Meta’s Muse AI Agent Raises Fresh Concerns Over Bulk Data Collection

Meta’s Muse AI agent, launched last month, quickly climbed to the top of Apple’s App Store thanks to its friendly avatar and promise of autonomous task handling. The app requests broad permissions—bank details, passwords, chat logs, contacts, and more—to build a contextual model of the user’s world.

Privacy advocates warn that this model inevitably sweeps up information about friends, family, and acquaintances who never agreed to share their data. As Signal Foundation president Meredith Whittaker noted, the system’s “autonomous actions” extend to anyone whose data can be inferred from messages, emails, or photos, creating a surveillance net that goes far beyond the individual who installed the app.

Why it matters for GPU/AI infrastructure

For GPU‑powered AI workloads, harvesting massive, non‑consensual datasets increases the strain on training pipelines and raises compliance risks for data‑center operators. Building privacy‑preserving alternatives—such as federated learning, secure multi‑party computation, or differential privacy—can reduce legal exposure while still leveraging the parallel power of modern GPUs for efficient model inference and training.