Social intelligence in robots has a quite recent history in artificial intelligence and robotics. However, it has become increasingly apparent that social and interactive skills are necessary requirements in many application areas and contexts where robots need to interact and collaborate with other robots or humans. Research on human–robot interaction (HRI) poses many challenges regarding the nature of interactivity and ‘social behaviour’ in robot and humans. The first part of this paper addresses dimensions of HRI, discussing requirements on social skills for robots and introducing the conceptual space of HRI studies. In order to illustrate these concepts, two examples of HRI research are presented. First, research is surveyed which investigates the development of a cognitive robot companion. The aim of this work is to develop social rules for robot behaviour (a ‘robotiquette’) that is comfortable and acceptable to humans. Second, robots are discussed as possible educational or therapeutic toys for children with autism. The concept of interactive emergence in human–child interactions is highlighted. Different types of play among children are discussed in the light of their potential investigation in human–robot experiments. The paper concludes by examining different paradigms regarding ‘social relationships’ of robots and people interacting with them.

Previous work on social categorization has shown that people often use cues such as a person's gender, age, or ethnicity to categorize and form impressions of others. The present research investigated effects of social category membership on the evaluation of humanoid robots. More specifically, participants rated a humanoid robot that either belonged to their in-group or to a national out-group with regard to anthropomorphism (e.g., mind attribution, warmth), psychological closeness, contact intentions, and design. We predicted that participants would show an in-group bias towards the robot that ostensibly belonged to their in-group--as indicated by its name and location of production. In line with our hypotheses, participants not only rated the in-group robot more favourably--importantly, they also anthropomorphized it more strongly than the out-group robot. Our findings thus document that people even apply social categorization processes and subsequent differential social evaluations to robots.©2011 The British Psychological Society.

In this article, I address the question whether or not robots should be social actors and suggest that we do not have much choice but to construe collaborative robots as social actors. Social cues, including emotional displays, serve coordination functions in human interaction and therefore have to be used, even by robots, in order for long-term collaboration to succeed. While robots lack the experiential basis of emotional display, also in human interaction much emotional expression is part of conventional social practice; if robots are to participate in such social practices, they need to produce such signals as well. I conclude that if we aim to share our social spaces with robots, they better be social actors, which may even include the display of emotions. This finding is of empirical as well as philosophical relevance because it shifts the ethical discussion away from the question, how social collaborative robots should be, to the question, what kinds of human-robot collaborations we want.

We conducted an online experiment to study people’s perception of automated computer-written news. Using a 2 × 2 × 2 design, we varied the article topic (sports, finance; within-subjects) and both the articles’ actual and declared source (human-written, computer-written; between-subjects). Nine hundred eighty-six subjects rated two articles on credibility, readability, and journalistic expertise. Varying the declared source had small but consistent effects: subjects rated articles declared as human written always more favorably, regardless of the actual source. Varying the actual source had larger effects: subjects rated computer-written articles as more credible and higher in journalistic expertise but less readable. Across topics, subjects’ perceptions did not differ. The results provide conservative estimates for the favorability of computer-written news, which will further increase over time and endorse prior calls for establishing ethics of computer-written news.

Self-endorsement—depicting the “self” as an endorser of a brand—represents a potentially powerful advertising strategy made possible by new media. This experiment tests the hypothesis that receiving brand recommendations from an intelligent personal assistant believed to be tailored to one’s own characteristics and consumer interests yields higher brand attitude and purchase intention toward the (self-endorsed) brand than receiving brand recommendations from a typical, but not self-tailored, intelligent personal assistant. Because endorsement is a well-known and highly effective advertising strategy, this is a high bar. We present evidence for self-referencing as an underlying mechanism, and perceived interactivity and identification as boundary conditions of self-endorsing. Consumers may show skepticism toward advertising but may not know how to be skeptical of themselves. As consumers outsource their tasks and decisions to new artificial intelligence (AI)-driven devices, they will need to be attentive to new media biases that threaten productive use of these devices.

We define Artificial Intelligence-Mediated Communication (AI-MC) as interpersonal communication in which an intelligent agent operates on behalf of a communicator by modifying, augmenting, or generating messages to accomplish communication goals. The recent advent of AI-MC raises new questions about how technology may shape human communication and requires re-evaluation – and potentially expansion – of many of Computer-Mediated Communication’s (CMC) key theories, frameworks, and findings. A research agenda around AI-MC should consider the design of these technologies and the psychological, linguistic, relational, policy and ethical implications of introducing AI into human–human communication. This article aims to articulate such an agenda.

The Computers are Social Actors (CASA) paradigm was proposed more than two decades ago to understand humans’ interaction with computer technologies. Today, as emerging technologies like social robots become more personal and persuasive, questions of how users respond to them socially, what individual factors leverage the relationship, and what constitutes the social influence of these technologies need to be addressed. A lab experiment was conducted to examine the interactions between individual differences and social robots’ vocal and kinetic cues. Results suggested that users developed more trust in a social robot with a human voice than with a synthetic voice. Users also developed more intimacy and interest in the social robot when it was paired with humanlike gestures. Moreover, individual differences including users’ gender, attitudes toward robots, and robot exposure affected their psychological responses. The theoretical, practical, and ethical value of the findings was further discussed in the study.

This article examines the emerging phenomenon of humanoid social robots and human-humanoid interactions. A central argument of this article is that humanoid social robots belong to a special type of robotic technology used for communicating and interacting with humans. These robotic entities, which can be in either mechanical or digital form, are autonomous, interactive and humanlike. Some of them are used to interact with humans for utilitarian purposes and others are designed to trigger human emotions. Incorporation of such robotic entities into the realm of social life invariably alters the condition as well as the dynamics of human interaction, giving rise to a synthetic society in which humans co-mingle with humanoids. More research is needed to investigate the social and cultural impact of this unfolding robotic revolution.