About us

We are an interdisciplinary group data of science researchers at Bauhaus University advised by Prof. Maurice Jakesch.

We use experiments, machine learning prototypes, and data science methods to study the impact of digital technologies and AI on society. For example, in the experiment above we test how an opinionated AI writing assistant influences users’ views. By diagnosing emerging problems and working towards early solutions, we contribute to a safer and more democratic information ecosystem.

Publications

Highlights
    • Maurice Jakesch, Jeff Hancock, and Mor Naaman |
  • PNAS 120.11| 2023

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...

    • Maurice Jakesch, Advait Bhat, Daniel Buschek, Lior Zalmanson and Mor Naaman |
  • ACM CHI| 2023

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...

Recent work
    • Sterling Williams-Ceci, Maurice Jakesch, Advait Bhat, Kowe Kadoma, Lior Zalmanson, Mor Naaman |
  • PsyArXiv| 2024
    • Zana Buçinca, C. M. Pham, M. Jakesch, M. T. Ribeiro, Alexandra Olteanu, and Saleema Amershi |
  • arXiv preprint| 2024
    • Jospeh Schlessing, Kiran Garimella, Maurice Jakesch, and Dean Eckles |
  • AAAI ICWSM| 2023
    • Sarah Kreps and Maurice Jakesch |
  • Government Information Quarterly 40.3: 101829| 2023

Expertise

Risks of emerging AI systems

Our communication is increasingly intermixed with language generated by AI. While the development and deployment of large language models is progressing rapidly, their social consequences are hardly known. We work towards an understanding of the risks of large language models by empirically exploring their effects on social phenomena such as trust and opinions.

Misinformation and platform polarization

Digital platforms are 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 understand how digital platforms contribute to ideological divides. We aim to inform measures and policies for a healthier digital discourse.

Technologies for better organisations

Digital technologies can help organizations navigate increasingly complex environments, but we are far from using their full potential. We explore the use of e.g. new AI language systems in organizations and political institutions to evaluate how technologies can enhance decision-making, improve communication, and foster collaboration at scale.

Methods for interdisciplinary data analysis

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

Team

Contact us
If you would like to get in touch with us regarding our work, collaboration opportunities, or other inquiries, e-mail us, follow us on Twitter, or contact our secretary Rubi Richter at +49 3643 - 58 3710. We are located at the Bauhaus University campus, Bauhausstraße 11, 99423 Weimar, Germany.