Blind Spots and Biases: Exploring the Role of Annotator Cognitive Biases in NLP

• URL: http://arxiv.org/abs/2404.19071v1
• Date: Mon, 29 Apr 2024 19:28:35 GMT
• Title: Blind Spots and Biases: Exploring the Role of Annotator Cognitive Biases in NLP
• Authors: Sanjana Gautam, Mukund Srinath,
• Abstract summary: There is growing concern over its potential to exacerbate existing biases and societal disparities. This issue has prompted widespread attention from academia, policymakers, industry, and civil society. Our research focuses on reviewing existing methodologies and ongoing investigations aimed at understanding annotation attributes that contribute to bias.
• Score: 3.9287497907611875
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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