Incident 204: A Chinese Tech Worker at Zhihu Fired Allegedly via a Resignation Risk Prediction Algorithm

Description: The firing of an employee at Zhihu, a large Q&A platform in China, was allegedly caused by the use of a behavioral perception algorithm which claimed to predict a worker’s resignation risk using their online footprints, such as browsing history and internal communication.


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Alleged: Sangfor Technologies developed an AI system deployed by Zhihu, which harmed Zhihu employees and Chinese tech workers.

Incident Stats

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Khoa Lam
Zhihu Denies Using Behavior Perception System to Monitor Employees · 2022

A picture of a system that monitors employees’ intentions of leaving the company has been circulating online. News emerged that Zhihu, a Chinese Q&A community, has used the system to monitor employee’s visits to job-seeking websites and the…

Chinese tech workers outraged by surveillance tool that flags employees who look likely to quit · 2022

A surveillance system developed by a Shenzhen-based software firm can identify workers who are planning to quit by spying on their online activities. Outrage at the dystopian tool from Chinese social media users resulted in the firm taking …

Zhihu said that it has never installed a perception system to monitor employee behavior! Sangfor related cases are no longer visible · 2022

Recently, a system that can monitor employee turnover tendency and sabotage has sparked heated discussions. Zhihu is accused of using the system to monitor employee turnover intention. On February 14, Zhihu told Nandu reporters that Zhihu h…

"Monitoring the tendency of employees to switch jobs" caused controversy, Sangfor urgently removed the product from the shelves, and the lawyer said that the employee was not informed of the suspected violation of the law · 2022

Along with Zhihu's layoffs, a system that claims to be able to monitor employee turnover tendencies and sabotage has aroused public attention and brought the listed company Sangfor and its partners to the forefront.

A few days ago, under th…


A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.