As AI-driven technologies become increasingly integrated into daily life, understanding their impact on diverse populations is critical. The importance of insights from African women and girls on the safety, supportiveness, and potential harms of AI-chatbot interactions cannot be overstated. By centering these lived experiences, developers and policymakers can identify unique cultural nuances and systemic risks that are often overlooked. This approach ensures that AI tools are not just technologically advanced, but are also safe, inclusive, and genuinely supportive of the communities they serve.
We’ve all been there. You’re chatting with an AI, maybe trying to figure out a symptom, get some insights on a problem, or just vent about a long day, and the response you get feels off. It’s polite, sure. It’s grammatically correct. But it feels like it’s coming from someone who has never lived a day in your shoes.
Now, imagine that disconnect not just as a minor annoyance, but as a barrier to safety, health, or economic opportunity. This is the reality for millions of African women and girls interacting with AI-driven technologies today.
As we hurtle toward a future where chatbots are our first point of contact for everything from banking to mental health, we have to ask: Who are these bots actually built for? If the answer isn't "everyone," then we have a problem. To fix it, we need to stop treating African women and girls as an afterthought and start centering their lived experiences at the very heart of AI development.
The tech world has a default setting. Historically, that setting has been Western, male, and English-speaking. When developers in a high-rise in California or London build an AI, they (often unintentionally) bake their own cultural assumptions, slang, and social norms into the code.
When these tools are exported to diverse contexts - say, a marketplace in Accra or a university in Nairobi - the default settings start to glitch. For an African woman, a chatbot might:
▪︎ Fail to understand local dialects eg Sheng (urban slang language in Kenya)
▪︎ Provide advice that is culturally insensitive or financially impossible.
▪︎ Ignore the specific safety risks she faces in her community.
Intellectual honesty check: We can’t just patch bias after the fact. If the foundation is built on a narrow worldview, the structure will always be a bit shaky for everyone else.
When we talk about AI safety, we often think of preventing the bot from saying something rude. But for women and girls in many African contexts, safety is much more complex.
Language is more than just translation; it’s about context. If a young girl in rural Rwanda uses a chatbot to ask about reproductive health, the bot needs to understand the social stakes of that conversation. Does it use clinical terms that feel cold and scary, or does it use supportive, culturally grounded language? If it doesn’t understand the local nuances of privacy and stigma, it isn't truly safe.
African women often navigate unique systemic risks, from specific types of gender-based violence to different digital surveillance landscapes. An AI that doesn’t recognize these patterns can’t help mitigate them. By listening to these women, developers can identify blind spots - risks that a developer in the Global North wouldn't even know to look for.
We often hear the word inclusion tossed around in corporate meetings. But inclusion usually means "we built this thing, and now we’ll let you use it too."
What we actually need is co-creation.
Centering the insights of African women means bringing them into the room before the first line of code is written. It means asking:
"What problems are you actually trying to solve?"
"What makes you feel unsafe online?"
"How do you want to be spoken to?"
When we do this, the AI stops being a generic tool and starts being a genuine support system.
When you build an AI that is safe and intuitive for a teenage girl in a bustling African city, you aren't just helping her. You're actually building better tech for everyone.
Clarity: Cutting through jargon helps everyone.
Empathy: More nuanced emotional intelligence makes the bot more helpful for every user.
Robustness: An AI that can handle complex, multi-lingual, and culturally diverse inputs is a more powerful piece of technology, period.
If we continue to overlook these perspectives, we risk creating a digital apartheid. We’ll have one tier of AI that works perfectly for the West, and another tier - full of hallucinations, biases, and safety gaps - for the rest of the world.
Moreover, African women are some of the most prolific entrepreneurs and community leaders on the continent. By failing to provide them with AI tools that actually work for their lives, we are effectively stifling economic and social progress.
"AI should be a mirror that reflects the world’s diversity, not a magnifying glass that enlarges its existing inequalities."
The goal isn't just to make AI "less bad" for African women; it’s to make it genuinely excellent.
Policymakers need to demand that AI companies prove their models have been tested with diverse populations. Developers need to move past token diversity and invest in local research hubs across the continent. And most importantly, we need to empower African women and girls to be the architects of their own digital futures.
We are at a crossroads in the history of technology. We can either automate the biases of the past, or we can use AI to build a more inclusive bridge to the future. The choice depends entirely on whose voices we decide to listen to right now.
The verdict? African women and girls aren't just "users" to be studied. They are the experts we’ve been missing. It’s time we started acting like it.