Daniel Braun

@d4br4.bsky.social

Professor of Computer Science at the University of Marburg. Working on Natural Language Processing (NLP), AI for Social Good, and Legal Tech. | Foto: Martin Schäfer https://www.responsible-nlp.net

I’m in Budapest for #emnlp2026. If you are interested in the open PhD scholarship in our „Human-in-Control“ project (deadline 2nd of November), come talk to me! And of course come to our poster about Anti-LGBTQ Biases in Multilingual Language Models in the poster session Monday afternoon.

A picture of the parliament building in Budapest

Our paper on anti-LGBTQ bias in German & multilingual LMs has been accepted to EMNLP 2026! The work started as the Master’s thesis of one of our students. The findings highlight why multilingual bias evaluation must go beyond translating English benchmarks and involve the communities represented.

Evaluating and Mitigating Anti-LGBTQ Biases in German and Multilingual Language Models

While gender and racial biases in language models have been widely studied, anti-LGBTQ biases remain underexplored, particularly beyond English. Existing benchmarks often do not capture cultural and l...

arxiv.org

In light of OpenAI’s “runaway” AI, a local newspaper asked me whether we’ve lost control of AI. We’ll see more AI-driven hacks. It's important to take a close look: A model optimized to find vulnerabilities, stripped of safeguards, and without oversight, isn’t rogue AI. It’s human negligence.

KIs brechen aus Testbereichen aus – Marburger Experte: „Das wird öfter passieren“

Im Juli 2026 brachen mehrfach KIs aus geschützten Testbereichen aus und streiften auf eigene Faust durch das Internet. Ob wir die Kontrolle über die KI verlieren, erklärt der Informatiker und KI-Forsc...

op-marburg.de

This week, I’m in Heidelberg attending the Heidelberg Laureat Forum #hlf25. It’s always a great pleasure to be among some of the smartest minds in Math and Computer Science and see what they are working on.

Bild

Are LLMs “Yes Sayers”? Humans often show acquiescence bias, i.e. prefer positive answers in questionnaires and surveys regardless of their actual belief. We investigated if LLMs show a similar bias and found: they’re disproportionately likely to answer “No,” even when the meaning flips.

Acquiescence Bias in Large Language Models

Acquiescence bias, i.e. the tendency of humans to agree with statements in surveys, independent of their actual beliefs, is well researched and documented. Since Large Language Models (LLMs) have…

arxiv.org

Ive written a "Last Word" opinion piece for CL about evaluating real-world impact. It * looks at how impact can be evaluated * shows via a structured survey that perhaps 0.1% of ACL Anth papers measure real-world impact * discusses why this is the case arxiv.org/abs/2507.05973

We Should Evaluate Real-World Impact

The ACL community has very little interest in evaluating the real-world impact of NLP systems. A structured survey of the ACL Anthology shows that perhaps 0.1% of its papers contain such evaluations; ...

arxiv.org

Now finally assigned an issue number: my article »Why “Artificial Intelligence” Should Not Be Regulated«, in which I argue not against technology regulation, but against arbitrary definitions of 'AI' by lawmakers and in favor of risk-based, technology-independent regulation.

Why “Artificial Intelligence” Should Not Be Regulated | Digital Government: Research and Practice

Lawmakers all over the world have started to draft new regulations for Artificial Intelligence (AI). While the European Union is currently leading the way with its AI Act, many other legislators will ...

dl.acm.org