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    AI Safety

    AI fundamentals & modelsSecure design of AI systems
    Editorially reviewed on: 1 source
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    The short answer · 10 words

    In short

    Design and deploy AI systems to prevent or limit damage.

    Flow-alerta.cab (2026): AI Safety. https://flow-alerta.cab/en/glossar/ai-safety. Editorially reviewed on: 09 October 2026.

    How much detail would you like?

    Practical

    The possible consequences determine how carefully an AI operation must be secured.

    Example scenario: An AI tool may only propose a risky action and passes the decision on to qualified personnel.

    Define application limits and error consequences; design tests and human intervention possibilities appropriately.

    At a glance

    Core
    In the sense of safety, safety concerns, for example, the consequences of misconduct for people, physical assets and the environment. It covers development, testing and deployment limits; protection against attacks is a related security area.
    Use
    The possible consequences determine how carefully an AI operation must be secured.
    Example
    Example scenario: An AI tool may only propose a risky action and passes the decision on to qualified personnel.
    Limits
    Just test average performance; overlook rare serious errors; promise absolute safety.

    In context

    AI Risk Management

    Identify, evaluate and adequately address risks of an AI system.

    AI Alignment

    Design AI systems in such a way that their behavior matches the intended goals and targets.

    AI Ethics

    Assess which values and consequences should be considered in the development and use of AI.

    Questions about this term

    Is safety the same as security?

    The terms overlap, but have different focuses: avoid damage and ward off attacks.

    All details and background

    In the sense of safety, safety concerns, for example, the consequences of misconduct for people, physical assets and the environment. It covers development, testing and deployment limits; protection against attacks is a related security area.

    ELI5 – Explained simply

    You check what could happen in the event of an error and build appropriate boundaries.

    Why it matters in practice

    The possible consequences determine how carefully an AI operation must be secured.

    Example

    Example scenario: An AI tool may only propose a risky action and passes the decision on to qualified personnel.

    Pitfalls and limits

    • Just test average performance; overlook rare serious errors; promise absolute safety.

    Origin & history

    The NIST AI RMF 1.0 of 2023 treats safety as its own property of trustworthy AI.

    Use in mid-sized companies

    • Define application limits and error consequences; design tests and human intervention possibilities appropriately.

    Related terms

    Matching Flow-alerta service

    AI opportunity analysis & roadmapAI consulting: AI potential analysis & roadmap on tasks, data and prerequisites of a possible first AI use case.

    Matching tool / use case

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    Sources

    Quellenprüfung: 09.10.2026. Die Quellen belegen Definition und dokumentierte Einordnung; Anwendungsbeispiele sind mögliche Szenarien.

    Editorially reviewed on:

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