@inproceedings {pub6432,
	title = {Human{\textendash}AI Cooperation Reconsidered: Integrating Reciprocity and Psychological Needs},
	author = {Christiane Attig AND Patricia Wollstadt AND Jouh Yeong Chew AND Alan  Sarkisian AND Christiane Wiebel},
	year = {2026},
	abstract = {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{\textendash}machine interaction becomes more relevant than ever. In this rapidly evolving sociotechnological landscape, what counts as {\textquotedblleft}successful{\textquotedblright} human{\textendash}AI cooperation from the human perspective remains an open question. We here argue that designing for human{\textendash}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{\textendash}AI interaction and explore how integrating them may add an explanatory value that can inform the design of psychologically aligned successful human{\textendash}AI cooperation over a broad range of application contexts. 

(Adapted version of the full paper we submitted to HAI 2025, which was rejected)},
	publisher = {Springer, LNCS, LNAI, LNBI},
	url = {https://link.springer.com/chapter/10.1007/978-3-032-30846-7_15},
	booktitle = { Artificial Intelligence in HCI. HCII 2026},
	editor = {H. Degen, S. Ntoa},
	volume = {16743},
	pages = {235-261},
	series = {Lecture Notes in Computer Science},
	institution = {Springer}
}