How do you ensure diversity and fairness in recommender systems?
Recommender systems are algorithms that suggest items or services to users based on their preferences, behavior, or context. They are widely used in e-commerce, entertainment, social media, and other domains to enhance user experience and generate revenue. However, recommender systems also face challenges in ensuring diversity and fairness, which means providing users with a variety of relevant options and avoiding bias, discrimination, or harm. In this article, you will learn how to design and evaluate recommender systems that promote diversity and fairness, and some of the trade-offs and ethical issues involved.