Towards enhancing trustworthiness of socially interactive and culture aware robots

Summary

Building fine-tuned socially believable autonomous agents interacting with humans in virtual environments is an important aspect of agent design, as humans are influenced more by virtual agents with a high degree of behavioral realism. However, modeling complex psychological processes such as the trust-building between humans and culturallyadaptable agents in a realistic manner is not a trivial task. When designing cultural features of intelligent agents we suggest using our model that integrates cognitive aspects of trust with culture. Certain thinking patterns are involved when a trustor evaluates the trustworthiness of a trustee and thus builds trust in him/her and finally decides whether to trust the person or not. Scientific literature describes five distinct such cognitive patterns called cognitive trust-building processes (CTBPs). Among other factors influencing how trust among parties is built, such as context or personality, culture shapes the preference for certain CTBPs over others (e.g. preferring to build trust by evaluating motivations over assessing ability to fulfill promised duties). National cultures can be evaluated by a combination of scores of cultural dimensions (CD) (e.g. individualism, masculinity). Drawing on theories from organizational management, cross-cultural psychology and social psychology, our model uses CD values to calculate values for each CTBP, Their order indicates the sequence in which each CTBP might be invoked. Agents would behave more realistically if they responded with trust/distrust behavior towards the user according to the agents designed cultural background and if they would display their own trustbuilding behavior according to their own designed culture. The focus of this paper is on understanding the theoretical underpinnings of the influence of culture on trust-building processes and on explaining how the results of our model can be applied in designing socially believable agents.