Exploring fairness in machine learning for international development
The Comprehensive Initiative on Technology Evaluation (CITE) at the Massachusetts Institute of Technology (MIT) produced a paper that looks at how fairness could be achieved by avoidable biases when developing machine learning (ML) for international implementation. The paper explores relevant areas that include the choice of algorithms, data use, software development management, providing relevant guidance to the application of these technologies through a case study. The paper was supported by the US Agency for International Development’s (USAID) Center for Development Research (CDR) and the USAID Center for Digital Development.