3 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
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…