Not as the final authority. AI can help you organize options, explain unfamiliar concepts, or prepare questions, but whether a particular system is suitable depends on the task, the evidence behind its output, the consequences of an error, and the safeguards around its use. For a consequential decision, verify important claims independently and keep a qualified person responsible for reviewing and making the decision.
Why there is no universal yes-or-no answer
“AI” covers different systems and uses. A tool that helps brainstorm questions may be useful while still being a poor choice as the sole basis for a medical, financial, legal, safety, or rights-affecting decision. Fluency is not proof that an answer is accurate, current, or appropriate to your circumstances.
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The OECD AI principles call for safety, risk management, human agency and oversight, and accountability suited to a system’s role and context. In practice, the greater the potential harm from an error, the stronger the checks and human review should be. There is no single generic “AI accuracy” score that establishes whether a system is safe for every important decision.
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Generative AI is especially important to treat as a source of claims to verify, not as proof. UNESCO’s Guidance for generative AI in education and research says, “GenAI can never be an authoritative source of knowledge on whatever topic it engages with.” That guidance also describes it as a “fast but frequently unreliable source of information.”
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How to check an AI recommendation before acting
- Define the decision and the downside. Be specific about what you are deciding and what a wrong answer could cost in health, safety, money, legal standing, or rights.
- Check whether this system is suited to this task. Look for information about the actual system’s intended use and evaluation for the task. Do not infer suitability from confident wording or a tool’s general reputation.
- Verify consequential claims at their sources. Check important facts against authoritative, current sources. If the AI gives citations, open them and confirm that they support the claims; a generated reference is not verification by itself.
- Look for assumptions and missing context. Ask what information the recommendation relies on, what remains uncertain, and whether it could affect different people differently. Correct or add relevant context, then reassess rather than accepting the first answer.
- Get qualified review when the stakes warrant it. For high-consequence choices, ask a qualified person to assess the facts and recommendation. Make sure the reviewer can disagree with or override the AI rather than merely approve its output.
- Protect sensitive information. Before entering personal or confidential details, check the service’s terms and the rules of any relevant employer, school, health provider, or other organization.
- Keep a route to correct the decision. If AI informs a decision affecting your rights or opportunities, ask who made the decision, what reasons were considered, and how to submit information or request review where such a route is available.
This is a practical application of the OECD’s principles, UNESCO’s guidance, and the NIST AI Risk Management Framework, not a universal legal checklist or guarantee of safety. NIST describes the AI RMF as voluntary; its generative-AI profile was released on July 26, 2024. The framework is a resource for managing risk across the design, development, use, and evaluation of AI, not a certification that a particular answer is correct.
Can you rely on AI for a medical decision?
Use AI, at most, as support for understanding information or preparing questions—not as a substitute for individualized clinical judgment. A system’s ability to produce a plausible explanation does not establish that it has the necessary accuracy and reliability for your specific health question.
The World Health Organization’s guidance concerns governance of large multimodal models in health. It recommends that applications perform well-defined tasks with the necessary accuracy and reliability, with engagement from health providers, patients, and other stakeholders. It does not certify every chatbot or provide an individual diagnosis. See the WHO publication and its summary of the guidance.
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AI can inform a decision, but responsibility should not be ceded to the system. UNESCO’s education and research guidance says, “Prevent ceding human accountability to GenAI systems when making high-stakes decisions.” That statement is made in an education and research context; it supports human oversight but does not, by itself, determine legal duties in every sector.
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For a consequential decision, identify the person or organization that can review the recommendation, explain the decision, and correct an error. If an organization uses AI in a decision affecting you, ask whether AI informed the outcome and what review or correction process exists. UNESCO’s Recommendation on the Ethics of Artificial Intelligence calls for people to be informed when AI informs a decision. Where rights and freedoms are affected, it says people should be able to access reasons and submit information to staff able to review and correct the decision. The legal rights available depend on the jurisdiction and setting.
What to compare when choosing an AI tool or review process
Suitability is specific to the system and task. Compare the aspects below rather than relying on a broad claim that a tool is “accurate” or “safe.” OECD guidance emphasizes traceability, accountability, safety, and lifecycle risk management; WHO’s health guidance emphasizes well-defined tasks and necessary accuracy and reliability; UNESCO emphasizes rights, transparency, and human oversight.
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| What to assess | Question to ask |
|---|---|
| Task-specific performance | Has this system been evaluated for the task and conditions in which it will be used? |
| Impact of an error | What could go wrong, and how serious or difficult to reverse would the harm be? |
| Transparency and traceability | Can someone inspect the information and reasoning that informed the recommendation? |
| Privacy and security | What information will be entered, and what rules govern its handling? |
| Unequal effects | Could the system’s recommendation work differently or unfairly for people in different circumstances? |
| Oversight and correction | Can a qualified person challenge or override the result, and can an affected person seek review? |
Where the evidence stops
Official principles and domain guidance support a risk-based approach, but they do not establish one threshold for when every AI system is safe enough for an individual’s important decision. Suitability depends on the actual system, task, decision-maker, safeguards, and applicable local rules. A general AI answer can be a useful starting point; it should not end the checking process.
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