AI identified coronavirus before it spread. Here's how it can contain future contagious viruses

Tech and medical experts say artificial-intelligence technology holds the key to preventing potential virus pandemics and outbreaks like novel coronavirus.

Researchers at the Toronto-based AI platform BlueDot identified COVID-19 on Dec. 31 just hours after local officials in Wuhan, China, reported the city's first diagnoses, but it took the Chinese government weeks to make an official announcement.

"Coronavirus is a huge wake-up call for us in a positive way because of how important AI technology is and how medicine should embrace AI technology so it can recognize viruses like [COVID-19]," Sergey Young, founder of a $100 million investment fund dedicated to making longevity affordable and accessible called the Longevity Vision Fund, told FOX Business.

"It's also a negative wake-up call because we are still human beings with a lack of trust in AI, and human beings have a weakness in terms of how we respond to AI," Young added.

Investors, tech experts and health care experts alike are starting to become more comfortable with the integration of AI in the medical field, including its use in identifying diseases that have the potential to become widespread. AI "is a huge search machine that searches the world's data," Young said.

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Imagine the world's biggest library. AI uses algorithms that could scan through all the books in that library in a fraction of the time that humans would be able to. For example, BlueDot's AI technology was able to identify coronavirus in just a day when its technology picked up signs of an “unusual pneumonia” coming from a market in Wuhan on Dec. 30, CNBC Make It reported on Wednesday.

BlueDot founder and CEO Kamran Khan, who worked as an epidemiologist and physician treating patients in Toronto during the 2003 SARS outbreak, said the purpose of AI and companies that use it like BlueDot is to "spread knowledge faster than the diseases spread themselves."

It would have been impossible for humans to come to the same conclusions about COVID-19 in December without AI, which partners with big tech and big pharma to search millions and billions of databases for keywords on social media, financial transactions, hospital data, people reporting unusual trends, travel activity and a number of other data to make connections between two unlikely factors, Young said.

COVID-19 has since spread to 85 countries outside of China with 95,333 confirmed cases within and outside the origin country. The virus has killed 3,015 in China and 267 elsewhere as of March 5, according to data from the World Health Organization.

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Despite knowing about the virus weeks before it began to rapidly spread, officials refrained from spreading information Young says the issue has to do with human trust in technology and AI, and AI's ability to connect dots that humans likely would not.

"Where AI is similar to human intelligence is that it tries to look for all relevant data and analyze it," Young said. "Where AI is unlike human intelligence is its enormous capacity to search, analyze and link data, and often come up with very unusual correlations. AI will not be scared to present unusual data correlations at the risk of sounding stupid" like humans would.

"The overall issue is two problems. One: We live in a world of oversupply of information. There is so much noise that we need AI to handle it. It is impossible for WHO and other world organizations to see abnormal activity coming from one specific direction," Young explained.

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"Two: I think we missed the point in the development of global health crisis. We didn't realize that like technology, viruses do not have borders. If people think it's just a China problem, that will create more problems," Young said. "The level of globalization today, not just in technology but human-to-human interactions," continues to develop.

Young and Kahn both said federal organizations like WHO that help fight infectious disease are too reliant on old systems and traditional medical research practices.

"What I learned during SARS is, let’s not get caught flatfooted, let’s anticipate rather than react," Kahn told CNBC. "If we rely on government agencies to report information about infectious disease activity, we may not always get that in the most timely way or as quickly as we would like."

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