By Tom Everitt, Ryan Carey, Lewis Hammond, James Fox, Eric Langlois, and Shane LeggAbout 2 years ago, we released the first few papers on understanding agent incentives using causal influence diagrams. This blog post will summarize progress made since then. What are causal influence diagrams? A key problem in AI alignment is understanding agent incentives. Concerns have been raised that agents may be incentivized to avoid correction, manipulate users, or inappropriately influence their learning. This is particularly worrying as training schemes often shape incentives in subtle and surprising ways. For these reasons, we’re developing a formal theory of incentives based on causal influence diagrams (CIDs).Source:https://deepmindsafetyresearch.medium.com/progress-on-causal-influence-diagrams-a7a32180b0d1Narrated for AI Safety Fundamentals by TYPE III AUDIO.---A podcast by BlueDot Impact.Learn more on the AI Safety Fundamentals website.

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