamwork, but has neglected team disruption, as may occur if team members relocate to another institution. We studied moves in 548 interdisciplinary research projects with 2691 researchers (PIs). Moves, and thus disruptions, were not rare, especially in large distributed projects. Overall, one-third of all projects experienced at least one member relocating but most moves reflected churn across high-ranking institutions. When collaborators moved, the project was disrupted. Our data suggest that moves exemplify normal disruptions. A design challenge is to help projects adapt to disruption.

Science policy across the world emphasizes the desirability of research teams that can integrate diverse perspectives and expertise into new knowledge, methods, and products. However, integration in research work is not well understood. Based on retrospective interviews with 55 researchers from 52 diverse research projects, we categorized teams as co-acting (50%), coordinated (15%), and integrated (35%). Integration, when it existed, usually began when PIs chose collaborators and pursued integration throughout the project. We describe researchers' experiences and research climates that discouraged or encouraged integration. Implications for policy choices and design include changes in team structuring and technology support.

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.

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.

To accommodate frequent emergencies, interruptions, and delays, hospital staff continually make and coordinate changes to the surgery schedule. The technical and social aspects of coordination in surgical suites have been described by prior studies. This paper addresses an understudied aspect of coordination: the physical environment. Based on a field study of four surgical suites in two large academic centers, we show how the physical layout of hallways and rooms, and barriers and spaces around displays and key coordinators, support or fail to support the common information spaces used for coordination. We use the concept "information hotspots" to represent how physical places and their characteristics facilitate coordination. We developed design principles based on the concept of information hotspots that should guide architectural considerations for coordination in dynamic environments such as hospitals.

In a world of widespread information access, information can overwhelm collaborators, even with visualizations to help. We extend prior work to study the effect of shared information on collaboration. We analyzed the success and discussion process of remote pairs trying to identify a serial killer in multiple crime cases. Each partner had half of the evidence, or each partner had all the available evidence. Pairs also used one of three tools: spreadsheet only (control condition), unshared visualizations, or shared visualization. Visualizations improved analysis over the control condition but this improvement depended on how much evidence each partner had. When each partner possessed all the evidence with visualizations, discussion flagged and pairs showed evidence of more confirmation bias. They discussed fewer hypotheses and persisted on the wrong hypothesis. We discuss the possible reasons for this phenomenon and implications for design of remote collaboration systems to incorporate awareness of intermediate processes important to collaborative success.

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.

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.

Information visualizations can improve collaborative problem solving, but this improvement may depend on whether visualizations promote communication. In an experiment on the effect of network visualizations, remote pairs worked synchronously to identify a serial killer. They discussed disparate evidence distributed across the pair using IM. Four conditions, respectively, offered (a) spreadsheet only (controls), (b) individual unshared visualizations, (c) view-only shared visualizations, and (d) a full-access shared visualization of all evidence. We examined collaborative performance, use of the visualization tool, and communication as a function of condition. All visualization conditions improved remote collaborators' performance over the control condition. Full access to a shared visualization best facilitated remote collaboration by encouraging tool use and fostering discussion between the partners. Shared visualization without full access impaired performance somewhat and made communication even more vital to identifying the serial killer. This study provides direct evidence of visualization tool features and partner behavior that promote collaboration.

Two recent studies of over 500 interdisciplinary research projects have documented comparatively poor outcomes of more distributed projects and the failed coordination mechanisms that partly account for these problems. In this paper we report results of an analysis of dyadic data from the most recent of these studies. The question we asked is, "Does prior experience with a collaborator reduce the barriers of distance or interdisciplinarity?" Analyses of 3911 pairs of collaborators found an answer: "In part, yes!" A prior project with a collaborator predicts greater strength of a current collaborative work tie. Prior experience also reduces the negative impact of distance and disciplinary differences. We discuss the implications of these results for CSCW, given the lack of evidence that today's technology eliminates collaboration barriers in distributed research.

We explored anthropomorphism in people's reactions to a robot in social context vs. their more considered judgments of robots in the abstract. Participants saw a photo and read transcripts from a health interview by a robot or human interviewer. For half of the participants, the interviewer was polite and for the other half, the interviewer was impolite. Participants then summarized the interactions in their own words and responded true or false to adjectives describing the interviewer. They later completed a post-task survey about whether a robot interviewer would possess moods, attitudes, and feelings. The results showed substantial anthropomorphism in participants' interview summaries and true-false responses, but minimal anthropomorphism in the abstract robot survey. Those who interacted with the robot interviewer tended to anthropomorphize more in the post-task survey, suggesting that as people interact more with robots, their abstract conceptions of them will become more anthropomorphic.

We describe Storytelling Alice, a programming environment that introduces middle school girls to computer programming as a means to the end of creating 3D animated stories. Storytelling Alice supports story creation by providing 1) a set of high-level animations, that support the use of social characters who can interact with one another, 2) a collection of 3D characters and scenery designed to spark story ideas, and 3) a tutorial that introduces users to writing Alice programs using story-based examples. In a study comparing girls' experiences learning to program using Storytelling Alice and a version of Alice without storytelling support (Generic Alice), we found that users of Storytelling Alice and Generic Alice were equally successful at learning basic programming constructs. Participants found Storytelling Alice and Generic Alice equally easy to use and entertaining. Users of Storytelling Alice were more motivated to program; they spent 42% more time programming, were more than 3 times as likely to sneak extra time to work on their programs, and expressed stronger interest in future use of Alice than users of Generic Alice.

Watching video online is becoming increasingly popular, and new video streaming technologies have the potential to transform video watching from a passive, isolating experience into an active, socially engaging experience. However, the viability of an active social experience is unclear: both chatting and watching video require attention, and may interfere with one another and detract from the experience. In this paper, we empirically examine the activity of chatting while watching video online. We examine how groups of friends and strangers interact, and find that chat has a positive influence on social relationships, and people chat despite being distracted. We discuss the benefits and opportunities provided by mixing chat and video, uncover some of the attentional and social challenges inherent in this combination of media, and provide guidance for structuring the viewing experience.

HRI researchers interested in social robots have made large investments in humanoid robots. There is still sparse evidence that peoples' responses to robots differ from their responses to computer agents, suggesting that agent studies might serve to test HRI hypotheses. To help us understand the difference between people's social interactions with an agent and a robot, we experimentally compared people's responses in a health interview with (a) a computer agent projected either on a computer monitor or life-size on a screen, (b) a remote robot projected life-size on a screen, or (c) a collocated robot in the same room. We found a few behavioral and large attitude differences across these conditions. Participants forgot more and disclosed least with the collocated robot, next with the projected remote robot, and then with the agent. They spent more time with the collocated robot and their attitudes were most positive toward that robot. We discuss tradeoffs for HRI research of using collocated robots, remote robots, and computer agents as proxies of robots.

When a robot provides direction--as a guide, an assistant, or as an instructor--the robot may have to interact with people of different backgrounds and skill sets. Different people require informat on adapted to their level of understanding. In this paper, we explore the use of two simple forms of awareness that a robot might use to infer that a person needs further verbal elaboration during a tool select on task. First, the robot could use an eye tracker for inferring whether the person is looking at the robot and thus in need of further elaboration. Second, the robot could monitor delays in the individual's task progress, indicating that he or she could use further elaboration. We investigated the effects of these two types of awareness on performance time, selection mistakes, and the number of questions people asked the robot. We did not observe any obvious benefits of our gaze awareness manipulation. Awareness of task delays did reduce the number of questions participants' asked compared to our control condition but did not significantly reduce the number of select on mistakes. The mixed results of our investigation suggest that more research is necessary before we can understand how awareness of gaze and awareness of task delay can be successfully implemented in human-robot dialogue.

Many small online communities would benefit from increased diversity or activity in their membership. Some communities run the risk of dying out due to lack of participation. Others struggle to achieve the critical mass necessary for diverse and engaging conversation. But what tools are available to these communities to increase participation? Our goal in this research was to spark contributions to the movielens.org discussion forum, where only 2% of the members write posts. We developed personalized invitations, messages designed to entice users to visit or contribute to the forum. In two field experiments, we ask (1) if personalized invitations increase activity in a discussion forum, (2) how the choice of algorithm for intelligently choosing content to emphasize in the invitation affects participation, and (3) how the suggestion made to the user affects their willingness to act. We find that invitations lead to increased participation, as measured by levels of reading and posting. More surprisingly, we find that invitations emphasizing the social nature of the discussion forum increase user activity, while invitations emphasizing other details of the discussion are less successful.

A problem with the location-free nature of cell phones is that callers have difficulty predicting receivers' states, leading to inappropriate calls. One promising solution involves helping callers decide when to interrupt by providing them contextual information about receivers. We tested the effectiveness of different kinds of contextual information by measuring the degree of agreement between receivers' desires and callers' decisions. In a simulation, five groups of participants played the role of ‘Callers’, choosing between making calls or leaving messages, and a sixth group played the role of ‘Receivers’, choosing between receiving calls or receiving messages. Callers were provided different contextual information about Receivers' locations, their cell phones' ringer state, the presence of others, or no information at all. Callers provided with contextual information made significantly more accurate decisions than those without it. Our results suggest that different contextual information generates different kinds of improvements: more appropriate interruptions or better avoidance of inappropriate interruptions. We discuss the results and implications for practice in the light of other important considerations, such as privacy and technological simplicity.

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.

Humanoid robots offer many physical design choices such as voice frequency and head dimensions. We used hierarchical statistical mediation analysis to trace differences in people's mental model of robots from these choices. In an experiment, a humanoid robot gave participants online advice about their health. We used mediation analysis to identify the causal path from the robot's voice and head dimensions to the participants' mental model, and to their willingness to follow the robot's advice. The male robot voice predicted impressions of a knowledgeable robot, whose advice participants said they would follow. Increasing the voice's fundamental frequency reduced this effect. The robot's short chin length (but not its forehead dimensions) predicted impressions of a sociable robot, which also predicted intentions to take the robot's advice. We discuss the use of this approach for designing robots for different roles, when people's mental model of the robot matters.

Human-robot interaction could be improved by designing robots that engage in adaptive dialogue with users. An adaptive robot could estimate the information needs of individuals and change its dialogue to suit these needs. We test the value of adaptive robot dialogue by experimentally comparing the effects of adaptation versus no adaptation on information exchange and social relations. In Experiment 1, a robot chef adapted to novices by providing detailed explanations of cooking tools; doing so improved information exchange for novice participants but did not influence experts. Experiment 2 added incentives for speed and accuracy and replicated the results from Experiment 1 with respect to information exchange. When the robot's dialogue was adapted for expert knowledge (names of tools rather than explanations), expert participants found the robot to be more effective, more authoritative, and less patronizing. This work suggests adaptation in human-robot interaction has consequences for both task performance and social cohesion. It also suggests that people may be more sensitive to social relations with robots when under task or time pressure.

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

Online communities need regular maintenance activities such as moderation and data input, tasks that typically fall to community owners. Communities that allow all members to participate in maintenance tasks have the potential to be more robust and valuable. A key challenge in creating member-maintained communities is building interfaces, algorithms, and social structures that encourage people to provide high-quality contributions. We use Karau and Williams' collective effort model to predict how peer and expert editorial oversight affect members' contributions to a movie recommendation website and test these predictions in a field experiment with 87 contributors. Oversight increased both the quantity and quality of contributions while reducing antisocial behavior, and peers were as effective at oversight as experts. We draw design guidelines and suggest avenues for future work from our results.

Email consumes significant time and attention in the workplace. We conducted an organizational survey to understand how and why people attend to incoming email messages. We examined people's ratings of message importance and the actions they took on specific email messages, based on message characteristics and characteristics of receivers and senders. Respondents kept half of their new messages in the inbox and replied to about a third of them. They rated messages as important if they were about work and required action. Importance, in turn, had a modest impact on whether people replied to their incoming messages and whether they saved them. The results indicate that factors other than message importance (e.g., their social nature) also determine how people handle email. Overall, email usage reflects attentional differences due both to personal propensities and to work demands and relationships.

Cell phone conversations distract drivers. This research explores the possibility of reducing distracting by providing callers with remote information about the driver's traffic. We asked whether providing such contextual information would change the caller's conversation such that drivers would be less distracted. In Experiment 1 we examined this question in a low-fidelity driving simulator; in Experiment 2 we examined this question in a higher fidelity simulator. In both experiments, remote callers and passengers were distracting. Providing traffic information to the remote caller significantly reduced crashes in the low fidelity tests and significantly reduced passing in the high fidelity tests, compared with the control conditions. We consider the implications for development of remote displays or signals to promote driving safety.

Effective communication between a person and a robot may depend on whether there exists a common ground of understanding between the two. In two experiments modelled after human-human studies we examined how people form a mental model of a robot’s factual knowledge. Participants estimated the robot’s knowledge by extrapolating from their own knowledge and from information about the robot’s origin and language. These results suggest that designers of humanoid robots must attend not only to the social cues that robots emit but also to the information people use to create mental models of a robot.

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.

We present a study of the effects of instant messaging (IM) on individuals' management of work across multiple collaborative projects. Groups of four participants completed four web design tasks. Each participant worked on two tasks, each task with a different partner who was either co-located or remote, connected via IM. In one condition, each participant had one co-located and one remote partner. In a second condition, both partners were remote. We examined communication, division of labor, and task performance as a function of condition. The results indicated that nearly all participants divided their time unequally between projects, but less unequally in the remote/remote condition. In the co-located/remote condition, participants favored the task with the co-located partner. The results show that the effects of IM differ depending on people's multiple tasks are distributed across space. We propose a new IM interface that promotes awareness of multiple collaborators on multiple tasks.

CSCW as a field has been driven primarily by researchers' desire to solve real world problems of groups and organizations, and to use new technology to solve these problems. The field has accumulated a set of empirically-based interdisciplinary studies and many interesting new applications. The question to be addressed in this panel is whether CSCW as a field is ready for theory--whether theory is needed to move the field along, or on the contrary, whether the problems and the technology are still too new or are changing too fast to accommodate theory. The panelists will describe some of the organization theories that could be applied to CSCW, and debate their usefulness, taking both sides of the question.

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.

Despite advances in technology, nearly everyone experiences technical challenges using home computers and the Internet. In a field trial of household Internet usage, 89% of 93 families needed support from a computer help desk in the 1st year they used the Internet. However, usually only the most technically involved members of the family requested external technical support, and this behavior was associated with other computer-related behaviors in the household. We explore the process by which a family member with comparatively high technical skill or enthusiasm, often a teenager, becomes the family guru, makes external support requests, and becomes the person in the family to whom others turn for technical help. The family guru benefits from this role, influences the household's adoption of technology, and represents an important link between households and computer support professionals. The role also is a fascinating example of the evolution of intergeneration relationships.

Article Communication and information: alternative uses of the Internet in households Share on Authors: Robert Kraut Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PAView Profile , Tridas Mukhopadhyay Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PAView Profile , Janusz Szczypula Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PAView Profile , Sara Kiesler Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PAView Profile , William Scherlis Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, 5000 Forbes Avenue, Carnegie Mellon University, Pittsburgh, PAView Profile Authors Info & Claims CHI '98: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsJanuary 1998 Pages 368–375https://doi.org/10.1145/274644.274695Online:01 January 1998Publication History 32citation2,409DownloadsMetricsTotal Citations32Total Downloads2,409Last 12 Months35Last 6 weeks4 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

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Article Free Access Share on HomeNet: a field trial of residential Internet services Authors: Robert Kraut Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PAView Profile , William Scherlis Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PAView Profile , Tridas Mukhopadhyay Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PAView Profile , Jane Manning Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PAView Profile , Sara Kiesler Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PAView Profile Authors Info & Claims CHI '96: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsApril 1996 Pages 284–291https://doi.org/10.1145/238386.238531Published:13 April 1996Publication History 30citation1,769DownloadsMetricsTotal Citations30Total Downloads1,769Last 12 Months132Last 6 weeks9 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteView all FormatsPDF

Do people disclose more on a computer form than they do in an interview or on a paper form?We report a statistical meta-analysis of the literature from 1969 to 1994.Across 39 studies using I00 measures, computer administration increased self-disclosure.Effect sizes were larger comparing computer administration with face-to-face interviews, when forms solicited sensitive information, and when medical or psychiatric patients were the subjects.Effect sizes were smaller but had not disappeared in recent studies, which we attribute in part to changes in computer interfaces.We discuss research, ethical, policy, and design implications.

We investigated how cooperation with a computer agent was affected by the agent's pictorial realism, humanlikeness, and likability.Participants played a social dilemma game with a talking computer agent that resembled a person, a dog, or a cartoon dog, or with a confederate interacting through a video link.Participants cooperated highly with the person computer agent and with the confederate.They loved the dog and dog cartoon agents, but (excepting dog owners), significantly less with the dog agents, questionnaire results suggest likability than respect in prompting cooperation agent.

People behave differently in the presence of other people than they do when they are alone. People also may behave differently when designers introduce more human-like qualities into computer interfaces. In an experimental study we demonstrate that people's responses to a talking-face interface differ from their responses to a text-display interface. They attribute some personality traits to it; they are more aroused by it; they present themselves in a more positive light. We use theories of person perception, social facilitation, and self-presentation to predict and interpret these results. We suggest that as computer interfaces become more "human-like," people who use those interfaces may change their own personas in response to them.

New computer-based communications technologies make possible new or expanded forms of group work. Although earlier researchers suggest that scant social information in these technologies might cause status equalization in groups, no experimental test of this phenomenon has been made. In a laboratory experiment, we compared face-to-face communication with electronic mail in decision-making groups whose members differed in social status. We examined status in two ways: by varying the external status of group members, and by varying the decision task to manipulate expertise. When the groups made decisions in face-to-face meetings, the high-status member dominated discussions with the three low-status members. Also, the high-status member more often was a "first advocate" in the face-to-face discussions, and first advocates were more influential than later advocates. These status inequalities in face-to-face decision making were pronounced just when the high-status member's expertise was relevant to the decision task. When the same groups made comparable decisions using electronic mail, status and expertise inequalities in participation were reduced. A striking and unexpected result was that "first" advocacy was shared by high- and low-status members in discussions using electronic mail. This behavior resulted in increased equality of influence across status and expertise. We discuss the implications of these results for research and for design of new communication technologies.

With the spread of computer networks, communication via computer conferences, electronic mail, and computer bulletin boards will become more common in society, but little is known about the social psychological implications of these technologies. One possibility is a change in physiological arousal, feelings, and expressive behavior-that is, affect. These computer-mediated communication technologies focus attention on the message, transmit social information poorly, and do not have a well-developed social etiquette. Therefore, these technologies might be associated with less attention to others, less social feedback, and depersonalization of the communication setting. In the present study we examined what would happen to feelings and interpersonal behavior in an experiment in which two people met for the first time and discussed a series of questions in order to get to know one another. We measured physiological arousal (pulse and palmar sweat), subjective affect (emotional state and evaluations), and expressive behavior (self-disclosure and uninhibited behavior) in both synchronous computer-mediated and face-to-face discussions. (For comparison purposes, we also examined these effects under high- and low-evaluation anxiety). Communicating by computer did not influence physiological arousal, and it did not change emotions or self-evaluations. However, people who communicated by computer evaluated each other less favorably than did people who communicated face-to-face, they felt and acted as though the setting was more impersonal, and their behavior was more uninhibited. These findings suggest that computer-mediated communication, rather than provoking emotionality per se, elicits asocial or unregulated behavior. Of course, our data are based on a laboratory experiment using just one type of computer-mediated communication, but the results are generally consistent with anecdotal evidence and new field research on how people use computers to communicate in organizations.