Abstract
Big data is both a product and a function of technology and the ever-growing analytic and computational power. The potential impact of big data in health care innovation cannot be ignored. The technology-mediated transformative potential of big data is taking place within the context of historical inequities in health and health care. Although big data analytics, properly applied, hold great potential to target inequities and reduce disparities, we believe that the realization of this potential requires us to explicitly address concerns of fairness, equity, and transparency in the development of big data tools. To mitigate potential sources of bias and inequity in algorithmic decision-making, a multipronged and interdisciplinary approach is required, combining insights from data scientists and domain experts to design algorithmic decision-making approaches that explicitly account and correct for these issues.
Highlights
Big data is both a product and a function of technology and the ever-growing analytic and computational power
Big data holds great potential to target inequities and reduce disparities, machine learning algorithms generated from big data have the potential to exacerbate existing disparities and create new ones
Big data techniques such as machine learning and artificial intelligence may not reflect the diversity of perspectives and backgrounds needed to assure fairness and reduce bias in the algorithms they create
Summary
Big data is both a product and a function of technology and the ever-growing analytic and computational power. Differential access to technology threatens the representativeness of the data that populate our big data models and inform the resultant algorithms, and undermines the potential of big data to improve the lives of the most vulnerable people.3,4
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