Welcome to the evolving landscape of digital privacy, where the lines between convenience and concern are constantly redrawn. Meta’s latest venture, the personal AI assistant named Muse, has rapidly captured public attention, drawing millions of downloads as users integrate it with their most sensitive data—from bank accounts to health records—to streamline daily tasks.
However, as Muse integrates deeper into consumer lives, a closer look at its internal workings reveals a sophisticated, and some might say unsettling, capability: the creation of intricate profiles for every person in a user’s life. This revelation, stemming from extracted internal files, offers a rare glimpse into the architecture of an AI designed not just to assist, but to intimately understand your social world.
The Deep Dive: Unearthing Muse’s Internal Directives
The curtain was pulled back on Muse’s operational blueprint thanks to the efforts of independent AI safety and security researcher Karan Joshi. By cleverly prompting Muse through its standard chat interface, Joshi managed to extract a comprehensive set of the agent’s operating instructions and system prompts. These findings, subsequently shared with WIRED, illuminate the depth of Muse’s data-gathering ambitions.
Profiling Your Inner Circle: An Hourly Endeavor
Among the extracted instructions, one stands out: Muse is programmed to create “a page for every person in the user’s life.” This isn’t a one-time scan; it’s an hourly process. The AI diligently compiles data on family members, partners, friends, colleagues, “collaborators,” and even individuals you “follow.” The goal? To build a robust “memory”—essentially structured text files—detailing your relationships and the significant individuals within them.
The practical application, Meta suggests, is to offer personalized suggestions, such as advice on improving relationships or recommending a suitable breakfast spot for a coffee-loving friend. While AI chatbots offering relationship advice isn’t new, Muse’s systematic approach, coupled with Meta’s extensive history and access to social network data, raises unique questions.
The “Creepy” Factor: AI as Your Intimate Confidant
Karan Joshi doesn’t mince words about his findings. “What it seemed like to me—from all these prompts, system skills data, and things that they’re feeding into Muse—is that they want to understand your relationships that you have with real people,” he states. “They’re trying to know you like a friend, which is honestly pretty creepy.”
A Page for Every Person: What Muse Records
Muse’s internal documentation outlines how these personal pages are constructed. Initially “sparse,” they are designed to be populated over time with sections like “Facts,” “History,” “The relationship,” “In common,” “Open threads,” and “Strengthening.” Meta’s directives emphasize using only “evidence” available, prioritizing an empty field over invented details.
The level of detail is striking. Instructions guide Muse to record specifics such as “Where they live, what they do, the threads that recur (the apartment move, the shared savings goal),” along with “dates that matter” like birthdays and anniversaries. A person’s “History” could encompass events like “the trip in March, the argument that got resolved, the milestone last week.” Relationship dynamics are also scrutinized, noting “how close they are, what it is built on, how they act with each other, and what it seems to need right now.” The “Strengthening” section even suggests ways to foster connections, from “A reason to call” to “a way to be there for them that matters.”
Privacy Implications: A One-Sided Exchange?
Carissa Véliz, an associate professor at Oxford’s Institute for Ethics in AI, highlights a critical imbalance. “We are giving AI systems much more information about us than we are getting information from them,” she observes. This isn’t just about explicit data sharing, but also what AI can infer—correctly or incorrectly—and what it can piece together from various data sources, raising significant concerns about surveillance and autonomy.
Meta’s Stance: Transparency and User Control
Meta, for its part, asserts that Muse is built with transparency and user control in mind. Each user operates within their own dedicated virtual machine (VM), which stores their data and context, inaccessible to other agents. Users are reportedly able to wipe memories or disconnect external services at any time. Furthermore, Muse is designed to seek human confirmation before executing actions like sending an email or making a purchase, and an audit log allows users to review all of the agent’s activities and future plans.
Daniel Roberts, a Meta spokesperson, explained to WIRED, “For any agent to be useful and actually help you achieve your goals, it needs to have context about you and those you interact with.” He added that Muse gathers this context from public information and user-shared data, enabling it to recall details like a plumber’s identity or a spouse’s preferred flowers. This “memory” feature, designed for greater personalization, is becoming increasingly common among AI assistants, as noted by Miranda Bogen, director of the Center for Democracy and Technology.
While Meta emphasizes utility and control, the depth of Muse’s relationship profiling capability undeniably opens a new chapter in the ongoing debate about AI, privacy, and the future of our digital selves.
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