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[MUSIC PLAYING] AMIT GANDHI: Hi, my name is Amit Gandhi. And I'm a graduate researcher at MIT. Welcome to the series on exploring fairness and machine learning for international development. In this module, we will have an example of how an organization would go about implementing machine learning and what some of the ethical challenges that may arise are. This module primarily focuses on decisions that are made at the organizational level. But it is important for both organizational decision makers and machine learning implementers to consider these interactions. In this case study, we will be taking the role of a chief technology officer of a social enterprise to provide solar lighting products in East Africa. The mission of the company is to provide affordable lighting solutions to people living in poverty. And the company started off by providing high-quality, inexpensive solar light, so a replacement for kerosene lanterns. Over time, the company has grown and inc...

[MUSIC PLAYING] AMIT GANDHI: Hi, my name is Amit Gandhi. And I'm a graduate researcher at MIT. Welcome to this course on exploring fairness in machine learning for international development. In this video, we will examine bias in machine learning models through a pulmonary health diagnostic case study. In particular, we will explore the influence of representative data on accuracy when building a model. Pulmonary diseases, including asthma COPD, allergic rhinitis, and others, can have significant detrimental health impacts if undetected. In remote areas with limited access to health care, they can often go undiagnosed and untreated. The motivation for this work was to develop a screening tool for community health workers to determine if patients who were presenting symptoms of pulmonary disease actually have pulmonary disease. To develop the tool, data was collected from 303 patients who sought medical care at health clinics between 2015 and 2018 in Kuna, India. Patie...

[MUSIC PLAYING] AMIT GANDHI: Hi, my name is Amit Gandhi, and I'm a graduate researcher at MIT. Welcome to this course on exploring fairness in machine learning for international development. I'm going to present the motivation for this course, why it is important to pay attention to ethics and appropriate use in the topics we will be covering. Let's start with an introduction to how machine learning is being used in international development. As a brief review, machine learning is a branch of artificial intelligence in which software learns how to perform a task based on experience as opposed to being explicitly programmed. As a result, this emerging technology is widely applicable across many fields and can leverage the power of data in ways that were previously impossible. Some application areas for machine learning include medicine, workforce development, and financial inclusion. In the next few slides, I will talk about some of the ways machine learning is...