Causality, LLMs & Abstractions || Matej Zečević || Causal Bandits Ep. 000 (2023)
Causal Bandits Podcast
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Navigating Causality: Insights from Human Reasoning to AI
This chapter explores the intricacies of human causal reasoning, questioning the intuitive understanding of causality and its complexities in various contexts, such as policy-making. It discusses the distinctions between black box and white box models in machine learning, emphasizing the ongoing challenge of explainability and transparency in AI systems. Furthermore, it highlights the significant role of causal algorithms in biomedical research and the importance of interdisciplinary collaboration in advancing the field.
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