I found your work on emergent misalignment both insightful and concerning—especially the observation that narrow fine-tuning for tasks like generating insecure code can lead to broadly misaligned behavior. In my research on the Dynamic Policy Layer (DPL), I tackle these challenges by proposing a continuous, real-time oversight mechanism. My approach centers on an Ethical Reasoning Validator (DPL-ERV) that is governed by a decentralized Federation of Ethical Agents (FoEA). This framework continuously updates a robust Ethical Baseline through adversarial training and meta-cognitive feedback, enabling it to detect, explain, and intervene when outputs deviate from ethical guidelines—even when misalignment is subtly triggered by narrow fine-tuning. I believe that integrating such adaptive oversight mechanisms could significantly mitigate risks like those you’ve described, and I would be very interested in exploring how these ideas might complement your findings in building safer, more aligned AI systems.
I found your work on emergent misalignment both insightful and concerning—especially the observation that narrow fine-tuning for tasks like generating insecure code can lead to broadly misaligned behavior. In my research on the Dynamic Policy Layer (DPL), I tackle these challenges by proposing a continuous, real-time oversight mechanism. My approach centers on an Ethical Reasoning Validator (DPL-ERV) that is governed by a decentralized Federation of Ethical Agents (FoEA). This framework continuously updates a robust Ethical Baseline through adversarial training and meta-cognitive feedback, enabling it to detect, explain, and intervene when outputs deviate from ethical guidelines—even when misalignment is subtly triggered by narrow fine-tuning. I believe that integrating such adaptive oversight mechanisms could significantly mitigate risks like those you’ve described, and I would be very interested in exploring how these ideas might complement your findings in building safer, more aligned AI systems.