Mental Privacy
Can a person inquire without unnecessary identity linkage, behavioral surveillance, or indefinite query retention?
Cognitive Liberty Audit
A research-derived, experimental framework for evaluating AI systems, search engines, recommenders, and digital platforms across ten separate dimensions of cognitive liberty.
Audit principles
The framework is designed to compare observable practices and expose uncertainty. It does not declare a platform morally pure, legally compliant, or safe in every context.
Ten-category scorecard
Each category asks a different question. Strong privacy cannot excuse arbitrary moderation; good appeals cannot excuse unnecessary surveillance.
Can a person inquire without unnecessary identity linkage, behavioral surveillance, or indefinite query retention?
Does the system preserve lawful research, criticism, education, curiosity, and controversial exploration?
Can users understand meaningful data practices, ranking/refusal boundaries, and consequential automated decisions?
Can users control personalization, memory, recommendations, and important defaults without coercive friction?
Does the service collect and retain only what is necessary for the stated purpose?
Are consequential restrictions explained, reviewable, correctable, and reversible?
Do safeguards target demonstrated harm with the least restrictive effective intervention?
Are rules applied to conduct and quality rather than hidden ideological loyalty tests?
Can users export, leave, switch, and preserve their own work or memory without lock-in?
Does architecture avoid unnecessary single points of control and make exit or interoperability technically possible?
Evidence method
Capture the public policy, feature scope, user controls, retention claims, and stated safety rationale.
Use reproducible, authorized test cases to see whether ordinary behavior matches the documented rule.
Evaluate proportionality, alternatives, errors, recourse, portability, and whether less data could achieve the same result.
State what was provider-reported, independently observable, inaccessible, time-sensitive, or outside the test scope.
A total can be useful for comparison, but it can also hide a serious weakness. A service that scores extremely well on portability and poorly on mental privacy should not be able to average the privacy problem away. Category scores remain the primary result.
Search and recommendation systems must rank, deduplicate, fight spam, remove unlawful material, and protect users from genuine hazards. The audit question is whether quality and safety rules are sufficiently clear and consistently applied that disagreement itself does not become an invisible disqualifier.
Decentralized systems can still be abusive, opaque, or unsafe. Centralized systems can still provide strong privacy and due process. Decentralization is therefore evaluated as an exit and concentration-of-control property, not as an automatic virtue.
Research basis: Cognitive Liberty Audit Framework, Cognitive Liberty Risk Actor Map, and AI System Website Evaluation Research. The public implementation intentionally removes claims of universal standardization or certification that would outrun the evidence.