About

We are entering an era of AI-Mediated Communication (AI-MC) where interpersonal communication is not only mediated by technology, but is optimized, augmented, or generated by artificial intelligence. Our study takes a first look at the potential impact of AI-MC on online self-presentation. In three experiments we test whether people find Airbnb hosts less trustworthy if they believe their profiles have been written by AI. We observe a new phenomenon that...

If large language models like GPT-3 preferably produce a particular point of view, they may influence people’s opinions on an unknown scale. This study investigates whether a language-model-powered writing assistant that generates some opinions more often than others impacts what users write - and what they think. In an online experiment, we asked participants (N=1,506) to write a post discussing whether social media is good for society. Treatment group participants...

Digital platforms are increasingly central to public discourse, yet may also facilitate the spread of misinformation and contribute to polarization. Using empirical methods, we analyze platform dynamics and user behavior to investigates how digital platforms may support ideological divides, informing measures and policies towards a healthier digital discourse.

Data-driven methods are transforming social analysis, enabling insights at unprecedented scales. We explore and refine new approaches for large-scale experimentation, causal inference, and mixed-methods analyses. We also adapt and extend concepts and tools from neighbouring disciplines, such as psychology, economics, or political science into digital research.

Our communication is increasingly intermixed with language generated by AI. While the development and deployment of large language models is progressing expeditiously, the social consequences are hardly known. We work towards an understanding of the risks of large language models by empirically exploring how the effects of people’s interactions with emerging AI systems.