Recommender systems play a pivotal role in shaping our digital experiences, influencing the content we see online, the products we consider purchasing, and the entertainment choices we make, such as which movies to watch. The increased adoption of deep learning technologies in recommender systems, while enhancing their efectiveness, has also raised substantial concerns regarding their transparency and trustworthiness. Critical issues such as bias, fairness, and privacy are increasingly coming under scrutiny, both in public discourse and academic research. In response, there's a growing momentum in developing recommender systems that are not only eficient but also uphold these ethical standards.