@inproceedings {pub5573,
	title = {What is successfull cooperation in human-AI partnerships?},
	author = {Christiane Wiebel AND Patricia Wollstadt},
	year = {2024},
	month = {September},
	abstract = {Cooperation is omnipresent in nature, from simple organisms that live in symbiosis to the creation of complex human societies. Recent research in AI-driven technology has claimed that AI systems need to learn to engage in cooperative interactions with humans, as well, to be successfully adopted in the future (Dafoe, 2020, 2021). Accordingly, the development of AI-systems must turn to developing cooperation {\textendash} or {\textquotedblleft}teaming-intelligence{\textquotedblright} {\textendash} rather than {\textquotedblleft}just{\textquotedblright} super-human performance in zero-sum games. Similarly, in the field of human-machine interaction (HMI) designing for human-machine cooperation (Klein, 2005; Krueger, 2017; Butepage, 2017; Gervasi, 2020) has been suggested as a means for overcoming automation failures and for increasing user satisfaction.
In this talk, we will review recent developments in AI teaming intelligence research and highlight the need for novel approaches to formally describe and quantify human-AI cooperation (Jarrasse, 2013; Bengler, 2012; Sciutti, 2012). We will argue that progress in the field needs to consider how to evaluate successful cooperation in HMI from a human perspective, apart from exclusively optimizing performance metrics, e.g. game scores.  Along these lines, we will briefly introduce a novel approach to quantify cooperative interactions in HMI using measures from information theory, which goes beyond simple measures of task success.},
	publisher = {DGPS},
	booktitle = {Deutsche Gesellschaft f{\"u}r Psychologie Kongress (DGPS 2024)},
	city = {Vienna}
}