Tutorial on bias and fairness in search and recommender systems

What is it about?

This tutorial covers basic concepts, definitions, optimization algorithms, evaluation metrics, challenges and opportunities in the field of bias and fairness in search and recommender systems, explained by examples and case studies.

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Why is it important?

This tutorial serves as an introductory material as well as an overview of the field of fairness-aware systems. We show how to differentiate fairness from common concepts such as bias and diversity, formulate fairness as an optimization problem, design fairness-aware algorithms, and evaluate such systems.