Madness project nexus 2 ai9/3/2023 To address these concerns, I offer five steps that need to be taken to encourage responsible research and innovation. Prepandemic concerns that data-driven innovations may function to reinforce entrenched dynamics of societal inequity have likewise intensified given the disparate impact of the virus on vulnerable social groups and the life-and-death consequences of biased and discriminatory public health outcomes. Moreover, societally impactful interventions like digital contact tracing are raising fears of ‘surveillance creep’ and are challenging widely held commitments to privacy, autonomy, and civil liberties. The need for researchers to act quickly and globally in tackling SARS-CoV-2 demands unprecedented practices of open research and responsible data sharing at a time when innovation ecosystems are hobbled by proprietary protectionism, inequality, and a lack of public trust. This wide-reaching scientific capacity, however, also raises a diverse array of ethical challenges. ![]() The versatility of AI/ML technologies enables scientists and technologists to address an impressively broad range of biomedical, epidemiological, and socioeconomic challenges. ![]() Innovations in data science and artificial intelligence/machine learning (AI/ML) have a central role to play in supporting global efforts to combat COVID-19.
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