Workplace health surveillance and COVID-19: algorithmic health discrimination and cancer survivors

Abstract

Purpose: This article examines ways COVID-19 health surveillance and algorithmic decision-making ("ADM") are creating and exacerbating workplace inequalities that impact post-treatment cancer survivors. Cancer survivors' ability to exercise their right to work often is limited by prejudice and health concerns. While cancer survivors can ostensibly elect not to disclose to their employers when they are receiving treatments or if they have a history of treatment, the use of ADM increases the chances that employers will learn of their situation regardless of their preferences. Moreover, absent significant change, inequalities may persist or even expand.

Methods: We analyze how COVID-19 health surveillance is creating an unprecedented amount of health data on all people. These data are increasingly collected and used by employers as part of COVID-19 regulatory interventions.

Results: The increase in data, combined with the health and economic crisis, means algorithm-driven health inequalities will be experienced by a larger percentage of the population. Post-treatment cancer survivors, as for people with disabilities generally, are at greater risk of experiencing negative outcomes from algorithmic health discrimination.

Conclusions: Updated and revised workplace policy and practice requirements, as well as collaboration across impacted groups, are critical in helping to control the inequalities that flow from the interaction between COVID-19, ADM, and the experience of cancer survivorship in the workplace.

Implications for cancer survivors: The interaction among COVID-19, health surveillance, and ADM increases exposure to algorithmic health discrimination in the workplace.

Keywords: Algorithmic health discrimination; COVID-19; Cancer; Chronic illness; Disability; Health surveillance.