Disclosure Requirements for AI Systems

Disclosure requirements address the foundational information asymmetry of the AI economy: the companies building the tools possess detailed knowledge of the choice architecture embedded in their products (defaults, optimization targets, engagement mechanisms, behavioral patterns the design is intended to produce), while users possess almost none of this knowledge and have no structural means to acquire it. The specific disclosures that matter in the AI context are: the metrics the tool is optimized to maximize; the default configuration (continuous availability versus structured sessions, with or without comprehension checks); the engagement mechanisms (variable reward schedules, notification triggers, social proof displays); and the data practices (what behavioral data is collected, how it is used, whether it personalizes the interface in ways affecting behavior). Each disclosure enables the user, the deploying institution, and the regulatory body to evaluate whether the tool's design serves user interests.