Artificial intelligence solutions are proliferating across the developing world. This growth in AI is highlighting instances of inequitable design, use, and impact of AI-enabled tools. Many of these machine learning tools and approaches have the capacity for inequitable outcomes across genders due to humans unconsciously embedding bias in AI technology during data collection, model design or end-use applications.

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