AI increases online abuse of women in NigeriaCEFR B2
10 Apr 2026
Adapted from Guest Contributor, Global Voices • CC BY 3.0
Photo by Ahmed Nasiru, Unsplash
Generative AI tools on social media have changed the online environment for women in Nigeria, making abuse easier to produce and share. Pre-existing problems — misogynistic abuse, cyberstalking and organised campaigns — intensified when AI began to generate and edit images from simple prompts. Investigations showed users misused Grok, an assistant embedded in X, to create non-consensual sexualised images of women and minors, and researchers found the tool could still produce such imagery despite platform policy updates.
Research and projections warn the issue may grow as generative AI spreads. A Gatefield report published in February 2026 estimated that by 2030 as many as 70 million Nigerian women and girls could be exposed to AI‑facilitated online abuse each year, with 30 million directly targeted. Earlier studies also highlighted gaps: UN estimates point to limited legal protections globally, ActionAid Nigeria reported widespread cyberstalking, and Gatefield’s 2024 State of Online Harms in Nigeria report found women were targeted in 58 percent of online abuse cases. X and Facebook were named as main platforms, and only a minority of users find X responsive to complaints.
Experts say the problem stems from weak enforcement, monetisation systems that reward engagement, and opaque algorithms that determine what is visible. To reduce harm, design and policy teams led by groups such as Superbloom, the Tech Policy Design Lab and Tope Ogundipe of TechSocietal recommend applying a gendered privacy lens before and after AI deployment. Key measures include:
- governance commitments and staff training
- accessible grievance mechanisms and meaningful consent
- data minimisation, encryption, and engagement with women’s rights groups
Applying these steps aims to limit harm, but it remains unclear whether platforms will adopt them.
Difficult words
- generative — creating new content from prompts
- misogynistic — showing strong dislike or hatred of women
- cyberstalking — repeated online harassment or tracking of someone
- non-consensual — done without a person's clear permission
- monetisation — making money from a product or service
- opaque — not clear or transparent in how it works
- data minimisation — collecting only necessary personal information
- grievance mechanism — a way to report complaints and seek remedygrievance mechanisms
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- Which recommended measure (for example data minimisation, grievance mechanisms, or staff training) do you think would be most effective, and why?
- How might platform monetisation models increase the risk of AI-facilitated abuse?
- What obstacles could prevent platforms from adopting the design and policy steps suggested in the article?
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