International Workshop on Algorithmic Bias in Search and Recommendation (BIAS 2025)

Designing search and recommendation models that are both efficient and effective has long been a central objective for both industry professionals and academic researchers. Yet, growing evidence highlights how models trained on historical data can reinforce pre-existing biases, potentially leading to harmful outcomes. Addressing these challenges by defining, evaluating, and mitigating bias across development workflows is a crucial step toward the responsible deployment of search and recommendation models in practice. The BIAS 2025 workshop seeks to gather innovative research and foster a shared space for dialogue among researchers and practitioners committed to advancing this fundamental direction. Workshop website: https://biasinrecsys.github.io/sigir2025/.