Understand what AI and generative AI do, recognize everyday examples, protect information, and make one responsible first decision.
Begin with your goal, place, access, time, budget, and responsibility. Open the original sources, compare realistic options, and confirm details with the people who maintain them.
What is the tool actually doing?
What information did it learn from or receive?
Can the answer be wrong even when it sounds confident?
Who could be helped, left out, or harmed?
Which person remains responsible?
These original and authoritative destinations are annotated so readers know what each contributes, what still requires local confirmation, and when to use it.
NIST
NIST explains AI risk management for developers, users, evaluators, executives, and nontechnical audiences.
It supplies the responsible-use foundation and human-accountability vocabulary.
Cybersecurity and Infrastructure Security Agency
CISA advises people not to put sensitive information into AI tools, warns about AI-enabled deception, and emphasizes account security and human expertise.
It supports the input restrictions, security controls, synthetic-media rules, training expectations, and incident reporting steps.
UNESCO
UNESCO centers human dignity, privacy, fairness, transparency, oversight, participation, and remedy.
It shapes the questions about who benefits, who may be harmed, who decides, and how people obtain correction.
Sources and requirements can change. Check the publication date, read the original material, and confirm the rules that apply locally before making a consequential decision.
Compare purpose, evidence, local access, cost, privacy, accessibility, support, and current source information before choosing a next step.
AI is a broad term for computer systems that perform tasks such as recognizing patterns, predicting, classifying, recommending, or generating content. It is not a person and does not understand or take responsibility as a person does.
Generative systems produce text, images, audio, video, or code by predicting patterns from training and input. Plausible output can still be inaccurate, invented, biased, or inappropriate.
Keep private information out, use strong account security, verify urgent requests through another channel, and do not assume a familiar voice, image, or message is authentic.
Start with purpose, protect people, check evidence, look for unequal effects, disclose material assistance, and keep a person accountable for consequential use.
✓ Starting from a specific learner, organizational, or community goal
✓ Opening original sources and recording the review date
✓ Comparing realistic alternatives before committing time, money, or information
× Treating inclusion as endorsement, approval, or ranking
× Relying on a title or summary without checking the current source
× Choosing a tool or program before considering access, privacy, accessibility, cost, and support
Use the comparison and planning tools while reviewing the original resources linked in the evidence section.
A six-question beginner safety check.
Use when an answer sounds confident, urgent, or unusually convenient.
Examine familiar technology and identify where patterns, data, and human decisions appear.
Choose three familiar tools or features.
Identify what information each receives.
Describe what it predicts, generates, or recommends.
Name where it could be wrong or unfair.
Identify the person responsible for checking or correcting it.
What changed when you looked past the word AI and examined the information, task, consequence, and responsible person?
Share the plan with the people responsible for the work and the people who may be affected. Confirm local rules, protect private information, and name the person who can answer questions or correct a problem.