Exclusive-Meta to start capturing employee mouse movements, keystrokes for AI training data

STREETINSIDER.COMApr 21, 4:27 PM UTC

Key insights

  • Meta is implementing software to track employee computer activity (mouse movements, keystrokes, screen snapshots) to train AI models. While Meta claims data is solely for AI training and not performance reviews, the initiative raises privacy concerns and could negatively impact employee morale, potentially leading to decreased productivity and a slight negative sentiment towards Meta's stock.
Exclusive-Meta to start capturing employee mouse movements, keystrokes for AI training data

By Katie Paul and ‌Jeff Horwitz

NEW ​YORK, ​April 21 (Reuters) - Meta is installing new tracking software on U.S.-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.

"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," ​said Stone.

(Reporting by Katie Paul in New York and Jeff Horwitz in San Francisco; Editing by Matthew ‌LewisContact: [email protected])

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