Academic researchers from underrepresented groups are contributing significantly to the literature on AI bias, offering new insights and methodologies for addressing these challenges. Their work is highlighting the importance of multi-dimensional and intersectional approaches to understanding and mitigating bias in AI, thereby shaping the direction of future AI research and development towards more inclusive models.
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