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AI Safety

A plain-English checklist for privacy, hallucinations, permissions, human review, and knowing when not to automate.

Beginner

9 min

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Most business AI risk is not science fiction. It is ordinary operational risk with a very convincing interface.

Leave knowing / Use AI without being reckless

Five risks

Know these before you connect anything important.

Wrong

AI can produce an answer that sounds certain and is false. Important facts need sources or verification.

Leaky

Do not paste sensitive information into tools your organization has not approved for that data.

Over-permissioned

An agent should get the smallest set of tools and access needed for its job, not the keys to everything.

Unaccountable

A human owner still needs to be responsible for the workflow, especially when people or money are affected.

Invisible

If software can act, you need logs, proof, limits, and a way to stop or recover it.

Traffic light

A simple risk model for everyday AI use.

LevelExamplesDefault
GreenBrainstorming, rewriting your own text, low-stakes summariesUse, review, learn
YellowCustomer drafts, internal analysis, operational recommendationsUse approved data, verify, keep a human owner
RedHiring decisions, legal/medical/financial decisions, moving money, deleting dataSpecial controls or keep final authority human

Before an agent can act

Seven things should exist first.

01

A narrow job and explicit allowed actions.

02

The minimum permissions needed for that job.

03

A budget or action limit.

04

A source of truth for current state.

05

A deterministic check where one is possible.

06

A human escalation path for uncertainty or exceptions.

07

An audit trail that proves what was attempted and what actually happened.

The useful mindset

Trust is not a personality trait you assign to AI. Trust is a property of the system around it: sources, permissions, tests, approvals, observability, and recovery.

Do not ask: "Do we trust AI?" Ask: "What would make this particular action safe enough to trust?"

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