Few days back, February 6, was the UN International Day for Ending FGM. The 2026 theme is: “Towards 2030: No end to female genital mutilation without sustained commitment and investment.”
FGM/C is a public health issue, a global health challenge, and a human rights violation. It persists because it is driven by social norms, not just ignorance. Changing behavior is hard. Predicting risk is harder.
Here’s where AI and machine learning can help:
Risk mapping: ML models can analyze health, education, and survey data to identify communities and periods of highest risk. Prevention becomes proactive, not reactive.
Message optimization: AI can test which social and behavior change messages resonate with parents, elders, youth and communities, improving relevance and impact.
Tracking norm shifts: Natural language processing can monitor community feedback and media to see where attitudes are softening and where resistance is rising.
Guiding resource allocation: With limited funding, AI helps target resources where they protect the most girls and strengthen local systems.
The point is this: AI will not end FGM/C on its own. Communities, trust, and human leadership will. But local innovation using AI and ML can reduce blind spots, stretch budgets, and support prevention, survivor care, and policy decisions.
Ending Female Genital Mutilation/Cutting by 2030 is still possible- but, only if we combine sharper intelligence with sustained human action.
♻️Connect with me Ijeoma Chiemela, where I design, lead, and share insights on AI and Machine Learning solutions for Global Health and Biosecurity.
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