Chapter
The Role of Models in Understanding Complex Systems
33:02 - 41:10 (08:07)
In this episode, the speaker discusses the role of models in understanding complex systems and how they can be used to infer causality without physically changing the system.
Clips
The speaker discusses how constructing a model of the human body can help infer whether higher blood pressure leads to increased mortality rates, without physically manipulating the body.
33:02 - 36:00 (02:58)
Summary
The speaker discusses how constructing a model of the human body can help infer whether higher blood pressure leads to increased mortality rates, without physically manipulating the body.
ChapterThe Role of Models in Understanding Complex Systems
EpisodeJudea Pearl: Causal Reasoning, Counterfactuals, Bayesian Networks, and the Path to AGI
PodcastLex Fridman Podcast
The complexity of the world makes it difficult to identify cause and effect through observational data alone.
36:00 - 38:33 (02:32)
Summary
The complexity of the world makes it difficult to identify cause and effect through observational data alone. While machine learning can help reason by association, it cannot always account for intervention and the limitations of causal inference.
ChapterThe Role of Models in Understanding Complex Systems
EpisodeJudea Pearl: Causal Reasoning, Counterfactuals, Bayesian Networks, and the Path to AGI
PodcastLex Fridman Podcast
Humans are capable of solving complex physics equations by using counterfactual thinking to process the problem and then solving the equation algebraically.
38:33 - 41:10 (02:36)
Summary
Humans are capable of solving complex physics equations by using counterfactual thinking to process the problem and then solving the equation algebraically.