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      <title>The Causal Inference Comeback: Why Correlation-Era ML Hit a Wall</title>
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      <description>Causal inference - the methodological tradition that asks &amp;#39;why&amp;#39; rather than &amp;#39;what&amp;#39; - is having a quiet renaissance in 2026 as the limits of correlation-based machine learning have become harder to ignore. A look at what has changed, what the practical methods are, and why this matters for anyone using data to make decisions.</description>
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