38.0 - Zhijing Jin on LLMs, Causality, and Multi-Agent Systems

Do language models understand the causal structure of the world, or do they merely note correlations? And what happens when you build a big AI society out of them? In this brief episode, recorded at the Bay Area Alignment Workshop, I chat with Zhijing Jin about her research on these questions.
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Ko-fi: ko-fi.com/axrpodcast
The transcript: axrp.net/episode/2024/11/14/episode-38_0-zhiji…
FAR.AI: far.ai
FAR.AI on X (aka Twitter): x.com/farairesearch
FAR.AI on YouTube: youtube.com/@FARAIResearch
The Alignment Workshop: alignment-workshop.com

Topics we discuss, and timestamps:
00:35 - How the Alignment Workshop is
00:47 - How Zhijing got interested in causality and natural language processing
03:14 - Causality and alignment
06:21 - Causality without randomness
10:07 - Causal abstraction
11:42 - Why LLM causal reasoning?
13:20 - Understanding LLM causal reasoning
16:33 - Multi-agent systems

Links:
Zhijing's website: zhijing-jin.com/fantasy
Zhijing on X (aka Twitter): x.com/zhijingjin
Can Large Language Models Infer Causation from Correlation?: arxiv.org/abs/2306.05836
Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents: arxiv.org/abs/2404.16698

Episode art by Hamish Doodles: hamishdoodles.com