Bauhaus CSS Lab

AI writing assistants powered by large language models are increasingly used to make autocomplete suggestions to people as they write text. Can these AI writing assistants affect people’s attitudes in this process? In two large-scale preregistered experiments (N = 2582), we exposed participants writing about important societal issues to an AI writing assistant that provided biased autocomplete suggestions. When using the AI assistant, the attitudes participants expressed in a posttask...

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...

Identifying false claims is difficult, and our cognitive biases make it even harder. A promising 2024 study suggests that conversational AI can help people identify false claim and overcome their biases. We expand on these insights with ClaimGuard — an app that supports citizens in fact-checking through collaborative AI dialogues, fosters media literacy, and creates a collaborative knowledge base for fact-checking efforts.

How can we collect and analyze digital data about human behavior? This course covers the pipeline of social data science research: from collecting survey data and wrangling digital trace data to running statistical analyses on numeric and relational datasets. Students learn hands-on methods while critically engaging with the limitations and ethical aspects of their analysis.

What does it mean to build AI systems that are fair, transparent, and accountable? This seminar-style project engages students with the principles and frameworks guiding responsible AI development. Combining an independent research projects with weekly readings and discussions, students examine issues such as algorithmic bias, explainability, and societal impact.

We supervise bachelor’s and master’s theses on topics at the intersection of computational methods and social science. Our linked thesis guide offers an overview of how we approach research, how we advise students, and the kinds of topics that interest us along with the steps to take if you’d like to write your thesis with us.