インシデント 204の引用情報

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.
推定: Sangfor Technologiesが開発し、Zhihuが提供したAIシステムで、Zhihu employees Chinese tech workersに影響を与えた

インシデントのステータス

インシデントID
204
レポート数
4
インシデント発生日
2022-02-11
エディタ
Khoa Lam
Zhihu Denies Using Behavior Perception System to Monitor Employees
pandaily.com · 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
supchina.com · 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
min.news · 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
min.news · 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…

バリアント

「バリアント」は既存のAIインシデントと同じ原因要素を共有し、同様な被害を引き起こし、同じ知的システムを含んだインシデントです。バリアントは完全に独立したインシデントとしてインデックスするのではなく、データベースに最初に投稿された同様なインシデントの元にインシデントのバリエーションとして一覧します。インシデントデータベースの他の投稿タイプとは違い、バリアントではインシデントデータベース以外の根拠のレポートは要求されません。詳細についてはこの研究論文を参照してください