A new report details the role of AI in China’s effort to fight the coronavirus.

What’s new: Researchers at Synced, a China-based AI publication, describe how nearly 90 machine learning products have contributed to the country’s pandemic response.

What it says: The report presents case studies in five areas: thermal imaging, medical imaging, epidemiology, contact tracing, and drug discovery. A few examples:

  • Infervision trained a computer vision system to detect signs of pneumonia on lung tissue shown in CT scans, helping to alleviate a shortage of human technicians typically needed to interpret this data.
  • Municipalities are using a language processing platform from Yidu Cloud to parse information from officials and health care systems, helping them track and predict the virus’ spread.
  • Guangdong Province uses MiningLamp Technology’s machine learning platform to trace people who have come in contact with Covid carriers.
  • An infrared sensor from Athena Security scans crowds for people running a fever, a common Covid-19 symptom. When it spots an overheated individual, it uses face identification to log their identity and status in the cloud.
  • Researchers developing vaccines are using Baidu’s AI-powered gene sequencing tool to decode the virus’ genetic structure rapidly.

Yes, but: Critics have pointed out shortcomings of machine learning in the fight against Covid-19 so far. In April, for example, two groups of researchers audited Covid-related machine learning models. They found bias in many systems for analyzing hospital admissions, diagnosis, imaging, and prognosis.

Why it matters: Not all AI-against-Covid initiatives will prove to be effective. Tracking the approaches underway is crucial to finding the ones that work.

We’re thinking: Artificial intelligence still needs to be complemented by human intelligence. Please wear a mask!


Subscribe to The Batch

Stay updated with weekly AI News and Insights delivered to your inbox