Describe three real AI deployments on the African continent
Evaluate one AI service you use with a critical eye
Identify one opportunity gap in your own community
Health and agriculture
AI assists radiology triage in several African hospitals, and mobile apps grade crop disease from a phone photo for smallholder farmers. The pattern: AI works best where it augments a scarce expert, not where it replaces people.
Finance and inclusion
Mobile money platforms use ML for fraud detection and alternative credit scoring, letting people without bank history access loans. Language models now support Swahili, isiZulu, Yoruba and more, shrinking the language gap in digital services.
Government and your critical eye
From traffic management to service chatbots, public AI is growing - and so are procurement and accountability questions. For every AI service you use, ask: what data does it take, who benefits, who can be harmed, and who is accountable when it fails?
Key terms
Augmentation
AI assisting human experts rather than replacing them.
Alternative credit scoring
Using non-traditional data to assess loan risk.
Low-resource languages
Languages with limited training data; a fairness frontier.
Accountability
A named human answerable for an AI decision.
🛠 Hands-on task: Community opportunity map
Tools: Notebook
List 3 problems in your community (transport, water, study, safety).
For each, write one line: could AI assist a scarce expert here?
Circle the one you would choose for your Week 4 portfolio.
Key takeaways: Before you go, three takeaways from this lesson. One: Describe three real AI deployments on the African continent. Two: Evaluate one AI service you use with a critical eye. Three: Identify one opportunity gap in your own community. And your hands-on task: community opportunity map. List 3 problems in your community (transport, water, study, safety). When it is done, mark the lesson complete on your dashboard, keep the artifact for your portfolio, and step into the next lesson. I will see you there.
