Medical and Public Health Algorithms as Colonizing Tools

• In Event: The Social Life of Algorithms - II

Abstract

Algorithms are ubiquitous in medicine and public health, especially in developed counties and in the management of epidemics. These are not software programs but rather decision making codes programmed in healthcare practitioners. When an individual arrives to the emergency room with chest pain, a team of professionals follows an algorithm that outlines every test and intervention. Known as “best practices,” these guides provide standardized management, and provide legal protection for clinicians and hospitals. Faced with a new outbreak, such as the recent Ebola and Zika epidemics, public health officials (based in places like Washington DC and Geneva) deploy a management algorithm that defines what cases are, how they are handled and by whom, what is the treatment, and how it will be contained. In both cases, the clinical and the epidemiological, these algorithms create the illusion of objective processes that will provide the best care and protection for all populations, based solely on up-to-date scientific research. But coded into these algorithmic pathways there is a medical colonization process that influences decisions based on gender, race, ethnicity, and location. Most hospital treatment guides have been constructed on clinical data obtained from white American males. Epidemiologic guidelines are written in institutions based in developed countries, far from where they are deployed and with disregard of local cultural and socio-economic realities.
This paper explores how medical and public health algorithms hide, under the semblance of homogeneity and objectivity, discriminatory practices; and how these processes can be addressed as a decolonizing project.

Author

• Jorge Benavides-Rawson, George Washington University