Christiane Attig, Alan Sarkisian, Jouh Yeong Chew, Christiane Wiebel, "Beyond Reciprocity: Psychological Needs as a Foundation for Human-AI Cooperation", HAI '25: Proceedings of the 13th International Conference on Human-Agent Interaction, pp. 445-448, 2026.

Artificial Intelligence (AI) systems are becoming increasingly pervasive in our daily lives. As these systems are applied across a wide range of domains, the need to thoughtfully design successful cooperative human-machine interaction becomes more relevant than ever. In this rapidly evolving sociotechnological landscape, what counts as “successful” human-AI cooperation from the human perspective remains an open question. We here argue that designing for human-AI cooperation must integrate, beyond short-term functionality, an experiential layer of the perceived cooperation, which supports psychological alignment over time and human intrinsic motivation to enter a cooperation. To support this perspective, we draw from two sets of theories that have a long history in explaining human psychological need satisfaction and well-being (self-determination theory) as well as the formation of sustainable cooperation among humans (evolutionary cooperation theory). We review recent empirical work that has applied these theoretical models to human-AI interaction and explore how integrating them may add an explanatory value that can inform the design of psychologically aligned successful human-AI cooperation over a broad range of application contexts.