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Production AI Institute · PSF v1.1 open standard
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Public campaign · PSF-aligned · open to cite

If AI uses your data or affects your life, you have a right to know.

No hidden AI. No silent data use. The AI Right-To-Know asks organisations to publish a simple AI System Disclosure for systems that affect people: owner, purpose, data touched, training reuse, human route, and incident process.

AI System Disclosure
A public artifact people can understand.
1
Identify when AI is used in a workflow that affects people.
2
Name the accountable owner for the system.
3
Publish the data boundary in plain language.
4
State whether data is reused for model training or shared onward.
5
Provide a human route for review, correction, or escalation.
6
Keep evidence for incidents, changes, and material failures.
The demand

People should not have to guess what AI is doing with their data.

This is intentionally plain. A disclosure does not claim perfection. It tells people the minimum facts they should not have to beg for: what the AI is doing, who owns it, what data it touches, whether that data is reused for training, how a person can intervene, and what evidence exists when something goes wrong.

PAI maps the disclosure back to the Production Safety Framework and PAI-8 so small organisations can start with transparency, while serious deployments have a path into stronger evidence, Lab review, and formal assurance.

For business owners

Publish a disclosure before customers ask for one. It shows maturity without pretending a lightweight public statement is a full audit.

Create a disclosure ->

For MSPs and consultants

Run a client session, capture the workflow, and leave behind a public disclosure that opens the deeper control conversation.

Open the MSP pack ->

For governments and regulators

Use the disclosure as a simple public expectation: AI systems that affect people should have ownership, data-use clarity, and an escalation route.

Read PAI-8 ->

For customers and workers

Ask for the disclosure. It is a direct way to request basic clarity without needing to understand the entire technical stack.

View registry ->
Founding signatoriesNow open

I support the AI Right-To-Know: if AI uses our data or affects our lives, people should be able to see what it does, what data it touches, whether that data is reused for training, and where a human can be reached.

What disclosure changes

From uncertainty to something people can inspect.

1

Name it

The organisation states where AI is used, what it does, and who owns it.

2

Explain it

People can see data boundaries, training reuse, human review, and incident routes in plain language.

3

Compare it

Customers, staff, partners, and communities can compare the disclosure with a public standard.

4

Improve it

Gaps become concrete work: clearer boundaries, escalation, evidence, and stronger controls.

Ask an organisation to publish a disclosure ->