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Dataset diversity: measuring and mitigating geographical bias in image search and retrieval
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In: Mandal, Abhishek, Leavy, Susan and Little, Suzanne orcid:0000-0003-3281-3471 (2021) Dataset diversity: measuring and mitigating geographical bias in image search and retrieval. In: 1st International Workshop on Trustworthy AI for Multimedia Computing, 24 Oct 2021, Chengdu, China. ISBN 978-1-4503-8674-6 (2021)
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Uncovering Gender Bias in Media Coverage of Politicians with Machine Learning ...
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Mitigating Gender Bias in Machine Learning Data Sets ...
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Abstract:
Artificial Intelligence has the capacity to amplify and perpetuate societal biases and presents profound ethical implications for society. Gender bias has been identified in the context of employment advertising and recruitment tools, due to their reliance on underlying language processing and recommendation algorithms. Attempts to address such issues have involved testing learned associations, integrating concepts of fairness to machine learning and performing more rigorous analysis of training data. Mitigating bias when algorithms are trained on textual data is particularly challenging given the complex way gender ideology is embedded in language. This paper proposes a framework for the identification of gender bias in training data for machine learning.The work draws upon gender theory and sociolinguistics to systematically indicate levels of bias in textual training data and associated neural word embedding models, thus highlighting pathways for both removing bias from training data and critically ... : 10 pages, 5 figures, 5 Tables, Presented as Bias2020 workshop (as part of the ECIR Conference) - http://bias.disim.univaq.it ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://arxiv.org/abs/2005.06898 https://dx.doi.org/10.48550/arxiv.2005.06898
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Navigating Literary Text with Word Embeddings and Semantic Lexicons
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Systems in Language: Text Analysis of Government Reports of the Irish Industrial School System with Word Embedding
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Uncovering gender bias in newspaper coverage of Irish politicians using machine learning
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