3 papers
stat.ML2025
From What Ifs to Insights: Counterfactuals in Causal Inference vs. Explainable AI
Galit Shmueli, David Martens, Jaewon Yoo +1
Counterfactuals play a pivotal role in the two distinct data science fields of causal inference (CI) and explainable artificial intelligence (XAI). While the core idea behind count…
cs.LG2025
Beware of "Explanations" of AI
David Martens, Galit Shmueli, Theodoros Evgeniou +14
Understanding the decisions made and actions taken by increasingly complex AI system remains a key challenge. This has led to an expanding field of research in explainable artifici…
stat.OT2025
Good intentions, unintended consequences: exploring forecasting harms
Bahman Rostami-Tabar, Travis Greene, Galit Shmueli +1
Organizations worldwide that rely on data-driven approaches regularly employ forecasting methods to enhance their planning and decision-making processes. While extensive research h…