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EdTech Hub’s AI Observatory: greater equity in learning outcomes in the age of AI

We, at the Edtech Hub, are pleased to announce the launch of the AI Observatory. This is the first post and the start of what we’re hoping will be a lively and ongoing conversation between the Hub, educators, policymakers, developers, technologists and funders. 

If that’s you then great, let’s start with three stories about this remarkable moment in time: 

🔢 Rori, an AI-powered virtual maths tutor, tested with 500 children in Ghana. Students had just one hour a week with Rori over WhatsApp, but the impact was huge. Learning outcomes by those using Rori improved, producing an effect size 0.36 — equivalent to gaining an extra year of school.

🍕 Angaza Elimu’s Founder Kiko Muuo will tell you about a teacher in rural Kenya who used generative AI to come up with ways to explain how to calculate the area of a circle in her class only to be offered pizza analogies? Though none of the children in her class had ever eaten pizza. 

💾 There are 85 data centres in the continent of Africa and 812 in California.

These three stories side-by-side do a good job of illustrating the various potential and challenges of this moment for AI in education — particularly in low- and middle-income countries (LMICs).

Last year, millions of dollars were invested in AI in education R&D, but it’s the way we integrate and implement these products in the real world that will disrupt and reshape a widening learning divide. As it stands, AI is set to widen the learning divide. Unless we design for equity and impact today.

Colleagues at the World Bank have identified how the widening equity gap is manifesting in the distinct groups of students: 

  1. The AI-Powered: In tech-rich cities, students use AI to think critically, solve problems, and build skills—with expert guidance ensuring they learn, not just use.
  2. The AI-Dependent: With good internet but little oversight, some students offload work to AI, gaining convenience but missing real learning.
  3. The AI-Excluded: For many, AI remains out of reach. Limited resources and training leave teachers and students struggling with even basic connectivity.

Most children in LMICs fall into the third category. That’s why our agenda is to make it more possible for these children to share in the upsides of this progress. 

To better understand, anticipate, guide and shape a more effective and equitable future for AI in education in LMICs, we’re embarking on an ambitious plan and we want you to join us on that journey.  

We’re going to ask questions like, how might we…

  • Ensure datasets are locally relevant?
  • Sustain the cost of compute over time?
  • Develop the talent and skills needed to adopt AI effectively?
  • Foster policy environment to support equitable AI use?
  • Identify AI integrations that add the most value to education systems?

We’ll be exploring  what is — and what isn’t — happening across curriculum reform, funding, safeguarding users and more. 

To do this, we’ll be working with those who see the challenges up close, if that’s you, get in touch at hello@edtechhub.org, or share this post with someone you think ought to be in this conversation.

And if you’re interested in what we discover and how our ideas shift over time, subscribe to our newsletter for updates about the EdTech, the AI Observatory, and more.

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