Chinese Workers Forced to Build AI Copies of Themselves Before Quitting
As Chinese companies expand their use of internal artificial intelligence, some employees are now required to create digital versions of themselves before leaving their jobs.
One former Baidu employee described the process: he had to build an AI replica of his own knowledge and decision-making patterns as part of his exit procedure. This digital twin is designed to continue performing certain tasks after the worker has left, ensuring the company retains key expertise [167915].
The practice reflects a broader push by Chinese firms to integrate artificial intelligence into their operations, even at the cost of asking departing staff to train their replacements—machines. While companies see this as a way to preserve institutional knowledge, critics argue it raises questions about labor rights and the value of human experience [167915].
Meanwhile, in China's remote hinterlands, thousands of rural workers are labeling data to train AI models. This work has become a key poverty-alleviation tool. These workers sit in computer rooms, tagging images and text to help AI systems recognize objects and language, turning less-developed regions into hubs for the country's AI industry [167954].
The push for AI integration also extends to national strategy. China is pushing a rapid "AI Plus" revolution in electronic warfare, aiming to redefine how militaries communicate, jam, and control the electromagnetic spectrum, according to industry experts [157704].
However, the technology still has critical flaws. A Chinese user’s chat log showing an AI assistant confidently inventing fake flight refund details has sparked a wave of online spoofs. The trend, known as “AI hallucination,” is growing in the country. In the screenshots, the AI provided numerous inaccuracies, including a false refund amount and incorrect policy. Users are now sharing their own examples of AI making up information, highlighting a key flaw in the technology: it can sound certain while being completely wrong [167920].