We plan to dedicate the 2023 – 2025 series of conferences to challenges and emerging topics in the area of mathematical statistics driven by the adventure of artificial intelligence. Tremendous progress has been made in building up powerful machine learning algorithms such as random forests, gradient boosting or neural networks. These models are exceptionally complex and difficult to interpret but offer enormous opportunities in many areas of application going from science, public policies to business. These sophisticated algorithms are often called “black boxes” as they are very hard to analyze. The widespread use of such predictive algorithms raises extremely important questions of replicability, reliability, robustness or privacy protection. The proposed series of conferences is dedicated to new statistical methods built around these black-box algorithms that leverage their power but at the same time guarantee their replicability and reliability.

The first conference of the cycle is dedicated to the potential of the statistical approach in accompanying the development of our data-driven society. Our goal is to encourage collaboration and knowledge sharing between theoretical computer scientists and mathematical statisticians by bringing them together in Luminy. Both communities possess unique visions, skills and expertise. We hope that merging these strengths will advance the field and bring us closer to solving some of the key challenges such as robustness, fairness and privacy of decision-making algorithms.