A year ago, U.S. President Donald Trump shut down public access to the Development Experience Clearinghouse, a $30 billion database holding 60 years’ worth of institutional knowledge from more than 150,000 projects administered by the U.S. Agency for International Development. But before the closure, former USAID employee and artificial intelligence scientist Lindsey Moore used a large language model (LLM) to read all of the information in this database — rescuing critical lessons on development, environmental, economic and social projects in countries across the globe, all documented by USAID. The data also included information on conservation projects. Many of the challenges presented in these projects repeated over the years, but the lessons were rarely retained — something Moore’s tech startup, DevelopMetrics, hopes to change. Moore joins this week’s podcast to explain what those lessons are and what conservationists can learn from them. DevelopMetrics deploys an AI model capable of understanding not just the information from USAID’s database, but also other public databases that could be at risk of deletion or being lost to time. Moore says the problems identified in the data are often not technological in nature, as they occurred over the course of six decades across various sectors and countries. Instead, they tend to be institutional, often rooted in the lack of local community engagement. “Most of the work of development happens in these air-conditioned rooms. And of course, field work is always encouraged, but it’s expensive.” Many of the solutions that Moore highlights in the conversation involve directly…This article was originally published on Mongabay

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