Most AI systems are trained on historical data. When conditions shift due to changing consumer sentiment, models trained on ...

Learn how Nihar V. Patel redefines marketplace data science by using causal inference and fairness frameworks to measure ...

In the article that accompanies this editorial, Lu et al 5 conducted a systematic review on the use of instrumental variable (IV) methods in oncology comparative effectiveness research. The main ...

We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...

Sub-headline: BIT researchers introduce CausalBridgeQA to tackle spurious correlations in complex multi-hop reasoning chains.

The crypto market has defeated more prediction models than any other asset class in history. Neural networks trained on ...

Every bank runs models. Credit scoring models. Fraud detection models. Customer risk models. AML transaction monitoring ...