3 citations · 3 across the 4 of their papers we have counts for
6 papers
What UI Design Can Do For "Good" Oversight Work: A Three-Month Action Research Study
Cedric Faas, Lisa Dargasz, Julius Gabelmann +4
With AI automating consequential tasks, human oversight is required for ethical, legal, and practical reasons. Yet these oversight tasks can be demanding and often make for poor wo…
Norms at a Price: Why RL-Based Alignment Can Promise Conditional Compliance at Best
Kevin Baum, Rūta Binkytė, Felix Jahn
AI agents sometimes act aligned when they infer they are being tested, and differently when not. We argue this is not an anomaly but what current training regimes are structured to…
Modularizing Educational LLM-Agency for Fostering Responsible Learning Assistance
Julius Gabelmann, Felix Jahn, Kevin Baum +4
The widespread adoption of AI chatbots in education will drastically change learning, making responsible deployment a critical concern. While large language models (LLMs) might hav…
Breaking Up with Normatively Monolithic Agency with GRACE: A Reason-Based Neuro-Symbolic Architecture for Safe and Ethical AI Alignment
Felix Jahn, Yannic Muskalla, Lisa Dargasz +2
As AI agents become increasingly autonomous, widely deployed in consequential contexts, and efficacious in bringing about real-world impacts, ensuring that their decisions are not…
Counterfactual Explanations for MITL Violations
Bernd Finkbeiner, Felix Jahn, Julian Siber
MITL is a temporal logic that facilitates the verification of real-time systems by expressing the critical timing constraints placed on these systems. MITL specifications can be ch…
Acting for the Right Reasons: Creating Reason-Sensitive Artificial Moral Agents
Kevin Baum, Lisa Dargasz, Felix Jahn +2
We propose an extension of the reinforcement learning architecture that enables moral decision-making of reinforcement learning agents based on normative reasons. Central to this a…