Chronic multitaskers perform worse on core multitasking skills: memory management, cognitive filtering and task switching, likely due to their inability to filter irrelevant stimuli [17]. Our experiment examines effects of chronic multitasking with task-relevant and irrelevant distractors on analytical writing quality. We found a general switch cost and, when controlling for that cost, effects of chronic multitasking habits: heavy multitaskers write worse essays in the irrelevant condition and better essays in the relevant condition. Our study changes multitasking research paradigms in two fundamental ways: it studied a realistic writing scenario including access to both irrelevant and relevant distractors. We found that the effect of chronic multitasking is complex; heavy multitaskers are seduced by unrelated distractors but able to integrate multiple sources of relevant information.

How people view relationships between humans and robots is an important consideration for the design and acceptance of social robots. Two studies investigated the effect of relational behavior in a human-robot dyad. In Study 1, participants watched videos of a human confederate discussing the Desert Survival Task with either another human confederate or a humanoid robot. Participants were less trusting of both the robot and the person in a human-robot relationship where the robot was dominant toward the person than when the person was dominant toward the robot; these differences were not found for a human pair. In Study 2, participants watched videos of a human confederate having an everyday conversation with either another human confederate or a humanoid robot. Participants who saw a confederate mirror the gestures of a robot found the robot less attractive than when the robot mirrored the confederate; the opposite effect was found for a human pair. Exploratory findings suggest that human-robot relationships are viewed differently than human dyads.

In this exploratory study, participants taking cover from a simulated earthquake interacted with a search-and-rescue robot that assumed one of four different identities, distinguished by varying degrees of autonomy, and whose communications were either clear or noisy. Results showed that identities with low autonomy elicited greater hopefulness from participants than identities with high autonomy. Discussion focuses on design recommendations for search-and-rescue robots, and on the design of immersive HRI experiments.

Designing and building mechatronic systems has gradually ceased to be the domain of only highly trained professionals and has become broadly accessible. Drawing from a notion of designing as a conversation with the materials of the situation we built an artifact that could actively engage in its own making by embedding a Wizard of Oz operated animated agent into an Arduino prototyping platform. In a 2x2 between-participants Wizard of Oz laboratory experiment with (N=68) high-school students we specifically examined how this prototyping agent's expression of interest affected perceptions of the agent and learning outcomes dependent on the embodiment of the agent as embedded in the prototyping material itself or as an external entity. We found evidence that embedding an agent into the prototyping material can positively influence learning processes and outcomes while not harming perceptions of the agent.

The current study (N = 49) took a user-centered approach to explore how level of automation (pedal automated, wheel automated or fully automated driving) and the interface modality (switching automation on or off via touch or voice control) in automated vehicles influence drivers' perceived experience and performance. The results found that full or wheel automation in vehicles was perceived significantly more intelligent than pedal automation. Furthermore, drivers in the pedal automation condition reported greater nervousness when using the touch interface than the voice interface. This tendency was not found among drivers in the full and wheel automation conditions. Drivers who used the voice interface to control automated driving had fewer driving mistakes than those who operated the touch interface. Our findings have important psychological and practical implications for designing a user interface for automated vehicles.

Behavior monitoring is an important part of many recommender systems; however, its effects on users' perceptions of such systems are not well understood. We describe a 2x2 factorial experiment that manipulates a simulated recommender system's monitoring of user behavior (monitoring: present vs. absent) and whom the system is perceived to benefit (benefit: corporate vs. consumer). We find that attitudes toward being monitored are moderated by perceptions about system intentions. We propose an explanatory mechanism and highlight the value of understanding the subjective experience of interacting with recommender systems.

We describe a social visualization system that monitors the vocal arousal levels of the participants in a simulated two-party employment negotiation. In a 3x2 factorial experiment (N = 84), we manipulate two variables of interest for social visualization systems: the feedback configuration of the system's display (participants receive self feedback vs. partner feedback vs. no feedback) and the status of the interactants (high vs. low). Receiving feedback about one's own arousal level has negative consequences for performance in and feelings about the negotiation. Receiving feedback about one's partner's arousal level interacts with status: high-status individuals benefit from the visualization, while low-status individuals do not.

Driving is a challenging task because of the physical, attentional, and emotional demands. When drivers become frustrated by events their negative emotional state can escalate dangerously. This study examines behavioral and attitudinal effects of cognitively reframing frustrating events. Participants (N = 36) were asked to navigate a challenging driving course that included frustrating events such as long lights and being cut-off. Drivers were randomly assigned to three conditions. After encountering a frustrating event, drivers in a reappraisal-down condition heard voice prompts that reappraised the event in an effort to deflate negative reactions. Drivers in the second group, reappraisal-up, heard voice prompts that brought attention to the negative actions of vehicles and pedestrians. Drivers in a silent condition drove without hearing any voice prompts. Participants in the reappraisal-down condition had better driving behavior and reported less negative emotions than participants in the other conditions.

We describe two experiments on whether individual thoughtful effort during online commenting is shaped by situational norms derived from the behavior of social others and the design of the environment, respectively. By measuring the length of participants' comments on a news website, the time taken to write them, and the number of issue-relevant thoughts they contain, we demonstrate that participants conform to high vs. low norms of thoughtfulness manifested through either the apparent behavior of other users or through visual, textual and interactional design features conceptually associated with thoughtfulness. Theoretical and applied insights for designing online participatory environments are discussed.

This paper describes an open source speech translator toolkit created as part of the "Survivor Buddy" project which allows written or spoken word from multiple independent controllers to be translated into either a single synthetic voice, synthetic voices for each controller, or unchanged natural voice of each controller. The human controllers can work over the internet or be physically co-located with the Survivor Buddy. The toolkit is expected to be of use for exploring voice in general human-robot interaction.

In this study, the effect of the user choice on social responses to computer-synthesized speech is investigated. Three previous findings about social responses to computer-synthesized speech (i.e., social identification, proximate source orientation, and similarity attraction) were tested using the choice paradigm. Social identification and proximate source orientation effects were found even when users had chosen a computer voice at their discretion. In addition, the primacy effect in the user choice prevailed: Participants were more likely to select whatever voice that they heard first between two options. The similarity attraction effect, however, was negated by the cognitive dissonance effect after user choices. The robustness of social responses, its implications for human–computer interaction, and the importance of the user choice in voice-interface designs are discussed.

Likert-type scales are used extensively during usability evaluations, and more generally evaluations of interactive experiences, to obtain quantified data regarding attitudes, behaviors, and judgments of participants. Very often this data is analyzed using parametric statistics like the Student t-test or ANOVAs. These methods are chosen to ensure higher statistical power of the test (which is necessary in this field of research and practice where sample sizes are often small), or because of the lack of software to handle multi-factorial designs nonparametrically. With this paper we present to the HCI audience new developments from the field of medical statistics that enable analyzing multiple factor designs nonparametrically. We demonstrate the necessity of this approach by showing the errors in the parametric treatment of nonparametric data in experiments of the size typically reported in HCI research. We also provide a practical resource for researchers and practitioners who wish to use these new methods.

Communication mediating technologies are throwing our voices away from our bodies in situations ranging from voice conference meetings to mass presentations. Physical height is known to influence dominance in interactions between people. This study explores how audio projection technologies also influence dominance behaviors between people. In an exploratory 2 (between-participants: own voice location set spatially high vs. low) x 2 (within-participants: voice agent set spatially high vs. low) mixed-design experiment (N=64), we investigated the psychological effects of voice location upon collaborative decision-making interactions between people and voice agents. We found evidence that suggests the dominating effects of project voices' coming from above can be mitigated by hearing one's own voice projected from above.

As their abilities improve, robots will be placed in roles of greater responsibility and specialization. In these contexts, robots may attribute blame to humans in order to identify problems and help humans make sense of complex information. In a between-participants experiment with a single factor (blame target) and three levels (human blame vs. team blame vs. self blame) participants interacted with a robot in a learning context, teaching it their personal preferences. The robot performed poorly, then attributed blame to either the human, the team, or itself. Participants demonstrated a powerful and consistent negative response to the human-blaming robot. Participants preferred the self-blaming robot over both the human and team blame robots. Implications for theory and design are discussed.

This paper describes the Survivor Buddy human-robot interaction project and how it was used by four middle-school girls to illustrate the scientific process for an episode of "SciGirls", a Public Broadcast System science reality show. Survivor Buddy is a four degree of freedom robot head, with the face being a MIMO 740 multi-media touch screen monitor. It is being used to explore consistency and trust in the use of robots as social mediums, where robots serve as intermediaries between dependents (e.g., trapped survivors) and the outside world (doctors, rescuers, family members). While the SciGirl experimentation was neither statistically significant nor rigorously controlled, the experience makes three contributions. It introduces the Survivor Buddy project and social medium role, it illustrates that human-robot interaction is an appealing way to make robotics more accessible to the general public, and raises interesting questions about the existence of a minimum set of degrees of freedom for sufficient expressiveness, the relative importance of voice versus non-verbal affect, and the range and intensity of robot motions.

Receiving poor results from a personalized recommendation system is frustrating. When users try to compensate by putting on a "different face" and game the system, the results can be even more frustrating. This paper investigates how to improve the user experience of such systems by: 1) adding personal photos to increase self-awareness, and 2) providing recommendations interspersed with personal questions. A 2x2 web experiment (N=56) within the context of an online dating match recommendation system was used to assess these two effects. Displaying a person's photo stabilized both response strategies and liking of a recommender's poor suggestions. Additionally, presenting all of the results together at the end was less frustrating than spreading them out. These results demonstrate that simple interface design decisions can have profound effects on user behaviors and attitudes with personalized recommendation systems.

As computational agents become more sophisticated, it will frequently be necessary for the agents to disagree with users. In these cases, it might be useful for the agent to use politeness strategies that defuse the person's frustrations and preserve the human-computer relationship. One such strategy is distancing, which we implemented by spatially distancing an agent's voice from its body. In a 2 (agent disagreement: none vs. some) x 2 (agent voice location: on robotic body vs. in control box) between-participants experiment, we studied the effects of agent disagreement and agent voice location in a collaborative human-agent desert survival task (N=40). People changed their answers more often when agents disagreed with them and felt more similar to agents that always agreed with them, even when substantive content was identical. Strikingly, people felt more positively toward the disagreeing agent whose voice came from a separate control box rather than from its body; for agreement, the body-attached voice was preferred.

Though legislation is increasingly discouraging drivers from holding on to their mobile phones while talking, hands-free devices do not improve driver safety. We offer two design alternatives to improve driver safety in the contexts of voice-based user interfaces and mobile phone conversations in cars' side tones (auditory feedback used in landline phones) and location of speakers. In a 2 (side tone: present vs. not) x 2 (location of speakers: headphones vs. dashboard) between-participants experiment (N=48), we investigated the impact of these features upon driver experience and performance on a simulated mobile phone conversation while driving. Participants became more verbally engaged in the conversation when side tones were present, but also experienced more cognitive load. Participants drove more safely when voices were projected from the dashboard rather than from headphones. Implications for driver user interface design are discussed.

As robots become more pervasive, operators will develop richer relationships with them. In a 2 (robot form: humanoid vs. car) x 2 (assembler: self vs. other) between-participants experiment (N=56), participants assembled either a humanoid or car robot. Participants then used, in the context of a game, either the robot they built or a different robot. Participants showed greater extension of their self-concept into the car robot and preferred the personality of the car robot over the humanoid robot. People showed greater self extension into a robot and preferred the personality of the robot they assembled over a robot they believed to be assembled by another. Implications for the theory and design of robots and human-robot interaction are discussed.

This article presents the results of two experimental laboratory studies that establish relationships between displays and people's attitudes, beliefs, and behaviors toward self, others, and social situations. Experiment I investigates how participants (N = 40) engaging in a trivia game respond when their answers and performance feedback evaluations are made public via either a large shared display or each person's laptop display. Using a 2 (answer display: shared vs. personal) × 2 (feedback display: shared vs. personal) between-participants, nested design, we find that participants exhibit differential levels of social anxiety, enjoyment, willingness to change answers, and attributions of coparticipant competence. Participants whose answers are shown on the shared display exhibit greater social anxiety but are attributed with greater competence by their peers. Viewing information on the shared display induces a greater degree of change in answers. Precisely because all information is public throughout the experiment, we are able to isolate the effects of sharing screens as opposed to sharing information. Experiment II (N = 40) builds from Experiment I by employing similar display configurations within an explicitly persuasive context. In a 2 (display: shared vs. personal) × 2 (context: common vs. personal) × 2 (content presentation style: common vs. interpersonal), mixed experimental design we produce systematic differences in the persuasiveness of information, people's engagement with content, and sense of social distance from each other. Through both experiments strong consistency effects are evident: enjoyment, engagement, and persuasiveness are all diminished where incongruencies are part of the experimental conditions. So too these mismatches increase the sense of social distance from others in the setting. We discuss the implications for future research and design of display ecologies and situated media.

Driving requires focused attention and timely decision making for appropriate maneuvers. This relies on well-timed and accurate information. Designing an in-vehicle information system it is important to ensure that the information for the driver does not negatively affect cognitive processing and driving performance. This study investigates levels of information accuracy necessary in in-vehicle information systems to elicit positive behavioral and attitudinal responses from the driver. In a 2 (gender) by 5 (accuracy: 100%, 88%, 76%, 64% and no system) between-participants study, 100 participants drove in a driving simulator for 25 minutes with an in-vehicle information system designed to inform the driver of hazard and traffic events. Results show that decreasing the accuracy of the system decreased both driving performance and trust and liking of car and in-vehicle system. Female drivers in particular benefit from the in-vehicle system and show higher tolerance of inaccuracies. Design implications for in-vehicle systems are discussed.

We present a study of people's attitudes toward robot workers, identifying the characteristics of occupations for which people believe robots are qualified and desired. We deployed a web-based public-opinion survey that asked respondents (n=250) about their attitudes regarding robots' suitability for a variety of jobs (n=812) from the U.S. Department of Labor's O*NET occupational information database. We found that public opinion favors robots for jobs that require memorization, keen perceptual abilities, and service-orientation. People are preferred for occupations that require artistry, evaluation, judgment and diplomacy. In addition, we found that people will feel more positively toward robots doing jobs with people rather than in place of people.

In a balanced between-participants experiment (N = 96) American and Swedish participants listened to tourist information on a website about an American or Swedish city presented in English with either an American or Swedish accent and evaluated the speakers' knowledge of the topic, the voice characteristics, and the information characteristics. Users preferred accents similar to their own. Similarity-attraction effects were so powerful that same-accents speakers were viewed as being more knowledgeable than different-accent speakers even when the information would be much better-known by the opposite-accent speaker. Implications for similarity-attraction overwhelming expertise are discussed.

A 2x2 enhanced Wizard-of-Oz experiment (N = 32) was conducted to compare two different approaches to presenting information to drivers in easy and difficult driving conditions. Data of driving safety, evaluation of the spoken dialogue system, and perception of self were analyzed. Results show that the user-modeled summarize-and-refine (UMSR) approach led to more efficient information retrieval than did the summarize-and-refine (SR) approach. However, depending on driving condition, higher efficiency did not always translate into pleasant subjective experience. Implications for usability testing and interface design were presented, followed by discussions of future research directions.

Advances in mobile communication technologies have allowed people in more places to reach each other more conveniently than ever before. However, many mobile phone communications occur in inappropriate contexts, disturbing others in close proximity, invading personal and corporate privacy, and more broadly breaking social norms. This paper presents a telephony system that allows users to answer calls quietly and privately without speaking. The paper discusses the iterative process of design, implementation and system evaluation. The resulting system is a VoIP-based telephony system that can be immediately deployed from any phone capable of sending DTMF signals. Observations and results from inserting and evaluating this technology in real-world business contexts through two design cycles of the Touch-Talk feature are reported.

This paper presents results of a Wizard-of-Oz (WoZ) study examining the effect of two different information presentation methods on a secondary task, namely driving. The results demonstrate that the user-model based summarize and refine (UMSR) approach enables more efficient information retrieval in comparison to the data-driven summarize and refine (SR) approach, and does not negatively affect driving performance.

People display adaptive language behaviors in face-to-face conversations, but will computer users do the same during HCI? We report an experiment (N=20) demonstrating that users' use of language (in terms of lexical choice) is influenced by their beliefs and expectations about a system: When users believe that the system is unsophisticated and restricted in capability, they adapt their language to match the system's language more than when they believe the system is relatively sophisticated and capable. Moreover, this tendency is based entirely on users' expectations about the system; it is unaffected by the actual behavior that the system exhibits. Our results demonstrate that interface design engenders particular beliefs in users about a system's capabilities, and that these beliefs can determine the extent to which users adapt to the system. We argue that such effects can be leveraged to improve the quality and effectiveness of human-computer interactions.

This paper explores the relationship between display of feedback (public vs. private) and the basis for evaluation (present vs. absent) of that feedback. Using a controlled, laboratory setting, we employ a fundamentally social, interpersonal context (speed-dating). Two participants (one male and one female) receive real-time performance feedback about either only themselves (private) or about both participants (public). We measure participant perceptions of monitoring, conformity, and self-consciousness about themselves and their dating partner. We also assess perceptions of system invasiveness, system competence, and system support. Results reveal a consistent pattern of significant interaction between feedback display and basis for evaluation conditions. In each of these interactions, public feedback with an added, trivial, basis for evaluation creates significantly lower perception of monitoring, conformity, self-consciousness, and system invasiveness, than the other three conditions. Additionally there is a main effect for basis for evaluation with respect to system competence and supportiveness. In each case, the presence of a basis produces more positive assessments than its absence. The experiment shows that reactions to being monitored and evaluated do not differ strictly along the dimension of public vs. private; basis for evaluation of feedback functions as a mediator and thus co-determines participant attitudinal responses. We discuss the implications of this at several levels, and present a broader cultural explanation in terms of the theory of rationalization. We also discuss the issues around and functionality of linking laboratory settings to larger cultural contexts in this and related fields of inquiry.

There is a long tradition in psychology asking the question, "how does a body affect how people think and respond?" There is a much smaller literature addressing the question, "how does having a body affect how people think about us and respond to us?" In this talk, I will discuss a series of experimental studies that are guided by the idea that an understanding of people's responses to other people can guide research on human-robot interaction. Questions to be addressed include: When should a robot say "I"? Should robots have body parts that do not operate like human body parts? When should robots use synthetic speech as compared to recorded speech? How should teams of robots interact with teams of people? How should robots respond to human error and their own errors? For each study, I will describe theory, methods, results, and application to design.

In this paper, we present a study concerning psychological ownership for digital entities in the context of collaborative working environments. In the first part of the paper we present a conceptual framework of ownership: various issues such as definition, effects, target factors and behavioral manifestation are explicated. We then focus on ownership marking, a behavioral manifestation that is closely tied to psychological ownership. We designed an experiment using DiamondTouch Table to investigate the effect of two of the most widely used ownership markers on users' attitudes and performance. Both performance and attitudinal differences were found, suggesting the significant role of ownership and ownership markers in the groupware and interactive workspaces design.

In this paper, we propose a software platform for realizing applications using socially-intelligent agents. Socially-intelligent agents are software agents which employ social intelligence. Although there exist many types of social intelligence, we focus on a type of social intelligence for providing emotional support. Applying the type of social intelligence, our socially-intelligent agents behave like people by simulating social behavior of people. We show how we realize the socially-intelligent agents through an explanation on the conceptual architecture of our software platform. We also show the mechanism for generating social behavior which makes our software platform unique. According to the theory of media equation, we expected socially-intelligent agents will cause good effect for users. To justify our expectation, we implemented an application of our socially-intelligent agents for eLearning. We give explanation about the application and how socially-intelligent agents work in it. We also discuss our ideas on social intelligence and show our direction for future works.

When devices become less visible and recede to the background, what kinds of influences would they have on users'? This paper presents two experiments (N=48 and N=96) that examine the effects of four different types of microphones (and voice vs. text output) on user's behaviors and attitudes. The microphones differ with respect to their visibility and users' mobility. Participants performed two different tasks: a standard creativity task and a standard disclosure task. Mobility facilitated creativity and disclosure of personal information. Recording reminder discouraged creativity and disclosure. Output modality had no significant effect. Implications for ubiquitous computing and voice user interfaces are discussed.

As robot technology is evolving and creating a social community between humans and robots, it is necessary to research and develop a new type of intelligence, which we refer to as "social intelligence''. Social intelligence enables natural and socially appropriate interactions. Its importance is gaining a growing interest among not just the human-computer interaction researchers but also robot technology researchers and developers. This article discusses the definition, importance, and benefits of social intelligence in human and robot collaborative systems. The virtual social environment is employed to implement an experimental social intelligence system because of its low cost and high flexibility. Software robots (i.e. agents) with the social intelligence model have been implemented by featuring an emotion model and a personality model under the virtual environment. The social intelligence model that handles affective responses is based on the theories of personality, emotion, and human-media interaction such as cognitive appraisal theory and media equation. The experiment was conducted with the virtual learning collaborative system to examine the effect of the social intelligence model in the collaborative system. The data showed that the users had more positive impressions about the usefulness and the application and learning experience when the cooperative agent displayed some social responses with personality and emotions. It should be noted here that the cooperative agent did not provide any explicit assistance for the human user such as giving clues and showing answers, and yet the user's evaluation on the usefulness of the learning system was influenced by the social agent. The data also suggested that the cooperative agent contributed to the effectiveness of the learning system.

This study examines the interaction effect between user factors and media factors on feelings of social presence which are critical in the design of virtual reality systems and human computer interfaces. Both Experiment 1 and Experiment 2 show that matching synthesized voice personality to user personality positively affects users' (especially extrovert users') feelings of social presence. Experiment 2 also reveals that users feel a stronger sense of social presence when the personality of synthesized voice matches the personality of textual content than when those two are mismatched. In both experiments, extrovert voice induces a stronger sense of presence than introvert voice. These results provide strong evidence for human's automatic social responses to artificial representations possessing humanistic properties such as language and personality. Finally, we discuss various applications of these findings in the design of human computer interfaces, as well as in the study of presence.

As machine evolution continues, human-machine collaboration systems are increasing their importance. In this paper, a social and intelligent agent is discussed as a strategy for improving the effectiveness and efficiency of human-machine collaboration. The proposed approach uses an embedded mind model, which enables agents to interact with the human user consistently, context-dependently, and socially. The relationship between the mind model, personality, and social behavior of the agents is studied through implementation of a prototype system as an e-learning application.

This study examines the effects of interface adaptation on user performance in HCI and CMC. No studies to date have explored the psychological effects of a combination of software performance monitoring and adaptation. This combination is the focus of the present study. Two competing possible effects of adaptive interfaces are presented: 1) Social facilitation, according to which users with high task confidence should perform better, and users with low task confidence should perform less well because their performance is monitored by the interface; and 2) choking, according to which users with high task confidence should perform less well, and users with low task confidence should perform better because the interface adapts to their performance. A 2 (adaptive vs. non-adaptive) x 2 (high user task confidence vs. low task confidence) x 2 (HCI vs. CMC) laboratory experiment was conducted. Results indicate that for CMC, the social facilitation explanation holds true, while results for HCI were consistent with the choking explanation. Implications for the theory and design of adaptive interfaces are discussed

This paper introduces a new application area for agents in the computer interface: the support of human-human interaction. We discuss an interface agent prototype that is designed to support human-human communication in virtual environments. The prototype interacts with users strategically during conversation, spending most of its time listening. The prototype mimics a party host, trying to find a safe common topic for guests whose conversation has lagged. We performed an experimental evaluation of the prototype's ability to assist in cross-cultural conversations. We designed the prototype to introduce safe or unsafe topics to conversation pairs, through a series of questions and suggestions. The agent made positive contributions to participants' experience of the conversation, influenced their perception of each other and of each others' national group, and even seemed to effect their style of behavior. We discuss the implications of our research for the design of social agents to support human-human interaction.

This study examines whether people would interpret and respond to paralinguistic personality cues in computer-generated speech in the same way as they do human speech. Participants used a book-buying website and heard five book reviews in a 2 (synthesized voice personality: extrovert vs. introvert) by 2 (participant personality: extrovert vs. introvert) balanced, between-subjects experiment. Participants accurately recognized personality cues in TTS and showed strong similarity-attraction effects. Although the content was the same for all participants, when the personality of the computer voice matched their own personality: 1) participants regarded the computer voice as more attractive, credible, and informative; 2) the book review was evaluated more positively; 3) the reviewer was more attractive and credible; and 4) participants were more likely to buy the book. Match of user voice characteristics with TTS had no effect, confirming the social nature of the interaction. We discuss implications for HCI theory and design.

Little published research exists on whether humor is a positive or a negative in task-oriented human-computer interaction (HCI). The prevailing notion is that humor distracts users, wastes their time, and may cause them to take their work less seriously. Two experiments examined the effects of humor in task situations involving HCI and computer-mediated communication (CMC). The studies used the same two-condition (humor or control) between-subjects design and essentially the same experimental method. Thus, data from the studies can be compared in a direct test of the social responses to communication technologies (SRCT) claim that people respond to humans and computers in identical ways. In the first experiment, participants worked on a task, ostensibly with another person in a different room, via a networked computer (CMC). All participants received preprogrammed comments, differing only in whether they contained humor. Humor participants rated the "other person" as more likable and reported greater cooperation with and similarity to this other person. They also made more jokes and responded more sociably. Task time and the amount of effort participants put into the task were unaffected by humor. In the second experiment, participants were told they were interacting with a computer in another room (HCI). The results from Experiment 2 were generally consistent with those from Experiment 1; however, HCI participants were less sociable, demonstrated less mirth, felt less similar to their interaction partner, and spent less time on the task. The results suggest both that humor may enhance likability of an interface and that SRCT theory should be revised. Implications for user-interface design and guidelines for the use of humor in HCI are discussed.

A laboratory experiment examines the claims that (1) humans are susceptible to flattery from computers and (2) the effects of flattery from computers are the same as the effects of flattery from humans. In a cooperative task with a computer, subjects (N=41) received one of three types of feedback from a computer: “sincere praise”, “flattery” (insincere praise) or “generic feedback”. Compared to generic-feedback subjects, flattery subjects reported more positive affect, better performance, more positive evaluations of the interaction and more positive regard for the computer, even though subjects knew that the flattery from the computer was simply noncontingent feedback. Subjects in the sincere praise condition responded similarly to those in the flattery condition. The study concludes that the effects of flattery from a computer can produce the same general effects as flattery from humans, as described in the psychology literature. These findings may suggest significant implications for the design of interactive technologies.

This study investigated the claim that humans will readily form team relationships with computers. Drawing from the group dynamic literature in human-human interactions, a laboratory experiment ( n =56) manipulated identity and interdependence to create team affiliation in a human-computer interaction. The data show that subjects who are told they are interdependent with the computer affiliate with the computer as a team. The data also show that the effects of being in a team with a computer are the same as the effects of being in a team with another human: subjects in the interdependence conditions perceived the computer to be more similar to themselves, saw themselves as more cooperative, were more open to influence from the computer, thought the information from the computer was of higher quality, found the information from the computer friendlier, and conformed more to the computer's information. Subjects in the identity conditions showed neither team affiliation nor the effects of team affiliation.

This paper introduces the multi-dimensional concept of anthropocentrism with respect to computers, the tendency to believe that (1) computers do not possess human physical and psychological capabilities; and (2) it is not acceptable for computers to fill routinized (e.g., auto mechanic), interpretive (e.g., newspaper reporter), and persona) (e.g., baby sitter) roles traditionally held only by people. A mail survey (n = 133) of individuals in Northern California focuses on individual differences rather than differences between technologies. As suggested by the literature on ethnocentrism, experience with other cultures and education are strong predictors of the dimensions of anthropocentrism; surprisingly, experience with computers fails as a predictor.

Article Free Access Share on Computers are social actors Authors: Clifford Nass Department of Communication, Stanford University, Stanford, CA Department of Communication, Stanford University, Stanford, CAView Profile , Jonathan Steuer Department of Communication, Stanford University, Stanford, CA Department of Communication, Stanford University, Stanford, CAView Profile , Ellen R. Tauber Department of Communication, Stanford University, Stanford, CA Department of Communication, Stanford University, Stanford, CAView Profile Authors Info & Claims CHI '94: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsApril 1994Pages 72–78https://doi.org/10.1145/191666.191703Published:24 April 1994Publication History 783citation16,174DownloadsMetricsTotal Citations783Total Downloads16,174Last 12 Months5,437Last 6 weeks619 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 Publisher SiteeReaderPDF