You've been selected to lead initiatives that deploy AI agents to help underserved communities around the world. Your decisions will shape how these technologies are implemented and the impact they have on people's lives.
In this simulation, you'll face real-world scenarios based on actual AI deployment projects. You'll make key decisions about system design, implementation strategies, and ethical considerations.
Your mission: Deploy AI agents that effectively address community needs while respecting local contexts and ensuring sustainability. The communities you serve are counting on your thoughtful leadership!
You are the project lead for a non-profit tech organization that has received funding to deploy an AI system to help smallholder cotton farmers in rural India combat pest infestations, particularly the devastating pink bollworm.
Many farmers in the region have limited education and technical literacy, but most have access to basic smartphones. Crop losses due to pests significantly impact their livelihoods, and traditional agricultural extension services are stretched thin.
Your team has been inspired by the Wadhwani AI initiative and wants to create a system that helps farmers identify, predict, and manage crop pests in real time.
How will you design the AI system's core architecture?
You are leading a technology initiative to deploy a mobile-based crop disease detection system across several countries in Sub-Saharan Africa, inspired by the PlantVillage Nuru system.
The system will help smallholder farmers identify diseases in staple crops like maize, cassava, and wheat. Early detection is critical, as diseases can spread rapidly and devastate entire harvests.
The target regions have varying levels of infrastructure, connectivity, and literacy. Your challenge is to create a system that works effectively across these diverse contexts.
How will you adapt the technology to work effectively in diverse African contexts?
You are the project director for a global initiative to deploy an AI-powered assistive technology similar to "Be My Eyes" for visually impaired individuals in regions with limited volunteer support.
The system will use advanced AI to interpret images and provide audio descriptions, helping users navigate their environment, read text, and identify objects.
Your focus is on making this technology accessible in underserved areas where traditional support services are scarce. The decisions you make will determine how effectively the technology serves these communities.
Given limited resources, which capabilities should your AI assistant prioritize?
You are implementing an AI-driven telehealth system in remote areas of Africa and South Asia where access to healthcare professionals is extremely limited.
The system will help with initial symptom assessment, appointment scheduling, and health record management. In many target communities, the nearest doctor may be hours away, and emergency medical transport is unreliable.
Your system could be the first point of medical contact for many people, making your decisions particularly consequential for community health outcomes.
How should you define the boundaries of what the AI system can and cannot do medically?
Congratulations, Technology Innovator! You've successfully navigated the complex challenges of deploying AI agents in underserved communities around the world.
Your decisions have demonstrated the importance of thoughtful technology deployment that considers local contexts, needs, and constraints. As these case studies show, AI has tremendous potential to address critical challenges in agriculture, healthcare, accessibility, and other domains when implemented with care.
Key takeaways from your deployment experience:
The communities you've served thank you for your thoughtful approach to technology deployment!