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

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

This paper describes threats to making valid causal inferences about pandemic impacts on student learning based on cross-year comparisons of average test scores. The paper uses Spring 2021 test score ...

The aim of this research therefore was to streamline the understanding of typical causal structures in both randomized and nonrandomized clinical trials in oncology, presenting concise guidelines for ...

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 ...

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