A Chinese court's ruling on Friday in the country's first case involving facial recognition has drawn widespread public attention.

In April 2019, Guo Bing, an associate professor of law at Zhejiang Sci-Tech University, had purchased an annual card for two persons at Hangzhou Safari Park, requiring verification of both persons' fingerprints before entering the park.

But the park later unilaterally replaced "fingerprint recognition" with "facial recognition" as the requirement for entering the park, earning Guo's dissatisfaction. The doctorate holder in law sued the park for breaking the contract with consumers and also asked them to delete his personal information and to compensate him.

Hangzhou Fuyang people's court ruled on Friday that the Hangzhou Safari Park's decision to collect individuals' facial features lacked legitimacy and the park should compensate Guo and also delete his personal information, especially facial features, from their database.

This is the first case involving the legality of collecting facial features in China.

With the rapid development of biological feature recognition and big data, facial recognition has become a convenient and accurate way to verify personal identity, apart from playing a key role in the prevention and control of the spread of the novel coronavirus.

But such widespread use of facial recognition technique has raised security concerns.

The abuse of facial recognition has become increasingly common nowadays. In the absence of specific laws and regulations on facial feature collection and recognition, many organizations illegally collect individuals' facial features. By collecting individuals' facial features on such a large scale, organizations such as the safari park are exposing individuals to great risks in the event of their personal biological features getting leaked.

The court's ruling effectively safeguards individuals' legal rights and interests, and hopefully the authorities will soon introduce sound laws and regulations for safeguarding individuals' personal biological feature information.