In the past 10 years, hundreds of projects have applied artificial intelligence (AI) to creating social good. The right tool applied to an appropriate problem has the potential to drastically improve millions of lives through better service delivery and better-informed policy design. But what kind of investments do AI solutions need to be successful, and which applications have the most potential for social impact?

To narrow in on AI use cases that offer the most promise, our team at IDinsight synthesized existing research from the United Nations, McKinsey and Company, nonprofit practitioners, past work, and other groups in the social sector. From there, we identified about 120 use cases across 30 areas where developers are using AI to address social and environmental problems.

Using a detailed framework, our team then analyzed which of these areas will most likely lead to significant social impact. In addition to potential risks, this framework looks at:

  • Size of potential impact.
  • Implementation feasibility.
  • Opportunity area synergies.

As we looked through the use cases that scored highest against our framework, three criteria—large impact potential (depth and breadth), differential impact compared to non-AI tools, and a clear pathway to scale—stood out as useful shorthand to explain why certain areas are uniquely primed for investment. We also considered whether each area had sufficient proof-of-concept evidence illustrating its feasibility, as well as manageable risks that investment and careful modeling can safely overcome. (The full framework outlines a process for more robust and precise analysis.)

Our analysis pinpointed three specific areas that appear optimal for near-term investment: medical diagnostic tools, communication support for marginalized communities and languages, and agricultural yield prediction. It’s important to note that these are not the only areas that AI could drive significant social good. Other areas we analyzed that scored well against our framework included medical research/drug discovery, natural disaster response, supply chain forecasting, and combatting misinformation. While we don’t detail these areas here, we encourage others to explore them.

Read the full article about AI for good by Ben Brockman, Skye Hersh, Brigitte Hoyer Gosselink, Florian Maganza & Micah Berman at Stanford Social Innovation Review.