As COVID-19, the disease caused by the novel coronavirus, continues to exponentially spread within the United States and globally, artificial intelligence has become one of the first lines of defense in the pandemic. The unprecedented pace of disease spread and data collection is challenging the medical research community to keep up with COVID-19. In a global pandemic such as this one, technology, artificial intelligence, and data science have become critical in helping societies effectively deal with the outbreak.
If properly utilized, AI can help government, industry, academia, and civil society process and utilize data and information relevant to these fields to more effectively combat the virus. Fighting COVID-19 requires extensive research in areas like bioinformatics, epidemiology, and molecular modeling to understand the threat we’re facing and form strategies to address it. The use of AI to do research in these areas and counter the pandemic demands massive computational capacity and data. Recently, the White House’s Office of Science and Technology Policy requested the creation of an open dataset of over 29,000 scientific articles published in journals and in publicly shared research papers. OSTP also announced the COVID-19 High Performance Computing Consortium, bringing together the federal government, industry, and academic leaders to provide access to the world’s most powerful high-performance computing resources in support of COVID-19 research.
Hospitals are using AI to help screen and triage patients and identify those most likely to develop severe symptoms. Among the most urgent questions hospitals are facing right now is which of their COVID-19 patients are going to get worse, and how quickly will that happen? Researchers are racing to develop and validate predictive models that can answer those questions as rapidly as possible. For example, researchers from New York University, Columbia University, and two hospitals in Wenzhou, China, developed and just published an AI tool to predict whether patients will go on to develop acute respiratory distress syndrome, or ARDS, a potentially deadly accumulation of fluid in the lungs. The new AI tool found that changes in three surprise indicators were most accurately predictive of subsequent, severe disease. Together with other factors, the team reported being able to predict risk of ARDS with up to 80% accuracy.
AI is playing an important role in rapidly developing a vaccine for the coronavirus, our best long-term hope for mitigating the devastating health and economic consequences of COVID-19. Mining data in many prior studies of related coronaviruses using AI has resulted in scientists understanding the coronavirus viral protein structures, necessary knowledge for developing a vaccine. Several COVID-19 vaccine candidates have recently been announced; one already in Phase I clinical trials for safety, and others are due to start clinical trials the early fall 2020. The accelerated timeline of vaccine development and testing has been possible only through expeditiously sharing data sets using AI in public–private partnerships.
Data sets collected by social media apps on smartphones have proven to be a critical tool for monitoring and responding to the rapid spread of COVID-19 in other countries such as South Korea and Italy. In recent days, U.S. technology giants announced that they will be using their massive collections of mobile location data to provide tools specific to the fight against coronavirus. One tool creates reports on the degree to which locales are abiding by social-distancing by measuring how much foot traffic has increased or declined to certain destinations. Other tools reveal the probability that people in one area will come into contact with people in another area, helping predict where cases of COVID-19 may appear next. AI makes this all possible. Technology firms state that their tools use aggregated and anonymized information, and that additional steps will be taken to obscure people’s identities and reduce the risk that anyone could be re-identified.
In this new age of the COVID-19 crisis, the beneficial technological abilities of AI offer a myriad of methods to track, predict and treat COVID-19. Embracing surveillance systems to track individuals’ movement and access sensitive health information seems to be most beneficial now for public health purposes now. But the surveillance efforts threaten to alter the precarious balance between public safety and personal health privacy.
The United States does not have a comprehensive privacy law to protect Americans’ personal information. Instead, we have a patchwork of federal, state, and local laws that regulate specific sectors or data sets like health records if they are held by certain entities. This has led to the explosion of patient data being accessed in potentially exploitive data-driven behaviors in a vast unregulated space. The need for some type of guardrails in big data use and patient health privacy is pressing. The Senate Commerce Committee recently held one of the first-ever “paper hearings” in the midst of this pandemic on data’s role in the war on the coronavirus and the privacy concerns that it may raise.
Many of these health data privacy questions amidst the current status of COVID-19 in the United States, the current use of big data in population health management, and how AI is incorporated into disaster and emergency management will be discussed and answered In BPC’s upcoming April 22 webinar about AI and Pandemics. Our speakers will be addressing the pressing question of what safeguards will protect our personal health information during the immediate COVID-19 crisis and the aftermath.
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