Machines Like Us and People Like You: Toward Human–Robot Shared Experience

Abstract

In the past years, the field of collaborative robots has been developing fast, with applications ranging from health care to search and rescue, construction, entertainment, sports, and many others. However, current social robotics is still far from the general abilities we expect in a robot collaborator. This limitation is more evident when robots are faced with real-life contexts and activities occurring over long periods. In this article, we argue that human-robot collaboration is more than just being able to work side by side on complementary tasks: collaboration is a complex relational process that entails mutual understanding and reciprocal adaptation. Drawing on this assumption, we propose to shift the focus from ''human-robot interaction'' to ''human-robot shared experience.'' We hold that for enabling the emergence of such shared experiential space between humans and robots, constructs such as coadaptation, intersubjectivity, individual differences, and identity should become the central focus of modeling. Finally, we suggest that this shift in perspective would imply changing current mainstream design approaches, which are mainly focused on functional aspects of the humanrobot interaction, to the development of architectural frameworks that integrate the enabling dimensions of social cognition.

Consumer–machine relationships in the age of artificial intelligence: Systematic literature review and research directions

“…">Researchers should attempt to develop novel theories that would be more applicable to the new social AI phenomenon as it develops. For example, while exchange‐based social psychology approaches do not precisely explain or predict human–AI relationships at present, conversational agents of the future are expected to better retain and accumulate background information, building common history with their human counterparts, and acquiring intersubjectivity (ability to share and resonate experiences; Gaggioli et al, 2021). Thus, exchange‐based relationship theories could be revisited at a later stage of social AI development. …”

A Hermeneutical Approach to Provide Robots with Socially Adaptive Perception

“…Its verbal and non-verbal behaviour may, in turn, affect the user's behaviour. Therefore, the two partners, the human user and the robotic agent, are not statical entities and influence each other during the interaction in a reciprocal and continual exchange and adaptation [32].…”

Gradual Rhythm Change of a Drumming Robot Enhances the Pseudosense of Leading in Human–Robot Interactions

“…[2] The participant is instructed to hit his/her drum (similar to the robot's) after the robot first hits the drum and then alternatively hitting the drum for 40 seconds. [3] The experimenter stops the session, and the participant is asked to answer five questions about her/his impressions concerning the above mentioned interaction. The questions are related to the subjective feelings of being followed by the robot, being a follower, pleasure for the interaction, favor for the robot, and closeness to the robot.…”

“…The recent development of robotics and artificial intelligence technologies predicts the arrival of a society in which social robots will support human lives as partners [1][2][3]. In order to realize such a society, it is not enough for robots to be highly functional; they must also be friendly to the human mind.…”