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Arxiv
2d
269
Image Credit: Arxiv
Investigating the Capabilities and Limitations of Machine Learning for Identifying Bias in English Language Data with Information and Heritage Professionals
- ML systems continue to harm marginalized people despite efforts to mitigate biases.
- Creating models to identify biased language instead of removing biases is a more feasible approach.
- Limitations of ML in identifying bias include its contextual nature and potential to privilege or oppress different communities.
- Expanding ML approaches to bias and fairness is necessary to address the limitations and promote a mixed-methods investigation.
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