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Sometimes as support, but not as the sole authority. Whether AI is safe to use depends on the particular system and task, what could happen if it is wrong, and whether a qualified person can check and correct its output. Use it to organize options or prepare questions; independently verify consequential claims and keep a human decision-maker accountable.
There is no universal yes-or-no answer
“AI” covers different systems used for different purposes. A tool that helps brainstorm questions may be useful, while the same tool may be unsuitable as the only basis for a decision affecting health, safety, legal standing, money, or rights. Fluency, popularity, and a generally good reputation do not establish that a particular system has been evaluated for your task.
The OECD AI Principles emphasize safety, risk management, human agency and oversight, and accountability appropriate to a system’s role and context. In practice, the more serious the possible harm, the more important it is to have task-specific evidence, independent review, and a way to challenge or correct the result.
Match the safeguards to the stakes
- Low stakes: AI may help generate ideas, summarize material, or compare options, provided you check important facts.
- Consequential: Treat the output as input for a qualified person, not as a decision in itself. Verify claims against current, authoritative sources.
- High stakes or rights-affecting: Do not let a general-purpose answer make the decision for you. Look for meaningful human review, reasons for the decision, and an available correction or appeal route.
Why a confident AI answer is not proof
Generative AI can produce polished, specific-sounding answers that are incomplete or wrong. UNESCO’s Guidance for generative AI in education and research calls GenAI a “fast but frequently unreliable source of information” and says it “can never be an authoritative source of knowledge.” Treat an answer as a claim to check, not as evidence that the claim is true.
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Pay particular attention to missing context, assumptions, uncertainty, and the sources cited. A citation is not verification: open it and confirm that it is genuine, current, and actually supports the statement. If the answer depends on a fact about your situation, check whether the system had that information and whether it interpreted it correctly.
How to check an AI recommendation before acting
- Define the decision. State what you are deciding and what an error could cost in health, safety, rights, money, or legal standing.
- Check whether this system fits this task. Look for evidence that the particular system was intended and evaluated for the use you have in mind. Do not infer suitability from fluent output or general reputation.
- Verify consequential claims. Check them against current authoritative sources, and open cited sources rather than relying on generated references.
- Test the answer for gaps. Identify assumptions, uncertainty, missing information, and possible unequal effects on different groups. Ask a qualified person to review recommendations where the consequences are serious.
- Protect sensitive information. Before entering personal or confidential details, check the service’s terms and the rules of your workplace, school, or other organization.
- Keep a person able to intervene. The decision-maker should be able to question, override, or correct the AI-supported result. For a decision affecting your rights, ask for its reasons and how to seek review where those routes are available.
This is a practical way to apply the OECD principles, UNESCO’s guidance on human oversight and recourse, and the NIST AI Risk Management Framework; it is not a universal legal checklist. NIST describes the framework as voluntary and released a generative-AI profile on July 26, 2024. The framework supports risk management; it does not guarantee that a particular output is correct.
Rank #2
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What to check when comparing AI tools or decision processes
There is no single generic “AI accuracy” score that establishes whether a tool is suitable for every important decision. Compare the system and the process around it on the dimensions that matter to the task:
- Task-specific accuracy and reliability: Is there evidence for this exact use, under relevant conditions?
- Traceability: Can someone see what information or reasoning informed the recommendation?
- Privacy and security: What information is entered, and how is it handled?
- Unequal effects: Has the process been examined for different effects on people or groups?
- Oversight: Can a knowledgeable person meaningfully challenge or override the output?
- Correction and recourse: Can an affected person get an explanation and ask an authorized person to review a mistake?
These considerations reflect the OECD’s emphasis on lifecycle risk management, traceability, safety, and accountability; WHO’s focus on well-defined health tasks with necessary accuracy and reliability; and UNESCO’s attention to rights, transparency, and human oversight.
Rank #3
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What this means in health, education, and rights-sensitive decisions
Health decisions
Do not treat a consumer chatbot as a diagnosis or as a substitute for a clinician’s advice. WHO guidance on large multimodal models in health calls for applications to perform well-defined tasks with necessary accuracy and reliability, with engagement from health providers, patients, and other stakeholders. That guidance addresses governance; it is not a blanket approval of chatbots or an individual diagnosis. See the WHO publication and its summary of the guidance.
Education and research
UNESCO’s generative-AI guidance emphasizes human agency, monitoring, and validation. It says, “Prevent ceding human accountability to GenAI systems when making high-stakes decisions.” This advice is specifically framed for education and research; it supports retaining human responsibility but does not, by itself, set legal duties for other sectors.
Rank #4
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Decisions affecting rights
UNESCO’s Recommendation on the Ethics of Artificial Intelligence says people should be informed when a decision is AI-informed. Where rights and freedoms are affected, it recommends access to reasons and an opportunity to submit information to staff able to review and correct the decision. The legal rights available to you depend on your jurisdiction and the setting.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Who is responsible when AI affects a decision?
Using AI does not make the system an accountable human decision-maker. A person or organization choosing to rely on its output should retain responsibility for how it is used and for having appropriate oversight. UNESCO’s statement about not ceding accountability is made in its education and research guidance; legal responsibility in a particular case depends on the sector, jurisdiction, and facts. OECD principles likewise emphasize accountability and risk management across an AI system’s lifecycle.
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