collaborators

6 papers

cs.CY2026

AI Strategy: How to Choose What AI Product to Implement

Foster Provost, Panos Ipeirotis

Firms struggle to choose AI projects that pay off: two projects can look equally promising to smart, motivated stakeholders and yet deserve opposite decisions. At the residential r…

stat.ML2026

Logging Policy Design for Off-Policy Evaluation

Connor Douglas, Joel Persson, Foster Provost

Off-policy evaluation (OPE) estimates the value of a target treatment policy (e.g., a recommender system) using data collected by a different logging policy. It enables high-stakes…

econ.GN2026

The Illusion of Collusion

Connor Douglas, Foster Provost, Arun Sundararajan

Algorithmic agents are used in a variety of competitive decision-making settings, including pricing contexts that range from online retail to residential home rental. We study the…

cs.LG2026

Prompt-Counterfactual Explanations for Generative AI System Behavior

Sofie Goethals, Foster Provost, João Sedoc

As generative AI systems become integrated into real-world applications, organizations increasingly need to be able to understand and interpret their behavior. In particular, decis…

stat.ML2025

Causal Post-Processing of Predictive Models

Carlos Fernández-Loría, Yanfang Hou, Foster Provost +1

Organizations increasingly rely on predictive models to decide who should be targeted for interventions, such as marketing campaigns, customer retention offers, or medical treatmen…

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…