We are in the midst of an unprecedented surge of interest in machine learning (ML) and artificial intelligence (AI) technologies. These tools, which allow computers to make data-derived predictions and automate decisions, have become part of daily life for billions of people. While they have the potential to improve outcomes across sectors, they also pose potential risks, especially when applied in development programs and in developing countries. To avoid these risks, development professionals must understand both the risks and benefits of these emerging technologies when applied in their programs.
This document aims to inform and empower those who may have limited technical experience as they navigate an emerging ML/AI landscape in developing countries. Donors, implementers, and other development partners should expect to come away with a basic grasp of common ML techniques and the problems ML is uniquely well-suited to solve. The document also outlines some of the ways in which ML/AI may fail or be ill-suited for deployment in developing-country contexts. Awareness of these risks, and acknowledgement of our role in perpetuating or minimizing them, will help development and technical experts work together to protect against harmful outcomes and ensure that AI and ML are contributing to a fair, equitable, and empowering future.
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