Recommendation systems have become an integral part of the online experience, influencing what we see, read, and buy. However, these systems have been shown to perpetuate and amplify biases, leading to unfair and inequitable outcomes for certain groups of users. In this talk, we will explore the importance of fairness in recommendation systems and discuss strategies for designing and implementing systems that promote equity.

We will examine real-world examples of bias in recommendation systems and consider the ethical implications of these biases. Finally, we will discuss the role that technologists and other stakeholders can play in creating a more equitable web through the design and use of fair recommendation systems