Zhijing Jin
Research scientist focused on causality, natural language, and ethics, affiliated with Max Planck Institute for Intelligent Systems and incoming Assistant Professor at the University of Toronto; author of work on causal reasoning in LLMs and multi-agent simulations.
Best podcasts with Zhijing Jin
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12 snips
Oct 30, 2025 • 1h 3min
The Causal Gap: Truly Responsible AI Needs to Understand the Consequences | Zhijing Jin S2E7
In this discussion, Zhijing Jin, a leading research scientist at the Max Planck Institute and incoming Assistant Professor at the University of Toronto, dives into the critical intersection of causality and AI ethics. She explores why LLMs often falter in their decision-making and the importance of causal reasoning in moral frameworks. Highlighting her work on multi-agent simulations, she reveals troubling patterns of self-destructive behavior in AI models. Zhijing also emphasizes the need for interdisciplinary research and greater awareness of causal understanding in AI to foster responsible development.
4 snips
Nov 14, 2024 • 23min
38.0 - Zhijing Jin on LLMs, Causality, and Multi-Agent Systems
Zhijing Jin, an Assistant Professor at the University of Toronto, specializes in the intersection of natural language processing and causal inference. In this engaging discussion, she investigates whether language models truly understand causality or just recognize correlations. Zhijing explores the limitations of these models in reasoning, their application in multi-agent systems, and the complexities of digital societies. She poses intriguing questions about AI governance and cooperation, emphasizing the delicate balance required for sustainable agent interactions.
