Safety6h ago
Safety
Exploring Causal Inference Through Informal Diaries
A researcher is documenting an informal journey into causal discovery using a diabetes dataset from an ML repository. The author tests model comparison and variable connectivity to avoid common correlation errors. This iterative approach highlights the difficulty of extracting reliable causal links from static data, a critical hurdle for AI safety and alignment.