Newsroom
Latest news from the alignAI doctoral network:
AI-nxiety and AI-gency: Young Adults Navigating Generative AI
As part of the TUM Institute for Ethics in Artificial Intelligence (IEAI) Speaker Series, a December 2025 session focused on young adults and generative AI. The talk, titled “AI-nxiety & AI-gency: Young Adults Navigating Generative AI” was delivered by Dr. Jaimee Stuart, Senior Researcher and Team Lead at United Nations University Macau.
Q&A with PI Martijn Willemsen
In this video interview, we speak with Professor Martijn Willemsen, a researcher at Eindhoven University of Technology known for his studies on human decision processes and recommender systems. He talks about the doctoral candidates he works with and the projects they pursue, his reasons for joining alignAI, the perspective his institute adds to the project, and the cooperation he hopes to see among partners.
Beyond Accuracy: Why “Being Right” Isn’t Enough for Human-Centred AI
Imagine the following two scenarios. A teacher asks an AI to review a student’s essay. Its feedback is accurate, the grammar is fixed and the facts are straight, yet the student still feels stuck. The student has no clue what to try next. A software team asks an AI to flag bugs. The model points to real issues, but the way it explains them leaves new engineers more confused than confident. In both cases, the tool passes the test and fails a person.
Accuracy matters, but it’s not the whole story. If we chase only the right answer, we ship systems that look strong in demos and lose people in real use.
Beyond the Hype: What Actually Makes AI Design Different
Just a few years ago, conversation flow design was at the heart of chatbot research (Cho et al., 2025). Designers developed detailed guidelines to structure dialogues, crafted messaging frameworks for seamless interactions, and carefully designed output messages to align with chatbot personas. Then as transformer-based large language models (LLMs) arrived, the rigid and predefined conversation structures that worked for rule-based systems couldn’t accommodate LLMs’ dynamic, context-aware response. Research priorities shifted from designing fixed dialogue trees to exploring prompt engineering and interaction patterns (Cho et al., 2025). The expertise built over years around conversation flow design was fundamental but it needed rapid reframing; designers had to rethink how to guide conversations without prescribing every turn, how to maintain coherence without rigid structures, and how to evaluate interactions that varied with each user (Subramonyam et al., 2024). This narrative about change isn’t just applicable to chatbots. It’s applicable to Generative AI’s (GenAI) unique temporal challenge and it raises a critical question for anyone designing with or for AI – are our design methods keeping up, or do we need new ones?
Q&A with PI Daniel Gatica-Perez
In this video interview, we speak with Professor Daniel Gatica-Perez, Head of Social Computing Group at Idiap and Professor at École Polytechnique Fédérale de Lausanne. He emphasises the importance of a human-centred approach and shares how he sees the alignAI project can help society.
The Moral Panic Around AI Mental Health
Trigger Warning/Disclaimer: This blog post mentions suicide.
Governments, startup founders, academics, mental health professionals and others wrestle over who gets to define the future of AI mental health care.
Amidst a lack of regulatory oversight regarding AI-based mental health chatbots, some states in the US have taken steps to ban these systems in order to protect the public. Full bans are in place in Illinois and Nevada, and although Utah has not banned it outright, it still imposes strong restrictions and requirements around transparency, advertising, data use and human professional involvement. Bans as a political strategy and policy risk unintended consequences on a population-wide scale (Oliver et al., 2019).