Data is increasingly important in planning and decision-making, but data can also be biased and shaped by our assumptions and gaps in knowledge. When this gap-filled data is plugged into algorithms, it can amplify existing forms of discrimination.
For example, the global HIV response is being undermined by the fact that many governments deny the existence of the key populations at greatest risk — gay men and other men who have sex with men, sex workers, drug users, and transgender people. Since no data is gathered about their needs, life-saving services are not funded, and the lack of data reinforces the denial. This creates a data paradox which can warp national health priorities and plans.
As this Tedx talk explains, stigma, discrimination and inequality are systematically creating invisibility which can keep marginalized, stigmatized groups uncounted and unserved. To break the vicious cycle of this data paradox, we have to change the power relationships that keep some groups hidden and on the margins.