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Explainers
TechPolicy

Explainer | What is facial recognition, and why is it more relevant than ever during the coronavirus pandemic?

  • Facial recognition software has been increasingly deployed by countries to secure access and improve surveillance, especially during the pandemic
  • But the technology is controversial, not just because data leaks are common, but also because of its potential to exacerbate racial or gender biases

Reading Time:7 minutes
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A man has his temperature measured at the entrance to an office building by an AI computer called ‘Smart AI Epidemic Prevention’ made by the company SenseTime, in Shenzhen, China in March 2020. Photo: EPA-EFE
Melissa Zhu
China may already have been home to most of the world’s most monitored cities before the coronavirus pandemic, but surveillance technologies, and in particular facial recognition software, have seen a new surge in popularity as governments scramble for ways to identify potential cases and maintain security while reducing human-to-human contact.
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Around the world, the artificial intelligence-based technology has been increasingly deployed by law enforcement and border control to secure access and improve surveillance.

But this is also not without controversy. In the wake of the Black Lives Matter protests that swept the US earlier this year, several companies including Microsoft, IBM and Amazon announced they would either pause selling police their facial recognition systems or stop producing them entirely.

Here’s a summary of what we know about facial recognition technology.

How does facial recognition work?

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Facial recognition systems involve the identification of people from a database of images, including still photographs and video. Deep learning – a subset of artificial intelligence – speeds up a system’s face-scanning capabilities, as it learns more about the data it is processing. Such systems require vast amounts of information to become faster and more accurate.

Essentially, these systems generate a so-called “unique face print” for each subject by reading and measuring dozens to thousands of “nodal points”, including the distance between eyes, the width of a person’s nose and depth of the eye socket. With a network of surveillance cameras, recognition systems process a wider range of features, including subjects’ height, age and colour of clothes.

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