For decades, artificial intelligence has excelled at spotting patterns in data. Machine learning models can predict customer behavior, forecast market trends, or identify medical risks with high ...

In an era where data-driven decision-making dominates the business landscape, traditional AI has excelled at predicting outcomes based on past occurrences. Yet, as our challenges grow in complexity, ...

In addition to efficient statistical estimators of a treatment’s effect, successful application of causal inference requires specifying assumptions about the mechanisms underlying observed data and ...

For decades, causal inference methods have found wide applicability in the social and biomedical sciences. As computing systems start intervening in our work and daily lives, questions of ...