The complexities of identifying causality in the real world: A new study presented at ICML

Summary

MBZUAI researchers presented a study at ICML 2024 examining how data aggregation distorts causal discovery. The study argues that current methods are misled because real-world interactions happen at a micro level while observations are aggregated. Using the example of ice cream sales and temperature, they highlight how aggregation introduces "instantaneous causality" where time-lags exist. Why it matters: The research identifies a fundamental limitation in current causal discovery methods, potentially impacting disciplines relying on accurate causal inference from observational data.