Machine learning thrives on data, but information about the novel coronavirus and the illness it produces has been either thin or hard to access. Now researchers are pooling resources to share everything we do know.

What’s new: The White House and researchers from top U.S. AI and health institutions launched CORD-19, a free, machine-readable dataset of nearly 30,000 scholarly articles on the coronavirus. Kaggle is hosting a competition for text- and data-mining tools that sift this mountain of information for valuable insights.

Promising directions: Lack of data so far has limited AI’s usefulness in combating this outbreak, but stronger data-collection efforts could prove decisive in the next, according to MIT Technology Review. Author Will Douglas Heaven describes three areas to focus on:

  • Prediction: Health surveillance companies spotted Covid-19 in late December by parsing news reports, social media, and official statements, but predicting how the epidemic will spread is harder. AI companies could do more if they were allowed access to patient records, but that would require working through thorny privacy issues. The U.S. recently finalized new rules for giving patients more control over their health data. What’s missing is an option for patients to share their data securely with researchers.
  • Diagnosis: A number of tools analyze scans of patients’ lungs to detect coronavirus infections. These technologies can’t see the virus itself, however, only the damage it has caused — and by the time such damage is visible, the illness may have progressed too far to be treated easily. Small data techniques might do better, pending further research.
  • Treatment: AI could accelerate discovery of new drugs and vaccines, though that will take time. DeepMind used its AlphaFold model to predict protein structures associated with the virus. If they’re verified, the information could aid efforts to develop treatments. Generative algorithms can model millions of molecules and sift through them to find potentially useful ones. More data on the disease’s evolution could accelerate that effort.

Behind the news: AI spotted the disease early, but humans still beat it to the punch. At least one Chinese doctor posted his concerns about what came to be known as Covid-19 on a WeChat group before AI health monitors issued their alerts. He later died of the virus.

Why it matters: AI has great potential to combat epidemics, and hopeful news reports bring attention to and support for the field. The community must work diligently while taking care not to encourage wildly inflated expectations and false hopes.

We’re thinking: Covid-19 isn’t the first pandemic, and sadly it won’t be the last. The AI community’s efforts to fight this virus will prove critical when the next one emerges. And there’s plenty we can do outside the medical sphere: Machine learning can help manage critical resources, coordinate responses, and optimize logistics. At this moment of international crisis, we face a common foe that is bigger than any of us, and we’re gratified to see so many AI developers eager to pitch in.


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