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The Impact of Perceived System Characteristics on Acceptance and Usage of AI Systems 

WorkgroupSocial Processes Lab 
FundingSondertatbestand Data Science
Project description

Humans often tend to treat technical systems as social actors and ascribe them human-like characteristics (e.g., when telling a computer to work faster). With the ongoing introduction of Artificial Intelligence (AI), this tendency is likely to increase – as technical systems become more and more capable (e.g., of solving complex problems or adapting to individual users) and are often even explicitly designed to appear human-like.

Up to now, a multitude of research has focused on how the objective technical capabilities of different technologies impact users’ interaction behavior. However, especially users’ subjective perceptions of system characteristics – which can substantially differ from the objective features it provides – are important to understand users’ interaction with AI systems. To address this gap, this project aims to investigate how user’s subjective perceptions of human-like characteristics in AI systems influence the interaction with as well as the acceptance of such technical systems. Doing so, we seek to contribute to a better understanding of how users perceive such systems, as well as to grasp how this influences their subsequent responses.

The project is part of the „Human-Agent Interaction“ Network (MAI Network).


Prof. Dr. Kai Sassenberg, Leibniz-Institut für Psychologie (ZPID)


Gieselmann, M., & Sassenberg, K. (2023). The more competent, the better? The effects of perceived competencies on disclosure towards conversational Artificial Intelligence. Social Science Computer Review, 41(6), 2342-2363. [Data] Open Access

Tschopp, M., Gieselmann, M., & Sassenberg, K. (2023). Servant by default? How humans perceive their relationship with conversational AI. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 17(3), Article 9. Open Access


Dr. Miriam Gieselmann Dr. Miriam Gieselmann
Tel.: +49 7071 979-204

Project team

Marisa Tschopp