The Open for Good alliance is building open, training datasets—data AI can train on—so it actually works in Africa, Asia, and beyond.
- Localized data sets are training data that reflect a specific place and people, not generic global data.
Why it matters
- Most AI fails without high‑quality local data; Open for Good fixes the bottleneck.
- Focuses on non‑discriminatory, open data that’s maintained over time.
- Goal: a training data commons people can find, use, and improve
Why you should care—wherever you are in the world:
- Better products and services, bigger markets: models trained on local data work for millions of new users.
- More robust AI for everyone: diverse data reduces blind spots and bias.
- Real‑world impact: voice tools that understand local languages, public‑service chatbots, and climate apps that perform in context first—then generalize.
Who’s behind it
- Members include A+ Alliance, AIMS, Mozilla, UNESCO, A2K4D, Radiant Earth, and more.
Quick links
- Lessons: Responsible AI Assessments (three‑part method)
- Visual: Open Data Licensing — demystifies how to release datasets safely
- Webinars: Open AI & Data in Law and Justice Systems
Check out https://openforgood.info — then share or use a dataset to help build the training data commons.