Metrics for popularity bias in dynamic recommender systems

Understand

Albeit the widespread application of recommender systems (RecSys) in our daily lives, rather limited research has been done on quantifying unfairness and biases present in such systems.

• Prior work largely focuses on determining whether a RecSys is discriminating or not but does not compute the amount of bias present in these systems.
• Biased recommendations may lead to decisions that can potentially have adverse effects on individuals, sensitive user groups, and society.
• Hence, it is important to quantify these biases for fair and safe commercial applications of these systems.