Concern 905 · Working draft · editorial review in progress
Trade-secret exposure via prompts
Trade-secret exposure through prompts happens when staff send confidential business information to an AI service without an appropriate basis or protection.
Understanding the concern
A person may paste a product plan, source code or negotiation document into a tool to save time. Even if the provider does not train on that material, it may still process or retain it under the applicable terms. Exposure also depends on account access, sharing settings and connected tools.
NCSC guidance highlights the need to understand what is being shared and with whom. Current product terms vary, so it is wrong to assume that every prompt automatically becomes public training data. Think of handing a confidential document to an outside editor: the service and agreement matter. Clear approved workflows can help staff get useful assistance without making ad hoc disclosure decisions.
An example
An employee uploads a confidential design to a personal AI account because the organization offers no clear alternative.
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.
- Training
- The process of using examples to shape how an AI model behaves. Learning patterns from material does not establish that the material is true or fair.
- Prompt
- The instructions or information given to an AI to guide its response.
Evidence and its limits
The security guidance is historical; the commercial policy provides a current counterexample to universal training claims. Neither establishes that every upload becomes visible to other users.
UK National Cyber Security Centre · Security guidance
ChatGPT and large language models: what's the risk? ↗ (opens in a new tab)2023 guidance explains risks in sharing prompts with a provider. Current training, storage and access terms differ by product; do not reuse historical defaults as current facts.
Anthropic Privacy Center · Provider policy
Is my data used for model training? ↗ (opens in a new tab)Commercial inputs and outputs are not used for training by default, with opt-in and feedback exceptions. Distinguish commercial from consumer products and the applicable agreement.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
- NIST AI RMF (opens in a new tab)
framework
- ISO/IEC 42001 (opens in a new tab)
standard
A question to discuss
Is this service and account approved for this information, and what do its actual access and retention terms allow?
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?
Stewardship
Stewardship means caring for resources and systems that others depend on, including people who will use them later. It looks beyond the benefit of a quick launch.
Plan for maintenance, energy use, data protection, and eventual shutdown. Ask who will look after the tool when the original team moves on and how future users can avoid inheriting hidden costs.
Ask together: What are we responsible for caring for over time?
Prudence
Prudence means using careful judgment before and during action. It balances worthwhile opportunities with the need to avoid harm that could have been anticipated.
Start with a limited trial, set stopping points, and prefer choices that can be undone when uncertainty is high. Review what happens rather than assuming the original plan remains sound.
Ask together: What is a careful next step, and when should we stop or change course?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
About the register and scoring →More ways to explore
Search for more writing
For more specific or recent material, open a search below or ask for a web summary. AI-generated summaries can contain mistakes; open the original articles to check them.