HEALTH-DATA POVERTY, RACIAL DISCRIMINATION AND ARTIFICIAL INTELLIGENCE: DIVERSITY AND INCLUSION IN CLINICAL TRIALS

Abstract

The use of biased artificial intelligence systems in the healthcare field involves the risk to crystallize and exacerbate existing health inequalities. The discriminatory functioning of the algorithm arises, in part, because of the use of an inadequate dataset. The study aims to explore the correlation between the low participation of ethno-racial minorities in clinical trials and the inability of these subjects - already in a condition of subalternity - to benefit from data-driven innovation developed, also, with data from such clinical trial. Moving from the analysis of US context, the paper will highlight the importance of a diversity and inclusion approach in the selection of the sample and in the conduction of the clinical trial, in order to promote equal access to healthcare even - and especially - when this is provided through the use of AI systems.