Unifying Bias and Unfairness in Information Retrieval: A Survey of Challenges and Opportunities with Large Language Models

arXiv:2404.11457v1 Announce Type: cross
Abstract: With the rapid advancement of large language models (LLMs), information retrieval (IR) systems, such as search engines and recommender systems, have undergone a significant paradigm shift. This evolution, while heralding new opportunities, introduces emerging challenges, particularly in terms of biases and unfairness, which may threaten the information ecosystem. In this paper, we present a comprehensive survey of existing works on emerging and pressing bias and unfairness issues in IR systems when the integration of LLMs. …

arxiv bias challenges cs.ai cs.cl cs.ir information language language models large language large language models opportunities retrieval survey type