Where was AI During the COVID-19 Pandemic? And what About the Next One?

July 30, 2020

There has been a debate going on about how much AI has contributed to combatting COVID-19, in terms of prevention, treatment or the search for a vaccine. While the work being conducted by biopharma researchers and drug manufacturers has taken center stage – and rightfully so – AI has quietly worked behind the scenes, most notably in finding and predicting the pandemic in the first place.

For example, Lawrence Berkeley National Lab in California is using an AI program, covidscholar.com, to sort through volumes of available research for any relevant data that could be helpful for treating patients and developing a vaccine. Researchers at Flinders University used AI to analyze the virus and how it infects cells, so that a vaccine could block that process. And, Northwestern University is using an AI program to rate and prioritize research in order to determine which programs should receive funding and fast-track their status for vaccine development.

It’s not just smart apps working on the front lines, but also chatbots, which are providing vital information to the public without straining staff resources. Healthcare facilities are turning to chatbots or conversational AI, which uses natural language processing to simulate human conversation. Providence St. Joseph Health in Washington State implemented a Coronavirus Assessment Tool online to educate the public about the potential symptoms of the virus and help people figure out if they should be seen by a healthcare professional. In its first day alone, more than 500,000 people used the chatbot. It not only gave people critical and immediate access to information, but it also freed up medical staff to focus on treating their patients.

AI is certainly not a panacea to magically solve every problem. Its purpose is to augment rather than replace human intelligence, and it depends on humans to provide the right conditions in order for it to be effective. First of all, AI needs to have a huge volume of good data. Since AI learns based on the data it is provided, the more reliable data it has, the more accurate it can be in identifying patterns that can lead to insights and innovation.

Additionally, this data must correlate to the problem that the AI program is trying to solve. Unfortunately, much of the data that AI programs need to address COVID-19 issues is just not available yet. Without the availability of this data, it is difficult, for example, for AI to find potential matches between symptoms and drugs for treatment.

One of the key factors contributing to the lack of data is that the information is unfolding in real time, and everyone is scrambling to come up with vaccines and treatments in the midst of the pandemic; it’s like trying to build a plane while flying it. Another roadblock is that much of the data that is needed is siloed within different labs and offices across countries, although efforts are underway to centralize this data.

Putting AI into Action in the Race to Treat COVID-19

Despite the challenges, AI is playing an important supporting role in addressing COVID-19, but it requires a collaborative and standardized approach that goes beyond private and public interests to succeed. Here are four key steps that can be taken to ensure that AI lives up to its full potential in this pandemic and future crises:

  • Carve out the appropriate role for AI and plan ahead. Any AI project requires a methodical approach despite the urgency. It’s important to leverage the strengths of AI, identify the problems you want it to solve, the type data that is required, and how that data will be collected.
  • Create an international AI taskforce. This should include representatives from as many countries as possible, so that for this pandemic or other crises that emerge, we can be prepared to address them collectively. We need to be able to identify and collect the right data quickly, and have consistent processes and procedures in place to do so.
  • Establish an international database. It should include all the data from around the world, which becomes available to everyone, in much the same way that the gene sequencing of the virus was shared globally. This is a time for collaboration, not competition, for the greater good. With the COVID-19 pandemic, we can see why diverse data from everywhere is critical. For example, Sweden took a very different approach than other countries regarding social distancing and quarantining. Their data will provide critical information that may not be available elsewhere.
  • Ease up a bit on privacy. There has to be privacy tradeoffs when it comes to collecting data. While privacy is certainly important, when it comes to combating a pandemic that can mean life or death for hundreds of thousands of people worldwide, it makes sense to ease up on some privacy concerns for the greater good, while working to find a good balance between privacy and safety.

As we’ve heard throughout the COVID-19 pandemic, data needs to drive the bus when it comes to addressing the many problems that have emerged. While AI certainly does not hold the cure for COVID-19, it can play a critical role in helping us turn data-driven insights into action. Yet, it requires global collaboration among businesses and governments, an understanding of its possibilities and limitations, and bright minds to guide its proper use today and into the future.

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