Concern 202 · Working draft · editorial review in progress
Undisclosed use of AI
Undisclosed use of AI occurs when people are not told that the content or interaction they encounter involves an AI system.
Understanding the concern
A person may make different choices if they believe they are speaking to a human adviser or reading a human-authored account. The importance of disclosure depends on the context, the role of the system, and what the person is being asked to trust.
A useful notice explains the relevant role rather than merely adding a vague AI label. It should not imply that a human has checked the output if that has not happened. Legal requirements differ; EU transparency rules cover specified interactions and generated content, with exceptions.
An example
A customer thinks they are chatting with a staff member who can exercise judgment, but the service is an automated assistant.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
- EU
- The European Union, a group of European countries with shared institutions and some shared laws.
Evidence and its limits
European Commission guidance explains Article 50 obligations for covered systems; the entry describes a broader trust concern, not a universal legal rule.
European Commission · July 2026 · Official regulatory guidance
Guidelines on transparency obligations for providers and deployers of AI systems ↗ (opens in a new tab)Explains Article 50 duties applying from August 2026 to specified systems and uses; not a worldwide disclosure rule.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
Would knowing the system's role change what the person shares or relies on?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Trustworthiness
Trustworthiness means giving people good reasons to rely on you. It grows when promises, actions, and evidence line up. With AI, a friendly voice or a famous brand is not enough: people need to know what was checked and what could still go wrong.
In practice, keep promises small enough to test, record mistakes, and tell people when the tool's limits affect them. If a service promises human review, make sure a person really has time and authority to review it.
Ask together: What would give the people affected a sound reason to trust this use?
Accountability
Accountability means being answerable for decisions and taking responsibility for repair. It requires more than saying that the software made the choice.
Name the person or team responsible, keep useful records, and give them authority to correct problems. Make the route to a complaint clear to the people affected.
Ask together: Who will answer for the outcome and help put things right?
Truthfulness
Truthfulness means making claims that match the evidence and being clear about what we do not know. It includes correcting mistakes rather than protecting a polished story.
Check sources, label guesses, and distinguish a trial result from a proven benefit. If AI helped produce a claim, someone still needs to take responsibility for checking it.
Ask together: What can we honestly say, and what still needs checking?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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