This is a talk I gave at the recent AI Safety Europe Retreat (AISER) on my research on obtaining insights from the cognitive science of empathy and applying them to RL agents and LLMs.
Talk description: I begin by presenting a short review on the cognitive science of empathy as a Perception-Action Mechanism (PAM) which relies on self-other overlap at the neuronal level. I continue by presenting the theory of change of this research direction by arguing that inducing self-other overlap as empathy is model agnostic and that it has the potential to avert AI x-risk and be sub-agent stable in the limit. Then I present experimental evidence of the emergence of PAM in RL agents and present a way of inducing PAM in RL agents. I end the talk by discussing how this paradigm could be extended to LLMs.
Acknowledgements: I am thankful for Dr. Bogdan Ionut-Cirstea for inspiring me to look into this neglected research direction, the Long-Term Future Fund for funding the initial deep dive into the literature, and for Center for AI Safety for funding half of this research as part of their Student Researcher programme. Last but not least, I want to thank Dr. Matthias Rolf for supervising me and providing good structure and guidance. The review on the cognitive science of empathy is adapted from a talk given by Christian Keysers from the Netherlands Institute for Neuroscience.
Towards empathy in RL agents and beyond: Insights from cognitive science for AI Alignment
Link post
This is a talk I gave at the recent AI Safety Europe Retreat (AISER) on my research on obtaining insights from the cognitive science of empathy and applying them to RL agents and LLMs.
Talk link: https://clipchamp.com/watch/6c0kTETRqBc
Slides link: https://bit.ly/3ZFmjN8
Talk description: I begin by presenting a short review on the cognitive science of empathy as a Perception-Action Mechanism (PAM) which relies on self-other overlap at the neuronal level. I continue by presenting the theory of change of this research direction by arguing that inducing self-other overlap as empathy is model agnostic and that it has the potential to avert AI x-risk and be sub-agent stable in the limit. Then I present experimental evidence of the emergence of PAM in RL agents and present a way of inducing PAM in RL agents. I end the talk by discussing how this paradigm could be extended to LLMs.
Acknowledgements: I am thankful for Dr. Bogdan Ionut-Cirstea for inspiring me to look into this neglected research direction, the Long-Term Future Fund for funding the initial deep dive into the literature, and for Center for AI Safety for funding half of this research as part of their Student Researcher programme. Last but not least, I want to thank Dr. Matthias Rolf for supervising me and providing good structure and guidance. The review on the cognitive science of empathy is adapted from a talk given by Christian Keysers from the Netherlands Institute for Neuroscience.