AI disclosure should survive the interaction

Article 50 transparency rules apply from 2 August 2026, according to the European Commission’s summary. The canonical AI Act establishes targeted obligations that include informing people when they interact directly with an AI system unless that fact is evident from the circumstances and context. It also addresses specified generated or manipulated content.

This article is an operating framework, not legal advice or a determination that every Super Genius Labs workflow is in scope. Counsel can establish which duties, exceptions, and actors apply to a specific system.

Disclosure can disappear between states

Disclosure is better represented as a tested interaction state than as a single line of interface copy.

That framing matters because the Commission distinguishes provider duties for direct AI interactions and machine-readable marking from deployer duties involving emotion recognition, biometric categorisation, deepfakes, and certain public-interest text (European Commission). A team therefore cannot infer one universal implementation from the existence of Article 50 alone.

Map each user-facing AI entry point, assign a provisional provider or deployer owner for counsel to confirm, specify when the disclosure appears, and test the state across relevant delivery paths. The resulting artifact can sit beside other build and release controls.

Build one record for every in-scope surface

Field	Operating question	Example evidence
Surface	Where can a person encounter the AI-mediated experience?	Screen, call path, message template, media asset, or embedded component
Audience	Which user or recipient sees this state?	Anonymous visitor, authenticated user, caller, message recipient, or downstream publisher
Interaction or content class	Is this a direct interaction, generated content, manipulated content, or another counsel-defined class?	Counsel-reviewed classification record
Timing	At what point does the disclosure appear?	Before interaction, at entry, during a transition, or with delivered content
Owner	Which provider or deployer owner is accountable for implementation and evidence?	Named team and escalation contact
Presentation	How is the disclosure expressed in this channel?	Approved copy, spoken introduction, visible label, or machine-readable marking
Persistence	Does the state survive channel changes, handoffs, exports, and republication paths within the tested scope?	Transition and delivery test results
Exception	Does a statutory exception or context-dependent assessment need counsel?	Legal decision and review date
Evidence	What proves the configured state was exercised in a bounded test?	Screenshot, recording, rendered artifact, event record, or test result
Regression check	Which release check detects removal, delay, or corruption of the state?	Automated assertion or documented manual case

The applicable disclosure mechanism depends on the system, the parties’ roles, the content, and the circumstances. The canonical Act’s direct-interaction rule itself includes a circumstances-and-context qualification (EUR-Lex).

Follow the disclosure through four transitions

A disclosure can be configured at one entry point while remaining untested elsewhere.

Transition	Bounded release check
Channel change	Start in one interface and continue in another; verify the approved state at every counsel-designated point.
Human handoff	Move from an AI-mediated flow to a person and, where supported, back again; verify that the interaction state does not become ambiguous.
Session recovery	Resume after timeout, reconnect, or authentication; verify whether the prior disclosure remains sufficiently available under the approved design.
Generated-media delivery	Export, download, forward, or publish a covered artifact through each supported path; verify the specified visible or machine-readable treatment.

These are engineering test categories, not statements of what Article 50 mandates in every case. The Commission’s summary says the rules distinguish direct-interaction duties, machine-readable marking, and specified deployer disclosures (European Commission); counsel can translate the relevant category into a product-specific test oracle.

Split product defects from legal questions

For each matrix row, record the tested build, locale, channel, audience state, expected presentation, observed result, evidence location, owner, and review date. A passing result supports only the configuration and path exercised. It does not establish that every session completed the disclosure or that the system satisfies every applicable obligation.

Failures can be classified without making legal conclusions:

• Missing: the expected state did not appear.
• Late: it appeared after the approved trigger.
• Ambiguous: the rendered or spoken result differed from approved content.
• Lost in transition: it disappeared during a supported handoff or delivery path.
• Unverifiable: the team lacks sufficient evidence to determine the tested result.
• Scope question: classification, actor ownership, or an exception needs counsel.

This makes the release decision explicit. Product and engineering can resolve implementation defects; counsel can resolve legal scope; operations can own recurring checks and evidence retention within the organization’s approved policy.

The supplied evidence does not determine which Super Genius Labs systems fall within Article 50, whether a particular interaction makes its AI nature evident from context, or which exceptions apply. It also does not establish one disclosure design, test cadence, or evidence-retention period for every product.

Start with a counsel-reviewed inventory of user-facing AI surfaces. For each surface selected as in scope, complete one matrix row and one bounded transition test. The result is a concrete release artifact without treating an internal test as proof of legal compliance.