The COVID-19 pandemic has forced the world to critically evaluate the ways in which state-of-the-art technology, and in particular Artificial Intelligence (AI), can be leveraged to dampen the impact of current and future threats. While AI is in our name, we are dedicated to examine many technologies involving intelligent machines, optimization algorithms, computer simulation, and other tools. The Rutgers AI & Pandemics Initiative is organized is organized around a transdisciplinary group of faculty including over 30 faculty members from Public Health, Psychiatry, the Cancer Institute of NJ, the DIMACS Center, The Rutgers Center for Cognitive Science, Computer Science, Mathematics, Statistics, Engineering, Law, Business, Library and Information Science, Urban Planning and Public Policy, Philosophy, English, Institutes related to homeland security and secure communities, and others.

The group’s work is organized around three questions:

(1) How can AI help in the current pandemic?

(2) How can AI help prevent, predict, and mitigate future pandemics?

(3) What ethical issues arise from the application of AI to pandemics?

AI technologies are proposed and deployed to combat COVID-19, including disinfecting robots, self-driving vehicles for deliveries, face recognition to identify infected contacts, drones to enforce quarantines, machine learning for drug discovery, and more. Such automation benefits society overall, while raising legitimate concerns about loss of privacy and diminished human rights that extend past the emergency. The Initiative brings together technologists, who can develop tools that can help mitigate effects of pandemics, with ethicists and health professionals who will evaluate the ethical ramifications and help guide the application of the corresponding technology. This group will serve as a broad umbrella of researchers addressing key issues related to AI and pandemics. Examples of such issues are: (1) contactless production and delivery, (2) tele-medicine and patient care, (3) privacy-conscious surveillance, contact tracing and disease testing, (4) redesign of COVID-19 supply chains, (5) metrics of physical and mental health under social distancing, (6) early warning of new disease outbreaks from multi-modal data, (7) semi-autonomous disinfection and contaminated waste management.

In the short-term, we have formed smaller, targeted teams (working groups) laying the foundations for the proposed transdisciplinary effort, while enhancing a transdisciplinary dialogue about all of these issues and preparing for groups to apply for larger external funding awards.