HealGorithms: Understanding the Potential for Bias and Discrimination in mHealth Apps

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HealGorithms: Understanding the Potential for Bias and Discrimination in mHealth Apps

August 28, 2018

July 2018 report from Michelle De Mooy, Center for Democracy & Technology

This report explores the potential for harmful bias in mHealth interventions and considers the impact of such bias on individuals, companies, and public health, ultimately providing recommendations for app developers to ensure that the tools they build are inclusive and nondiscriminatory. This report seeks to advance the conversation about — and implementation of — equity and inclusivity in automated decisions in the health sector in ways that benefit both the public and the companies using data to make decisions by: (a) providing a landscape of the mHealth ecosystem; (b) synthesizing research and investigations to draw out key issues and
concerns related to bias in automated decision-making in the commercial health context; and (c) making recommendations that advance identification and mitigation of bias and discrimination in processes that produce commercial health app content.

Part II of this report provides an overview of the mHealth marketplace, covering the types of mHealth apps available, how data flows in and out of these apps, who uses these apps, how these apps are regulated, and how effective these apps are. Part III discusses the efficacy of mHealth and suggests that reducing bias is vital to delivering effective health interventions with these tools. Part IV examines how and when bias can be introduced into mHealth interventions.

Part V provides a recommended roadmap of inquiry for developers and others involved in mHealth to identify and mitigate bias. Part VI is a review of areas for future research, and Part

VII is a brief conclusion.