Disclosure Requirements for AI Systems

In The You On AI Field Guide

Disclosure alone does not change behavior. This is one of the most robust findings in the behavioral literature, and it is the finding that distinguishes the nudge framework from the informational approach that preceded it. Decades of research on financial disclosure, nutritional labeling, and privacy notices consistently demonstrate that information provision by itself produces minimal behavioral effect. People do not read disclosures. When they read them, they do not understand them. When they understand them, they do not act on them, because the gap between information and action is bridged not by knowledge but by the architecture of the choice environment.

The disclosure requirement is therefore foundational rather than culminating. It creates the transparency on which more substantive interventions — default standards, deliberative oversight, ongoing evaluation — depend. Without disclosure, defaults are designed blind. Without disclosure, the deliberative body cannot assess what the commercial architecture is actually doing. Without disclosure, users cannot make informed choices in the contexts where the override matters most. Disclosure is the floor beneath the architecture, not the architecture itself.

The political economy of disclosure is the mechanism's most important feature. Companies building AI tools possess strong financial incentives to resist requirements that would reveal engagement-maximizing features of their interfaces. The countervailing force is public demand for institutional protection, which depends on public understanding of what is at stake. Transparency about the choice architecture of AI tools would, if widely understood, generate the political pressure that sustains the more substantive interventions. The people who learn that the AI tool they use every day was designed to maximize their engagement rather than their well-being become the constituency for the regulatory architecture that protects their interests. The disclosure requirement is the foundation not only informationally but politically.

The technical challenge of meaningful disclosure is substantial. Simple text disclosures in terms-of-service documents produce no behavioral effect. Effective disclosure requires formats designed for comprehension — visual representations of engagement mechanisms, comparative displays of default configurations across competing products, plain-language descriptions of optimization targets. The design of disclosure itself becomes a choice architecture problem, and the quality of disclosure design determines whether the requirement produces informed users or formal compliance.

Origin

Cass Sunstein

Disclosure as regulatory tool has a long history in American administrative law, running through securities regulation (1933), truth-in-lending (1968), nutritional labeling (1990), and privacy notices (various). Sunstein's contribution has been to integrate disclosure into the broader behavioral framework and to specify conditions under which disclosure is effective (simplicity, salience, timing) versus merely formal (dense text, buried location, infrequent presentation).

Key Ideas

Information asymmetry is foundational. Builders know the choice architecture; users do not; the gap cannot be closed without deliberate disclosure.

Disclosure alone is insufficient. The behavioral literature consistently demonstrates that information provision produces minimal behavioral effect without complementary architectural interventions.

Disclosure enables other interventions. Transparency creates the informational foundation for defaults, deliberation, and sunset review — remove disclosure and the architecture degrades.

Disclosure design matters. Dense text buried in terms-of-service produces formal compliance; visual, comparative, plain-language disclosure produces informed users.