AI and Coronavirus

What this episode covers

Is there an upside to the coronavirus? Nope. But the outbreak did show how AI can be used to predict and accurately track a pandemic. From Short and Sweet AI, I’m Dr. Peper, and today I’m talking about what everyone is talking about, the coronavirus or COVID 19. There are so many ways AI impacts the cornavirus outbreak. Chinese drones are disinfecting public areas and track people who don’t adhere to quarantine. Robots decontaminate hospital rooms. Self-driving cars in China deliver supplies to medical workers. Facial recognition cameras search for people not wearing their mandated face mask. Infrared temperature scanners detect fevers in large groups of people. Doctors use AI software to find evidence of coronavirus in lung scans from patients who are ill. Think about what happened with the SARS virus in 2003 and compare that to the coronavirus today. What you realize is over the last two decades AI has really advanced how we respond to pandemics. Early Prediction with AI Early detection means earlier disease containment. And AI can do it faster. Right from the beginning an artificial intelligence company sounded the alarm on the coronavirus. A Canadian company BlueDot used AI powered algorithms to analyze information from many different sources. They were able to identify places were there were outbreaks of diseases and forecast how they spread. The company sent out warnings to it’s clients to avoid Wuhan on December 31, 2019. The World Health Organization sent out a public warning on January 9, 2020, not until 10 days later. 100,00 reports /day BlueDot used natural language processing and machine learning to analyze large amounts of data. The company uses an automated infectious disease surveillance program. The algorithm sifts through foreign language news reports, animal and plant disease publications, new releases from government and public health departments and much, much more. The data is vast: 100,00 new reports in 65 languages a day. BlueDot’s algorithm doesn’t use social media data because the company says it’s too messy. Finding signs of the virus in a vast soup of rumors, posts about ordinary cold and flu symptoms and lots of speculation, requires as yet unavailable training sets for the algorithms. But BlueDot does use some unexpected sources such as global airline ticketing data. Using this information, the Bluedot physician and programmers correctly predicted in the first few days the virus would jump from Wuhan to Seoul, Taipei, then Tokyo. Humans Validate Conclusions Bluedot highlights how the best use of AI is to augment human understanding. After the data sifting is finished, epidemiologists take over to make sure, from a scientific stand point, the conclusions from the data make sense. As blueDot’s founder Kamran Khan points out “What we have done is use natural language processing and machine learning to train this engine to recognize whether this is an outbreak of anthrax in Mongolia versus an reunion of the heavy metal band Anthrax”. But final supervision requires human input to validate the AI’s findings. Information from AI algorithms need humans to put it in context to take the next step. The field of artificial intelligence needs people who can operate at the intersection of AI and biology. It’s not enough to be an AI engineer. What’s needed is someone who can understand biology well enough to apply what AI comes up with. Augmented Intelligence The use of AI in prediciting the coronavirus pandemic shows us what many experts in artificial intelligence alr...