Such direction-setting exercises and perspective-gathering from across the field, as demonstrated in this article, seem incredibly valuable for understanding the AI safety landscape. Given how rapidly the AI landscape evolves, it might be worth considering how such field-wide perspective-gathering could remain current and representative over time. Perhaps there’s value in exploring mechanisms for continuous feedback loops across the AI safety landscape to help track shifting priorities and emerging concerns. I’m curious whether an actor or institution focused on maintaining these feedback loops could help bridge perspectives across technical research, governance, and policy domains, keeping a finger on the pulse of this complex field?
Such direction-setting exercises and perspective-gathering from across the field, as demonstrated in this article, seem incredibly valuable for understanding the AI safety landscape. Given how rapidly the AI landscape evolves, it might be worth considering how such field-wide perspective-gathering could remain current and representative over time. Perhaps there’s value in exploring mechanisms for continuous feedback loops across the AI safety landscape to help track shifting priorities and emerging concerns. I’m curious whether an actor or institution focused on maintaining these feedback loops could help bridge perspectives across technical research, governance, and policy domains, keeping a finger on the pulse of this complex field?