Preface to the special issue on fair, accountable, and transparent recommender systems

@article{Burke2021PrefaceTT,
  title={Preface to the special issue on fair, accountable, and transparent recommender systems},
  author={Robin D. Burke and Michael D. Ekstrand and Nava Tintarev and Julita Vassileva},
  journal={User Model. User Adapt. Interact.},
  year={2021},
  volume={31},
  pages={371-375}
}
Personalization has become a ubiquitous and essential part of systems that help users find relevant information in today’s highly complex information-rich online environments. Recommender systems are a key enabling technology that allows intelligent systems to learn from users and adapt their output to users’ needs and preferences. However, there has been a growing recognition that these underlying technologies raise novel ethical, legal, and policy challenges. It has become apparent that a… 
1 Citations
Retrieval and Recommendation Systems at the Crossroads of Artificial Intelligence, Ethics, and Regulation
TLDR
The mostly technical audience of SIGIR is equipped with the necessary understanding of the ethical implications of their research and development on the one hand, and of recent political and legal regulations that address the aforementioned challenges on the other hand.