613: Causal Machine Learning
Super Data Science: ML & AI Podcast with Jon Krohn
00:00
Importance of Domain Knowledge in Causal Machine Learning
The chapter delves into the pitfalls of incorrect causal assumptions and the necessity of human intervention in setting up causal relationships between variables in machine learning. It also explores challenges in achieving artificial general intelligence without causal reasoning and discusses the potential for automation of causal assumptions. The conversation emphasizes the importance of integrating domain knowledge into algorithms and includes examples from computational social science research on topics like online mental health and soil management for climate change mitigation.
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