内容来源：https://techcrunch.com/2026/04/21/meta-will-record-employees-keystrokes-and-use-it-to-train-its-ai-models/

内容总结：

为提升人工智能模型性能，科技公司正不断拓展训练数据来源。近日有报道称，Meta公司计划采集员工日常工作时的鼠标移动轨迹、按键操作等行为数据，用于训练其AI模型。该公司表示，此举旨在通过真实人机交互数据提升AI助手的实用性，同时强调已建立数据保护机制，仅将信息用于特定模型训练。

行业观察显示，随着AI研发对数据需求持续增长，企业内部通讯记录、协作平台历史资料等正逐渐成为新的数据来源。这一趋势在推动技术发展的同时，也引发了关于数据隐私与企业伦理的新一轮讨论。

中文翻译：

Meta公司为其人工智能模型找到了新的训练数据来源：自家员工。该公司计划利用从员工鼠标移动和键盘敲击中提取的数据，以构建更强大、更高效的人工智能系统。

据路透社首次报道，这一事件揭示了科技公司为寻找训练数据新来源所采取的各种手段——训练数据是人工智能模型的生命线，能帮助程序学习如何更有效地执行任务和响应用户查询。

当TechCrunch联系Meta发言人置评时，对方发表如下声明："如果我们正在构建帮助人们使用计算机完成日常任务的智能体，我们的模型就需要人们实际使用计算机的真实案例——比如鼠标移动、点击按钮、导航下拉菜单等操作。为此，我们正在推出一款内部工具，将在特定应用程序中捕获这类输入数据以辅助模型训练。我们已建立保护机制来防范敏感内容泄露，且这些数据不会用于任何其他目的。"

这一趋势似乎揭示了人工智能行业令人担忧的隐私隐患——昔日的企业内部通讯正日益成为新型企业供应链的原料。上周有报道称，科技公司正在从老牌初创企业的企业通讯记录（包括Slack存档、Jira工单及其他内部通讯平台）中挖掘数据，这些都可能被转化为人工智能的"燃料"。

英文来源：

Meta has found a new source of training data for its AI models: its own employees. The company plans to use data culled from the mouse movements and keystrokes of its own staff in its pursuit to build more capable and efficient artificial intelligence.
The story, which was first reported by Reuters, shows the lengths to which tech companies are going to find new sources of training data — the lifeblood of AI models that helps the programs learn how to more effectively carry out tasks and respond to user queries.
When reached for comment by TechCrunch, a Meta spokesperson provided the following statement:
“If we’re building agents to help people complete everyday tasks using computers, our models need real examples of how people actually use them — things like mouse movements, clicking buttons, and navigating dropdown menus. To help, we’re launching an internal tool that will capture these kinds of inputs on certain applications to help us train our models. There are safeguards in place to protect sensitive content, and the data is not used for any other purpose.”
This trend would seem to reveal the troublesome privacy implications of the AI industry, as yesterday’s internal corporate communications are increasingly becoming fodder for a new corporate supply chain. Last week it was reported that old startups were being scavenged for their corporate communications (from Slack archives, Jira tickets and other internal messaging platforms), which could be converted into AI fuel.