This crisis, he feared, was creating unprecedented dangers of species-level self-destruction ranging from geoengineering and unbridled automation to nuclear holocaust. Von Neumann, then stricken with terminal cancer, wrote about what he called “the maturing crisis of technology,” a situation in which the global effects of accelerating technological advancement were outpacing the development of ethical and political self-understandings that were capable of responsibly managing such an explosion of innovation.

In June 1955, the great Hungarian mathematician and polymath John Von Neumann published a popular essay entitled “Can we survive technology?” (Von Neumann, 1955). Keywords: COVID-19, AI ethics, responsible research and innovation, open science, digital contact tracing, public trust When taken from the start, these steps will not only enhance the capacity of innovators to tackle COVID-19 responsibly, they will, more broadly, help to better equip the data science and AI/ML community to cope with future pandemics and to support a more humane, rational, and just society. These provide a practice-based path to responsible AI/ML design and discovery centered on open, accountable, equitable, and democratically governed processes and products. 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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