@inproceedings{gautam-srinath-2024-blind,
    title = "Blind Spots and Biases: Exploring the Role of Annotator Cognitive Biases in {NLP}",
    author = "Gautam, Sanjana  and
      Srinath, Mukund",
    editor = "Blodgett, Su Lin  and
      Cercas Curry, Amanda  and
      Dev, Sunipa  and
      Madaio, Michael  and
      Nenkova, Ani  and
      Yang, Diyi  and
      Xiao, Ziang",
    booktitle = "Proceedings of the Third Workshop on Bridging Human--Computer Interaction and Natural Language Processing",
    month = jun,
    year = "2024",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.hcinlp-1.8/",
    doi = "10.18653/v1/2024.hcinlp-1.8",
    pages = "82--88",
    abstract = "With the rapid proliferation of artificial intelligence, there is growing concern over its potential to exacerbate existing biases and societal disparities and introduce novel ones. This issue has prompted widespread attention from academia, policymakers, industry, and civil society. While evidence suggests that integrating human perspectives can mitigate bias-related issues in AI systems, it also introduces challenges associated with cognitive biases inherent in human decision-making. Our research focuses on reviewing existing methodologies and ongoing investigations aimed at understanding annotation attributes that contribute to bias."
}