EPISODE · Apr 20, 2026 · 37 MIN
AI for Good
from vBrownBag · host vBrownBag
Join us as Kira Intrator (MIT-trained urban planner, systems thinker, and social impact technologist based in Geneva) makes the case that AI for Good isn't failing because of models - it's failing because of systems. Kira walks through why so many AI pilots never reach deployment, drawing on her experience building tools scaled across 9,000 users, three ministries, and six countries in Central Asia. You'll learn the five factors that kill AI projects in the development sector, why 80% of clinical AI models are trained on data that can't be deployed outside Western contexts, and what the $2.6 trillion opportunity in developing markets actually requires to unlock. This episode is equal parts systems thinking masterclass and call to action - a rare perspective from someone who has moved AI from prototype to production in places most tech professionals never consider. Timestamps 0:00 Welcome & Introduction 2:47 Kira's Background: MIT, Geneva, Central Asia 3:54 The Core Thesis: It's About Systems, Not Models 5:20 AI is Our Generation's Revolution 6:35 The $2.6 Trillion Opportunity 7:17 The 80% Western Data Problem 8:20 Why AI Projects Fail in Development: 5 Factors 9:28 Systems Mismatch & Low-Bandwidth Environments 9:52 Built for Pilot vs. Built for Deployment 10:29 Ownership, Economics & Sustainability 18:22 Real-World Case Studies 24:16 What Actually Works: Levers for Scale 30:41 The Role of Tech Companies & Foundations 33:39 Crystal Ball: Merging the Two Universes 35:01 A Call to Action 38:48 Wrap-up How to find Kira: https://www.linkedin.com/in/kiraintrator/ Links from the show: Infrastructure & Platforms Anthropic Beneficial Deployments: https://www.anthropic.com/ Google Research Global South Labs: https://research.google/ Lelapa AI: https://lelapa.ai/ Microsoft AI for Good: https://www.microsoft.com/en-us/ai/ai-for-good OpenAI Foundation: https://openai.com/ Research & Innovation Hubs Data Science Africa: https://www.datascienceafrica.org/ Masakhane: https://www.masakhane.io/ Stanford HAI: https://hai.stanford.edu/ Wadhwani AI: https://www.wadhwaniai.org/ Global Governance & Policy OECD AI Observatory: https://oecd.ai/ UNICEF Office of Innovation: https://www.unicef.org/innovation/ World Health Organization AI: https://www.who.int/ Funders & Philanthropies Gates Foundation: https://www.gatesfoundation.org/ Patrick J. McGovern Foundation: https://www.mcgovern.org/ Conferences AI for Good Global Summit (July 7-10, 2026 - Geneva): https://aiforgood.itu.int/ Data Science Africa 2026 (July 20-24 - Kampala, Uganda): https://www.datascienceafrica.org/ Deep Learning Indaba 2026 (August 2-7 - Lagos, Nigeria): https://deeplearningindaba.com/
What this episode covers
Join us as Kira Intrator (MIT-trained urban planner, systems thinker, and social impact technologist based in Geneva) makes the case that AI for Good isn't failing because of models - it's failing because of systems. Kira walks through why so many AI pilots never reach deployment, drawing on her experience building tools scaled across 9,000 users, three ministries, and six countries in Central Asia. You'll learn the five factors that kill AI projects in the development sector, why 80% of clinical AI models are trained on data that can't be deployed outside Western contexts, and what the $2.6 trillion opportunity in developing markets actually requires to unlock. This episode is equal parts systems thinking masterclass and call to action - a rare perspective from someone who has moved AI from prototype to production in places most tech professionals never consider. Timestamps 0:00 Welcome & Introduction 2:47 Kira's Background: MIT, Geneva, Central Asia 3:54 The Core Thesis: It's About Systems, Not Models 5:20 AI is Our Generation's Revolution 6:35 The $2.6 Trillion Opportunity 7:17 The 80% Western Data Problem 8:20 Why AI Projects Fail in Development: 5 Factors 9:28 Systems Mismatch & Low-Bandwidth Environments 9:52 Built for Pilot vs. Built for Deployment 10:29 Ownership, Economics & Sustainability 18:22 Real-World Case Studies 24:16 What Actually Works: Levers for Scale 30:41 The Role of Tech Companies & Foundations 33:39 Crystal Ball: Merging the Two Universes 35:01 A Call to Action 38:48 Wrap-up How to find Kira: https://www.linkedin.com/in/kiraintrator/ Links from the show: Infrastructure & Platforms Anthropic Beneficial Deployments: https://www.anthropic.com/ Google Research Global South Labs: https://research.google/ Lelapa AI: https://lelapa.ai/ Microsoft AI for Good: https://www.microsoft.com/en-us/ai/ai-for-good OpenAI Foundation: https://openai.com/ Research & Innovation Hubs Data Science Africa: https://www.datascienceafrica.org/ Masakhane: https://www.masakhane.io/ Stanford HAI: https://hai.stanford.edu/ Wadhwani AI: https://www.wadhwaniai.org/ Global Governance & Policy OECD AI Observatory: https://oecd.ai/ UNICEF Office of Innovation: https://www.unicef.org/innovation/ World Health Organization AI: https://www.who.int/ Funders & Philanthropies Gates Foundation: https://www.gatesfoundation.org/ Patrick J. McGovern Foundation: https://www.mcgovern.org/ Conferences AI for Good Global Summit (July 7-10, 2026 - Geneva): https://aiforgood.itu.int/ Data Science Africa 2026 (July 20-24 - Kampala, Uganda): https://www.datascienceafrica.org/ Deep Learning Indaba 2026 (August 2-7 - Lagos, Nigeria): https://deeplearningindaba.com/
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AI for Good
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