This is a research prototype. The data and analyses are preliminary and not yet validated — we'd welcome your .
Facebook's 'People You May Know' (PYMK) recommendation algorithm inadvertently outed sex workers by suggesting their private accounts to clients or family members. The system used opaque data signals to link separate identities, causing significant privacy and safety concerns for users who intentionally kept their professional and personal lives separate. Facebook failed to provide clear explanations for these linkages or a viable opt-out mechanism, and even provided incorrect information regarding potential workarounds.
Facebook's "People You May Know" feature reportedly outed sex workers by recommending clients to their personal accounts or family members to their business accounts with no option to opt out.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
AI systems that memorize and leak sensitive personal data or infer private information about individuals without their consent. Unexpected or unauthorized sharing of data and information can compromise user expectation of privacy, assist identity theft, or cause loss of confidential intellectual property.
Also classified as
Facebook maintains an algorithmic black box around PYMK, refusing to disclose the 100-plus signals used, leaving users unable to understand or prevent the privacy leaks.
The PYMK algorithm correctly inferred and linked highly sensitive, non-public connections between users' real-world identities and their separate sex-work personas without their consent.
AI system
Due to a decision or action made by an AI system
Unintentional
Due to an unexpected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The privacy violations were caused by the autonomous operations of Facebook's PYMK recommendation algorithm, which produced unexpected and harmful identity linkages after deployment.
Added categories peak at 2: Minor (Psychological Harm, Direct)
Facebook's PYMK recommendation algorithm unintentionally linked and exposed the separate identities of users who sought to keep their personal and professional lives apart, such as sex workers. While posing significant privacy and safety concerns for vulnerable individuals, the incident does not present direct or substantial threats to national security, representing a minor impact on societal stability and privacy rights.
The PYMK algorithm operates independently in the background, processing user data and social graphs to autonomously generate and display friend recommendations to users without direct human intervention or explicit step-by-step planning.
Minimal or No Risk: The system is a social media recommendation algorithm used for suggesting friend connections, which does not fall under the high-risk or limited-risk categories of the EU AI Act.
The primary function of the 'People You May Know' system is to recommend social connections (profiles) to users to increase network density. It also performs identification by linking disparate data points to identify real-world relationships.
The report provides detailed, first-hand accounts from affected individuals ([name withheld] and [name withheld]) and representatives of advocacy groups, clearly establishing the connection between Facebook's PYMK algorithm and the privacy violations. While the exact technical signals used by the algorithm remain undisclosed by Facebook, the real-world impact and the failure of the platform to provide workarounds are well-documented.
None. The link between the algorithm's recommendations and the exposure of separate identities is clear and undisputed, even if the underlying technical mechanism is opaque.
Technology
Black Box Recommendation Engine
PYMK uses over 100 opaque signals to link users without their consent.
Intrusive Network Analysis
Algorithms aggressively map social connections, bypassing user privacy shields.
Data Inputs
Undisclosed Contact Tracking
System utilizes indirect contact lists and metadata to establish linkages.
Lack of Data Separation
Platform aggregates disparate data points, blending separate user personas.
Human Factors
False Sense of Security
Users assumed separate emails and phone numbers would guarantee anonymity.
User Vulnerability to Stalking
Sex workers and performers face heightened physical and professional risks.
Process and Methods
No Opt-Out Mechanism
Facebook did not provide an option to disable or opt out of PYMK.
Inadequate Feedback Loops
X-ing out suggestions does not prevent the user from being suggested.
Flawed Privacy Workarounds
Documented workarounds to disable suggestions were non-existent or false.
Management
Growth-Above-All Strategy
Management prioritized network growth and density over user safety and privacy.
Lack of Transparency
Management refused to disclose the specific signals used for recommendations.
Regulatory Environment
Lack of Privacy Regulations
Absence of strict laws governing algorithmic contact linking and profiling.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
