Genetic tests help us negotiate the uncertainty posed by a body’s inherited genetic legacy. In the United States, it has never before been more affordable and available. On what behind-the-scenes rhetorical tactics do genetic scientists and testing corporations rely, though? How do ancestries, geographies, environments, politics, economies, and technologies intra-act in the genetic backstage? This chapter deploys Adele Clarke’s situational analysis method in order to unearth how two genetic testing companies (23andMe, Inc. and Color Genomics, Inc.) employ next-generation genetic sequencing. Analyses reveal that genetic scientists enact a host of computational cuts that affect how genetic data are interpreted, how mutations are defined, and how disease risk is calculated. By mobilizing the explanatory power of Susan Leigh Star’s boundary infrastructure, the chapter describes how the choices a laboratory makes about which reference materials, analytic procedures, and algorithms they use ultimately render different results. The chapter concludes by discussing the ideological, economic, and algorithmic machines—or shadow work—that help to navigate genetic uncertainty. Readers are encouraged to interrogate politicized promises of a more personalized and precise approach to medical practice and to take care when choosing to purchase, use, and make medical decisions based on results from genetic tests.
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