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Many widely used health algorithms have been shown to encode and reinforce racial health inequities, prioritizing the needs of white patients over those of patients of color. Because automated systems are becoming so crucial to access to health, researchers in the field of artificial intelligence must become actively anti-racist. Here we list some concrete steps to enable anti-racist practices in medical research and practice.
Being a parent scientist can feel like a catch-22, feeling guilty for both the time spent away from the children and the time spent away from the bench. Embracing healthy boundaries can be liberating but will only go so far if childcare remains unaffordable.
The rapid rollout of digital health approaches in the ongoing global COVID-19 pandemic has neglected to prioritize data privacy and is a missed opportunity for building users’ trust in these technologies for future outbreaks and quotidian healthcare.
Every crisis is a strong call to mobilize the entire research community to respond. The COVID-19 pandemic is no exception. Researchers, universities, funders, philanthropies, journals, and journalists have all pivoted, en masse, to COVID-19. Everyone is ‘Covidized’, and it should worry us.
Only 6 months after the first identification of the causative coronavirus, vaccine candidates against COVID-19 are already in clinical trials. The secret weapon behind the speed of development? Computational immunology.
Racism is a social determinant of health and negatively affects health outcomes. This Comment describes steps to take toward achieving equity and racial justice in medical training and addressing racism in clinical settings.