These terms are complementary lenses, not interchangeable labels.
Safety: what could go wrong?
AI safety concerns reducing risks from AI systems, including mistakes, misuse, and unintended consequences. It involves technical controls, product design, evaluation, and the context in which a system is used.
Alignment: what is the system trying to do?
Alignment concerns whether a system’s behavior and objectives fit intended human goals and values. There can be disagreement about those goals, and an apparently helpful response may still miss what a person actually needs.
Security: can someone manipulate the system?
AI security focuses on protecting systems, data, and workflows against adversarial actions. Protecting credentials and defending tool use are examples. The boundaries overlap: a security failure can become a safety incident.
A single incident can involve all three
Suppose an assistant pursues a user’s request efficiently but discloses a colleague’s private information. It may have followed the immediate request while failing to respect another person’s interests. If a hostile document caused the disclosure, there is also a security problem. Naming the dimensions separately helps assign a concrete control and an owner to each failure.
Whose intention should count?
An assistant may face instructions from a provider, application developer and user, alongside information about people who are not present. OpenAI’s Model Spec describes one provider’s approach to instruction priorities. It is a designed policy, not an inevitable or universally agreed answer to how competing interests should be resolved.
Source: OpenAI · OpenAI Model Spec · 18 December 2025Move from broad labels to evidence
NIST’s generative AI profile organizes risk-management work across a system’s lifecycle. Use that kind of structure to ask a smaller question: what failure are we addressing, in which setting, and what evidence would show improvement? Calling a model ‘aligned’ is too broad to settle whether an organization should connect it to sensitive data.
Source: NIST · Generative AI Profile · NIST AI 600-1A situation to think through
A calendar assistant finds a time that suits its user by cancelling a colleague’s meeting. The objective may need revision, the tool may need narrower authority, and the interface may need a review step. Improving the wording of the goal alone does not address all three issues.
Questions to take with you
- State whose interests and instructions are involved.
- Describe the unwanted outcome without relying on the word unsafe.
- Ask which control addresses that outcome and how it will be evaluated.
For more reading
The sources behind this page, with a reason to open each one. Practical examples and recommendations are our editorial interpretation.
- OpenAI Model Spec · 18 December 2025
The provider’s intended behavior and instruction hierarchy; a policy is not proof of consistent behavior.
- Claude’s constitution
Describes the values Anthropic intends to train into Claude, including tensions between them.
- Generative AI Profile · NIST AI 600-1
A framework for identifying, measuring and managing generative AI risks across the system lifecycle.
Sources reviewed 13 September 2026. Product documentation can change. How we use evidence