Taxonomizing and Measuring Representational Harms: A Look at Image Tagging
نویسندگان
چکیده
In this paper, we examine computational approaches for measuring the "fairness" of image tagging systems, finding that they cluster into five distinct categories, each with its own analytic foundation. We also identify a range normative concerns are often collapsed under terms "unfairness," "bias," or even "discrimination" when discussing problematic cases tagging. Specifically, four types representational harms can be caused by providing concrete examples each. then consider how different measurement map to these types, demonstrating there is not one-to-one mapping. Our findings emphasize no single approach will definitive and it possible infer from use particular which type harm was intended measured. Lastly, equipped more granular understanding show attempts mitigate some may in tension one another.
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ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2023
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v37i12.26670