Overcoming Digital Gravity when using AI in Public Health Decisions

2021/11/05 by Sekou L. Remy, Aisha Walcott-Bryant, Remy, Sekou L +7
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Big Data Technologies and Applications #Cognitive Science and Mapping #FOS: Computer and information sciences #Leadership, Behavior, and Decision-Making Studies

paper · pdf · doi:10.48550/arxiv.2111.07779

openalex publication_date 2021/11/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In popular usage, Data Gravity refers to the ability of a body of data to attract applications, services and other data. In this work we introduce a broader concept, "Digital Gravity" which includes not just data, but other elements of the AI/ML workflow. This concept is born out of our recent experiences in developing and deploying an AI-based decision support platform intended for use in a public health context. In addition to data, examples of additional considerations are compute (infrastructure and software), DevSecOps (personnel and practices), algorithms/programs, control planes, middleware (considered separately from programs), and even companies/service providers. We discuss the impact of Digital Gravity on the pathway to adoption and suggest preliminary approaches to conceptualize and mitigate the friction caused by it.

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