Disclosure

What does “Disclosure” mean in practice?

Here, AI Ethics asks what Disclosure changes for the person making, reviewing, or living with a decision. Place Disclosure inside a workflow you already know. Who provides the input, who uses the result, and who needs to review it? You will turn Disclosure from an abstract idea into a choice with an owner and a review rule.

After this lesson

• Here, AI Ethics asks what Disclosure changes for the person making, reviewing, or living with a decision.
• Use the idea of “Disclosure” to interpret one realistic situation.
• Explain the limits of the concept and the information that still needs to be checked.

Start with the situation

Understand the situation first. The label can come later.

People need to know when AI supports a decision and how they can ask for a correction. This lesson uses the idea of “Disclosure” to examine that situation without treating a single term as the answer to every problem.

Here, AI Ethics asks what Disclosure changes for the person making, reviewing, or living with a decision. Explain when AI is used, why a result appears, how people can appeal, and who makes the final decision. Connect the term to a decision someone genuinely needs to make.

See how the decision unfolds

Move from the situation to a choice others can review.

Visual model

Map the parts before choosing what to do.

Read the diagram as a map of Disclosure: begin with the context, follow the connections, and inspect the highlighted point before making a decision.

Do not rush the choice

Two ways to look at Disclosure

The stronger choice is the one whose evidence, owner, and limits can be explained, not simply the more sophisticated option.

A tempting shortcut

A familiar term can still lead us to the wrong decision.

Why this can seem reasonable

Human review only works when the reviewer has enough time, information, and authority to act. This mistake often appears when a label is used before the problem is understood. Write down your assumptions so another person can review them.

How to check it

Place Disclosure inside a workflow you already know. Who provides the input, who uses the result, and who needs to review it? Begin with what can be observed, then separate facts, assumptions, and open questions.

Pause for a moment

What evidence could change this decision?

Answer before opening the discussion. Name one fact and one assumption.

Try it on your work

Try it with one small piece of real work.

1. Choose one real situation related to Disclosure.
2. Separate what you can observe from what you are assuming.
3. Write one decision, its owner, and the evidence needed to review it.
4. Name the signal that would make you stop or change direction.

Write two examples that fit Disclosure and one that does not. Explain the difference in your own words. The larger module activity is: Design an appeal path for a high-impact decision. Keep the first version small enough for another person to review in a few minutes.

Quick practice

Write two examples that fit Disclosure and one that does not. Explain the difference in your own words. The larger module activity is: Design an appeal path for a high-impact decision.

Summary

• Here, AI Ethics asks what Disclosure changes for the person making, reviewing, or living with a decision.
• Use examples and evidence to test your understanding.
• Record the limits, risks, and conditions that should trigger another review.

Continue from here

• Explanation and Recourse: Continue the idea from Transparency and Human Control with a closely related example.
• Roles: Connect this lesson to Leadership and test the idea in another context.
• Skill Gaps: See how the same decision changes when viewed through Future of Work.

Sources and further reading

• People + AI Guidebook: Google PAIR · official-guidebook. Primary reference for the definition, evidence, or limits discussed in “Disclosure”.
• Recommendation on the Ethics of Artificial Intelligence: UNESCO · official-recommendation. Further evidence and context for checking the explanation in “Disclosure”.
• European approach to artificial intelligence: European Commission · official-policy. Further evidence and context for checking the explanation in “Disclosure”.