Diseases, treatments and drugs affect people differently according to factors such as race, ethnicity, gender or age, meaning these data gaps in research drastically limit our knowledge to effectively diagnose and treat disease. In the age of digital health, the data-gap can no longer be overlooked if we are to avoid exacerbating existing health inequalities.
At BenevolentAI, we launched an internal initiative to address this challenge, raise awareness and brainstorm possible solutions to the data diversity problem. We then broadened our scope by engaging with the wider scientific and research community.
During our inaugural event, we invited a panel of experts to discuss the problem of diversity in medical data, and then invited our audience to participate in an interactive workshop to brainstorm holistic and concrete solutions:
