Meta 捕获员工鼠标移动和按键记录,用于人工智能训练数据。
Meta capturing employee mouse movements, keystrokes for AI training data

原始链接: https://economictimes.indiatimes.com/tech/technology/meta-to-start-capturing-employee-mouse-movements-keystrokes-for-ai-training-data/articleshow/130422612.cms?from=mdr

Meta正在在美国员工的电脑上部署新的追踪软件,用于收集数据以训练人工智能模型。该软件将监控鼠标移动、点击、键盘敲击,并在与工作相关的应用程序内定期截屏,以提高人工智能自主执行任务的能力——特别是下拉菜单选择和键盘快捷键使用等领域。 根据内部备忘录,收集的数据*不会*用于员工绩效评估。Meta强调,其目的仅仅是通过提供真实世界的使用案例来增强其人工智能代理。据报道,已经采取了安全措施来保护敏感信息。 这项由Meta SuperIntelligence Labs团队主导的举措,旨在利用员工的工作流程来完善人工智能模型,并构建更强大的人工智能助手,以完成日常任务。

一份最新报告详细介绍了Meta收集员工鼠标移动和键盘敲击数据,用于生成其人工智能模型训练数据的情况。 这在Hacker News上引发了讨论,用户们争论其影响。 一些人对Meta声称数据不会用于绩效评估表示怀疑,而另一些人则看到了潜在的好处。 一位评论员认为,这种数据收集实际上可以通过弥合人类和人工智能工作流程之间的差距来*改善*人工智能模型的训练。 另一位评论员指出,数据收集本身并非新鲜事,但其*用途*——用于人工智能训练——是新的。 一个幽默但愤世嫉俗的观点设想了一个反馈循环,人工智能会逐渐恶化,导致沮丧的员工真的会“把头撞向键盘”。 这次讨论凸显了利用内部数据进行人工智能开发日益增长的趋势,以及围绕此类实践固有的信任问题。
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原文

Meta is installing new tracking software on US-based employees' computers to capture mouse movements, clicks and keystrokes for use in training its artificial-intelligence models, part of a broad initiative to build AI agents that can perform work ‌tasks autonomously, ⁠the ⁠company told staffers in internal memos seen by Reuters.

The tool will run on a list of work-related apps and websites and will also take occasional snapshots of the content on employees' screens for context, according to one memo, posted by a staff AI research scientist on Tuesday in a dedicated ⁠internal channel ‌for the company's model-building Meta SuperIntelligence Labs team.


The ​purpose ​of the exercise, according to the memo, was ⁠to improve the company's models in areas where ​they still struggle, like choosing from dropdown menus ​and using keyboard shortcuts.

"This is where all Meta employees can help our models get better simply by doing their daily work," it said.

Meta spokesperson Andy Stone said the data collected would not be used for performance assessments or ‌any other purpose besides model training and that safeguards were in place to protect sensitive content.