Title

An OR journey toward fair and explainable Machine Learning

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are disruptive technologies that create significant opportunities while also raising profound challenges. We are witnessing a paradigm shift in which AI and ML are increasingly automating decision-making processes. However, automation alone is not enough: it must also be carried out in a trustworthy manner. In this context, Operations Research is not only relevant but essential, and our team has worked on these challenges for decades. In this talk, we will explore some of the major contributions of Multi-Objective Optimization to Fair and Explainable ML.

Keywords

  • Data Driven Decision Making
  • Machine learning
  • Multi-objective optimization

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