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Cross-sectional activities

Human-Agent Interaction Network



The Human-Agent Interaction Network (MAI Network) explores human interaction with artificial intelligence processing natural language. Such agents are already routinely used by many people. Language-based agents such as Siri and Cortana are available in almost every digital device and learning programs provide increasingly complex feedback in natural language. However, scientific knowledge about the interaction between users and voice-based agents is very limited so far. The IWM is well prepared to address this gap due to the IWM’s expertise in research on individual and social processing of knowledge during the use of digital media. Thematically, the acceptance of language agents and the effects of using these agents on human performance are investigated in the MAI Network. The topics of the projects include acceptance and comprehension of AI-generated texts and language, writing support by AI, and communication between humans and AI language agents.

The MAI Network consists of eight interdisciplinary projects carried out in collaboration with researchers from the universities of Tübingen and Stuttgart. All IWM Labs and Junior Research Groups are involved in the projects. Each project has a cooperation partner with expertise in data science and artificial intelligence at one of the universities. The MAI Network is funded from a small strategic special budget on the topic of data science.


Projects









Leibniz-WissenschaftsCampus Tübingen

The MAI-Network follows the tradition of the Leibniz-WissenschaftsCampus Tübingen (WCT). The WCT provided an institutionalized form for the IWM's cross-sectional activities. It was established in 2010 targeting the topic »Informational Environments«. From 2017-2020 it was continued with a focus on »Cognitive Interfaces«. In this research network, departments of the IWM cooperated with partners of the University of Tübingen. Since 2018 the University of Stuttgart was associated partner. The WCT focused on how thinking, acting and working in the context of digital media can be improved by designing human-computer interfaces.