Making Sense with Sam Harris #453 — AI and the New Face of Antisemitism
87 snips
Jan 16, 2026 
Judea Pearl, a computer scientist and philosopher known for his work on causality, dives into the complexities of AI and its relationship with sociopolitical issues. He argues that LLMs will not lead to AGI, highlighting the limits of deriving causation from mere correlation. Pearl reflects on the rise of anti-Zionism and its intersection with antisemitism, sharing his experiences engaging in public dialogue after the tragic loss of his son. The conversation also touches on the challenges of aligning AGI and the barriers to meaningful East-West dialogue.
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LLMs Summarize, Not Discover Causality
- Judea Pearl argues current LLMs summarize human-created world models rather than discovering causal structure from raw data.
- He claims mathematical limits prevent scaling alone from producing true causal reasoning or AGI.
Scaling Alone Won't Deliver AGI
- Scaling data and compute is insufficient to cross theoretical barriers toward AGI.
- Pearl states a fundamental breakthrough beyond deep learning is required.
The Ladder Of Causation Limits Learning
- Pearl emphasizes the ladder of causation: correlation cannot yield causation without extra inputs.
- He explains interventions alone cannot produce interpretations or counterfactual understanding.
