Wide employment of agents in human–computer interaction (HCI) design has proven to be an effective way to construct robust yet flexible software architecture, in which information communication between the user and the technical system is mediated by many kinds of agents. The new interaction paradigm, evolved from traditional HCI, can be called human–agent interaction (HAI). In HAI, users are provided with a novel social collaborator during their tasks: the software agent (Wooldridge & Jennings, 1995). Obviously, this new interaction element opens a series of design considerations. At its core, HAI invites a more consequent evaluation and application of social psychological concepts to guide the agent’s behaviors during interaction.
Hence, a key question is what we can learn from social interaction research in the human context in order to design user-friendly, adaptive, and effective HAI (e.g., Nass & Moon 2000; Reeves & Nass, 1996). This exploitation of social psychological concepts in interaction design is a logical extension of the user psychological approach to human–technology research (Moran, 1981; Oulasvirta & Saariluoma, 2004)—a paradigm approach that is especially effective in projects where the product or technology is new or where the audience characteristics and habits are not yet well defined (Goschnick & Sterling, 2002; Murray, Schell, & Willis, 1997). Thus, it is ideal for contemporary HAI research pursuing psychologically-based, integral agent architectures (Pasquier, Rahwan, Dignum, & Sonenberg, 2006; Rahwan, 2005). In this vein, it is essential to evaluate core issues such as interpersonal communication, influence, persuasion, and decision making in interaction (e.g., Cialdini, 1984; Eagly & Chaiken, 1984; McGuire, 1969, 1985; Petty & Cacioppo, 1981; Sewell, 1989; Zimbardo & Leippe, 1991).
For instance, one may argue that the way by which agents interact with people should be considerate and comfortable. This applies naturally to the presentation or communication of information to the user in general. Another criterion is to design for effective, that is, influential agent support of user deeds. Because one of agent’s crucial roles is that it can enhance or substitute human user decision making when encountering points of judgment during system tasks, the exertion of persuasive influence is quite central. Therefore, communication skills, including argumentative rhetoric, dialogue strategies, and verbal proficiency, are highly relevant for the agent to effectively argue for its decisions, and to achieve the user’s trust.
The present research concerned agent communication skills and the influence of such in the buildup and sustainment of a trusting collaborative relationship between the user and the agent. The core interest was the agent’s ability to effectively persuade users during decision-making tasks in system interaction (e.g., Fogg, 2003; Parise, Kiesler, Sproull, & Waters, 1999; Stiff & Mongeau, 2002; Stock, Guerini, & Zancanaro, 2006). Persuasive design is an important complement to the traditional usability concept because it specifically addresses socioemotional dimensions of interaction. One problem with the traditional usability perspective is that it presupposes user need or motivation to utilize a tool. However, with the mushrooming of technological solutions, and ever-increasing functionalities built into them, it becomes of growing importance not just to allow users to do in a simple and effective manner what they essentially want to do, but to go above and beyond that, to influence their desire and inclination regarding what they want to do or use.
Agents, as sophisticated extensions to the interaction interface, are of core concern in this context. Agents are conceptualized as supports to user tasks in various ways, but often their use is based on a freedom-of-choice model. As a result, legitimate concerns are not so much whether users can in principal profit from agent use or in what way agent support is beneficial but, rather, whether users are willing to make use of the agent and how this is expressed in human–agent collaborative decision making. Hence, HAI is a suitable and interesting subject in persuasive interaction design research, especially in the context of the spreading relevance of agent technology in industrial applications (e.g., Luck, McBurney, Shehory, & Willmot, 2005; Wooldridge & Jennings, 1995).
Previous research has, for instance, investigated the potential of recommendation agents for electronic shopping to influence the human decision making by shaping user preferences (Häubl & Murray, 2001). Other research projects, such as those pertaining to the RPD enabled (recognition-primed decision) agent, focus on supporting decision-making teams by anticipating information relevant to their decisions based on a shared mental model (Fan & Yen, 2004). The results indicate that human teams, when supported by agents, can perform better in highly time-sensitive situations. Pasquier et al. (2006) developed an argumentation framework for an agent that is best suited to persuade other agents in a particular situation with a given standpoint. Social psychological insight is hereby applied to help in the exploration of belief/decision formation within a single agent and “social” interaction among many agents (Rahwan, 2005), yet not agent–user interaction. Finally, Katagiri, Takahashi, and Takeuchi (2001) reported on two preliminary experimental studies focusing on the nature and the effectiveness of social persuasion in HCI environments. In these types of studies, social factors, such as affiliation, authority and conformity, have been taken into account in interface agent design. Nguyen, Masthoff, and Edwards’ (2007) experiment also suggests that dialog-based systems with the visual appearance of a conversational agent are preferred over systems that use text only. The former are perceived to be more personal and caring, less boring, and, to some extent, easier to follow. However, in spite of these valuable efforts, more research on the issues of collaboration and persuasion in HAI is needed.