Offered by Mila and the Public Policy Forum, this program is designed to equip policy and decision makers with the tools to navigate the opportunities and risks of AI. The next cohort will be held in French on September 1-2, 2026, at Mila.
This program supports AI startups at any time of the year. Benefit from cutting-edge resources and tailored support to accelerate your technology's development.
Connect with a Mila academic advisor and current student-researchers to learn more about Mila's community and how to join us on August 19, 31 and September 11, 2026.
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Richard Khoury
Affiliate Member
Associate Professor, Université Laval, Department of Computer science and software engineering
Machine learning classifiers in dynamic environments face concept drift -- changes in the data-generating process that degrade performance. … (see more)Conventional evaluation via static test sets or noise perturbations fails to preserve causal dependencies in tabular data, often producing causally invalid assessments. Post-hoc tools like SHAP and LIME offer correlational insights that may not reflect the causal mechanisms driving model failure. We propose a framework that complements existing drift detection by leveraging Structural Causal Models as "Digital Twins" of data-generating processes, enabling precise causal interventions while preserving structural dependencies. Our technique, Causal Parametric Drift Simulation, stress-tests classifiers to identify vulnerabilities before deployment. Experiments on the Open Sourcing Mental Illness (OSMH) dataset demonstrate that this approach exposes latent vulnerabilities invisible to standard statistical monitors.