How do people assess the person they are explaining something to? Psychologists Viviane Gladow and Prof. Dr. Heike Buhl from Project A01 “Adaptive Explanation” of TRR 318 explored this question in a new study. They interviewed 26 primary school teachers, university lecturers and physicians—three professional groups for whom explaining is an important part of everyday work.

In a new video, Nils Klowait explains how AI works in general, why it can sometimes lead to problematic decisions, and why it is important to understand how AI operates in our society.

More doctoral candidates successfully completed their dissertations in 2026. In the third episode of the dissertation presentations, researchers from computer science and linguistics present their research findings.

This highly endowed honor ranks among the world’s top scientific awards. With this year’s Balzan Prize, Prof. Dr. Elena Esposito is being recognized for her scientific work on the sociology of AI and algorithms. At TRR 318, she leads Project B01: A dialog-based approach to explaining machine learning models. (Article in German)

Although people who explain technical objects take their listeners’ interests into account, they still primarily focus on how these objects work. This is shown by a recent study from the A04 project of Transregio 318 “Constructing Explainability.” The findings were published under the title “Navigating the Dual Nature: Do Explainers Adapt to Explainee Interests When Explaining Technical Artifacts?”

When do people follow recommendations from AI – and when do they ignore or question them? Researchers from Project A03 TRR 318 investigated this question. They sought to determine the influence of users’ emotional states on how they respond to AI recommendations. Their findings revealed that people in a moderate state of emotional arousal, in particular, appear to scrutinise AI recommendations more critically.

Bielefeld University Press has now published the proceedings of the third TRR 318 conference, “Contextualizing Explanations.” The proceedings, edited by Philipp Cimiano, Benjamin Paaßen, and Anna-Lisa Vollmer, explore how explanations can be contextualized to increase their relevance and empower users.

An international team of researchers, including members of TRR 318, argues that explainable AI must take social aspects into account. In their new book, „Social Explainable AI: Communications of NII Shonan Meetings“, they apply social concepts to explainable artificial intelligence and develop proposals for its practical implementation.

With a kick-off event on March 3 in the CITEC building at Bielefeld University, the Collaborative Research Center/Transregio TRR 318 “Constructing Explainability” officially began its second funding phase. The next phase of joint research was heralded with lectures and various exchange formats for members and associates.

At the end of the first funding phase of TRR 318, more doctoral candidates have successfully completed their dissertations. In the second episode of the doctoral presentations, researchers from computer science and psychology present their research results.

In the eighth and final episode of the TRR podcast, Prof. Dr.-Ing. Britta Wrede talks with Prof. Dr. Friederike Kern and Prof. Dr. Benjamin Paaßen about the role of context in explainable AI and how AI systems can be designed to be more context-sensitive.

The year 2025 was marked by significant developments for TRR 318: new research findings, the third TRR conference, and a variety of formats for exchange with the public. In addition, the second funding phase was approved, starting in 2026. Here is a brief review of the year 2025.

How can different social groups be involved in discussions about artificial intelligence technologies? “First of all, by learning to talk about it and ask questions,” says Dr. Nils Klowait from the Ö project of TRR 318. The Co-Construction Workshops (CCWS) are one platform for this. They were developed in the first funding phase (2021-2025) of TRR 318 and tested with a variety of groups.