As covid-19 spreads across the globe taking a toll on human life, wreaking havoc on healthcare systems, and throwing financial markets into turmoil, governments and industry are doing everything they can to help slow the spread of the virus and “flatten the curve” of the pandemic.
Over the past few weeks, we’ve seen that Artificial Intelligence can play a supporting role in helping control the pandemic. These are some of the ways AI technology is being deployed to help curtail the devastating impact of the virus.
As a content moderation tool
Even before Covid-19 became part of our daily vernacular, platforms such as Amazon, Facebook, Google, YouTube, and Twitter have faced serious issues in properly automating listening and content moderation tools. Ultimately these platforms have struggled to keep pace with the overwhelming flood of content posted, advertisements placed and uploaded every day and require human adjudication of complaints.
This struggle has been further exacerbated as the COVID-19 outbreak has shuttered offices and forced employees to work remotely. However, privacy concerns mean that content moderation isn’t something that can be easily and securely managed via remote means. And yet, during a time when the threat of medical misinformation is dire, these platforms need moderation more than ever.
Reliance on human content moderators is increasing as platform providers have looked to AI to pick up the slack. Some reports indicate that the technology isn’t quite ready to meet the moment, and platforms are warning users to expect mistakes in these early stages.
As a scientific data mining tool
As the pandemic has spread globally, there has been an influx of medical research published about Covid-19. While such a large volume of research is a potential boon to our understanding of how to control and treat the virus, it also presents Big Data challenges. So much research is difficult to distill and, therefore, can be difficult to draw conclusions from.
Researchers are turning to AI to help them better mine data for insights. This same technique has been used previously to identify a possible use case for magnesium in the treatment of migraines. According to an article in Wired, “The hope is that AI will accelerate insights into the novel coronavirus by finding more subtle connections across more data.”
In service of pandemic prediction
The earlier interventions are taken to stem the tide of a pandemic, the more effective they are at slowing and stopping its spread. This is why early identification of a crisis in development is so essential.
Companies like BlueDot and Metabiota are actively using AI to predict outbreaks of infectious diseases. There are reports that these companies used machine learning to predict the Coronavirus outbreak after picking up spikes in the number of pneumonia cases in Wuhan, China.
To diagnose patients
As cases of coronavirus spiraled in China, hospitals there have leaned on AI to help them more quickly diagnose suspected cases. According to Wired, with hospitals stretched to the limit by the scale of the pandemic, AI has been deployed to “detect visual signs of the pneumonia associated with Covid-19 on images from lung CT scans.” Though the AI technology alone can’t confirm cases of COVID-19, it does help reduce the burden on healthcare providers and direct limited resources by identifying the likeliest cases.
To track potentially infected persons
Not all uses of AI during the pandemic are without controversy. There are reports that facial recognition and geolocation technology is being used in China to track individuals who may have come in contact with infected persons. These tools can also be used to track compliance with self-isolation and quarantine orders, though whether or not democratic governments choose to deploy such tools despite privacy concerns remains to be seen.
Never has the potential of AI been more clear than in this particular moment of crisis. During a pandemic, when time is of the essence, AI can help stem the tide of the virus by predicting outbreaks, serving as a triage tool, and helping researchers mine insights from huge swaths of data.
