---
id: "question-plam-privacy"
type: "open-question"
source_timestamps: ["§ The Everything Engine Needs Your Data"]
tags: ["privacy", "data-security"]
related: ["concept-personal-large-action-models"]
resolution_path: "Advancements in on-device processing, federated learning, and zero-knowledge proofs deployed by hardware manufacturers like Apple and Google."
sources: ["futures"]
sourceVaultSlug: "hbr-seg-futures"
originDay: 2
articleStem: "hbr-foci-73-living-intelligence"
sourceUrl: "https://hbr.org/2025/01/why-living-intelligence-is-the-next-big-thing"
sourceTitle: "Why “Living Intelligence” Is the Next Big Thing"
---
# How will PLAMs balance autonomy with user privacy?

**Open question:** [[concept-personal-large-action-models|Personal LAMs (PLAMs)]] require access to *all* user data on personal devices — health metrics, location, habits — to function autonomously. The text states they will do this *"while maintaining a user's privacy and preferences,"* but the exact technical or cryptographic mechanisms for securing this **ultimate honeypot** of personal data remain an open challenge.

**Resolution path:** Advancements in **on-device processing, federated learning, and zero-knowledge proofs**, deployed by hardware manufacturers like **Apple and Google** — the same firms Webb notes are motivated to embed more sensors to build these individualized profiles.