M4 · Recalibrating the AI Revolution — datocracy

M4 · Recalibrating the AI Revolution

How to Build, Use, and Govern AI on Africa's Terms

Half-day interactive workshop · eLearning Africa 2026 · Wed 3 June 2026 · 09:00–12:30 · Room Adinkra
Facilitators: Dr Ronda Železný-Green (UK) · Habib Houndekindo (Senegal)

Where Data & Democracy Meet

Everything in this companion works offline and stays in your browser. Nothing you type is sent anywhere — your notes, tool assessment and roadmap are saved on this device only. Use Print / Save as PDF at the bottom to keep a copy.

Today is not about how to use one more tool. It is about governing AI on your own terms: deciding the purpose, the limits, who is accountable, and whose knowledge counts.

Agenda

Time	Block	What happens
09:00	Welcome & orientation	Objectives, ground rules, framing question
09:15	Session 1 · Beyond access	A governance-first lens on AI + discussion
10:00	Session 2 · Interrogating AI tools	Hands-on tool review in small groups
10:45	Coffee break	15 minutes
11:00	Session 3 · Your AI roadmap	Draft your one-page institutional roadmap
12:00	Peer review & synthesis	Exchange roadmaps, plenary, next steps

The governance-first framework

1 · Local knowledge as expertise

Treat community, indigenous and frontline knowledge as primary data — not decoration.

2 · Institutional readiness

People, policy and infrastructure in place before a tool is adopted.

3 · Accountability

Who decided, who is responsible, and how do we review and challenge?

4 · Data stewardship

Named roles for how data is collected, stored, shared, protected and retired.

Framing question

What does it mean to govern AI rather than merely use it?

Your first answer (before we discuss) After the discussion — did your answer change? How?

Dependency–agency spectrum

Passive consumerUses whatever is given. No questions about data, bias or cost.

Cautious userSenses risks but has no process; relies on goodwill.

Active managerHas rules: checks outputs, manages data, trains staff.

Governance leaderSets purpose & limits, names roles, holds tools accountable.

Today, my organisation is mostly a… (which stage, and why)

In 12 months I want us to be a… (stage + the one behaviour to get there)

AI tool assessment

Interrogate one real AI tool. Write evidence, not opinions. Saved on this device

1 · Tool name & purpose What is it, and what problem does it claim to solve — is that ours? 2 · Who introduced it & on what terms Donor / vendor / staff / leadership? Free, paid, or mandated? 3 · Data in / data out & where data goes What we put in, what it returns, and where our data is stored or reused. 4 · Observed extractive patterns What does it take from us vs. give back? Lock-in, reuse, our labour. 5 · Observed bias Whose knowledge, language and context is centred — or missing? 6 · Accuracy / fabrication check What did we test? Where did it invent or get local detail wrong? 7 · Local-relevance check Does it work in our languages, infrastructure and norms? Verdict

Use Use with limits Don't use

Mitigations — what must change for a safer verdict?

My institutional AI roadmap

One page, six sections. Rough and real beats polished and empty. Name people, not “the team”.

1 · Organisation & context Who we are, who we serve, our languages and constraints. 2 · Priority AI use cases (2–3) Tied to our mission — and one we will NOT pursue yet. 3 · Data stewardship roles Named people for data in, out, storage, consent and protection. 4 · Accountability & review cycles Who signs off, how often we review, how harms are reported. 5 · Peer-learning plan How we keep learning — inside and beyond our organisation. 6 · First 90-day actions (start on Monday)

Action	Owner (name)	By when

Next steps & resources

Keep the practice alive

Run your first tool review within 2 weeks.
Name your data steward this month.
Start a monthly 30-min “AI clinic”.
Revisit your roadmap each quarter.

Learn with datocracy

Join datocracy's community of practice.
Explore datocracy's learning offers on data & AI.
Ask about the people-centred AI ethics framework.
Follow the Africa AI Literacy Movement.

Stay connected

Swap contacts with two people today.
Pair with a peer organisation for accountability.
Share your roadmap with your leadership.
Tell us how it goes — we learn from you.

My accountability partner from today

Contact: learn@datocracy.ai · datocracy — Where Data & Democracy Meet

Workshop materials & downloads

Access the full workshop slide deck, handouts, templates and reference materials from the shared drive.

Download session materials

Open Google Drive folder →

Your entries are stored only in this browser.