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Recent headlines have shown the same unsettling pattern.

An AI system confidently generated legal cases that never existed, as reported when UK courts received filings built on fictitious case law (The Guardian, Scottish Legal News).

Health researchers have warned that AI can give medical guidance that is not just inaccurate but dangerously misleading. A British Medical Journal article as reported in the Independent stated that 20% of AI medical answers were "highly problematic".

And tech reporters have documented AI‑generated news summaries that included entirely fabricated headlines and events (Sky News).

In every case, the system generated output that communicated total confidence. In every case, the AI was wrong. Fluency is not understanding. Appearing proficient is not accuracy. This confusion is exactly where the real risk lies.

Give Clear Instructions

AI works best when you tell it exactly what you want. It does not infer your intentions or read between the lines. The output you see is a statistical software prediction based on patterns in the training data of the AI. The clearer your request, the better the output.

Start by stating your goal. Instead of asking, "Tell me about climate change," try: "Give me a 150‑word summary of the main causes of climate change for a general audience." A specific target gives the system's statistical pattern-matching something concrete to aim at.

Set the format you want. Simple instructions like "Give me three options," "Write this as a short email," or "List the steps in order" immediately improve the result. Format acts as a constraint, and constraints make the output sharper.

Define the audience. AI changes tone and detail depending on who you say it is for: beginners, executives, customers, or the general public. A single line about the audience can transform the clarity of the answer.

If accuracy matters, add constraints such as "Use widely accepted information," "If you’re unsure, say so," or "Do not invent details." These reduce the risk of confident mistakes.

Clear instructions make the output better and safer, but they do not eliminate the risk of mistakes. Even with perfect prompts, a system can still deliver something that sounds certain but is completely wrong.

The AI is not weighing evidence or checking facts. AI is programmed to produce an answer that appears most likely based on patterns in its training data. When those patterns point in the wrong direction, the result is a confident mistake. Your prompt has to help the AI navigate any bias or missing data in its training data. Think of your prompt as you nudging the AI in the direction you want to go.

When your task is large, break it into smaller steps. Ask for an outline first, then expand each section. AI performs far better when guided step‑by‑step.

Clear instructions don’t just improve the output, they keep you in control of the process.

Provide Enough Context

AI performs noticeably better when it has the background information it needs, such as who the audience is, what the situation involves, or what constraints apply.

When context is missing, the system often fills in the gaps with incorrect predictions that will look like guesses, and recent reporting shows how easily this can go wrong. The Guardian found that Google AI Overviews gave misleading health advice because the AI responded without understanding the medical circumstances involved, including a case where it advised pancreatic cancer patients to avoid high fat foods, which experts described as really dangerous. This is dangeous advice as some who suffer from pancreatic cancer are malnourished and consuming fat can be a nutritionally efficient way to ingest energy.

Check the Output Carefully

AI is not a source of truth, it is a generator of plausible answers, so treat every response as a draft, not a verdict.

Read the answer to then ask basic questions: Does this match what you already know, does it contradict trusted sources, does anything feel too neat or too extreme?

For factual topics, spot check key claims against reputable outlets or official documentation, especially numbers, names, dates, web links, and legal or medical details.

For writing tasks, look for invented quotes, fake references, or details that are oddly specific without any support.

If something important hinges on the answer, ask the system to show its reasoning, to list uncertainties, or to offer alternative possibilities.

The core habit is simple: never confuse a confident tone with a reliable answer. Once you see the answer you can ask the AI more questions to check the reliability of that answer. This is especially important if you are going to do something that relies on that answer.

Use AI for the Right Tasks

AI is most effective when the work involves drafting, summarising, organising ideas, exploring options, or speeding up early stage thinking.

AI can turn rough notes into a clean paragraph, reshape a long document into a shorter one, or generate several ways to frame a problem so you can choose the best one.

AI is also useful for outlining reports, comparing approaches, rewriting for different audiences, or helping you see alternatives you might not have considered. These are tasks where speed and structure matter more than perfect accuracy. You can make text accurate later.

AI is far less reliable when the task requires expert judgment, real world verification, or precise factual detail, so keep it focused on the parts of the job where it can genuinely help rather than the parts where it can get you into trouble.

Keep in mind that AI is not thinking. AI does not check for truth. It generates plausible text based on its training data.

Avoid Using AI for Judgement or Decisions

AI cannot weigh values, consequences, or ethics, and it cannot understand the human context that sits behind real decisions.

AI can offer options, outline trade offs, or summarise information, but it cannot decide what matters most, what is acceptable, or what is fair. Those choices rely on experience, responsibility, and an understanding of people, none of which an AI possesses.

Use AI to support your thinking, not to replace it. Human judgement must stay in charge, especially when the outcome affects safety, wellbeing, trust, or the outcome has long term consequences.

Be Cautious with Personal or Sensitive Information

Treat AI tools the same way you would treat an online form or an email to someone you do not know.

Do not share details that could identify you, expose someone else, or create problems if they were ever seen by the wrong person. This includes financial information, medical records, passwords, private conversations, or anything that involves children, colleagues, or business clients.

Keep the boundary simple. If you would hesitate before typing it into a website, keep it out of an AI prompt. The safest approach is to describe the situation in general terms and remove anything that is not essential to the task. This protects your privacy and prevents sensitive information from being handled in ways you cannot control.

Compare Answers with Reliable Sources

Treat AI output as a starting point, not a final answer, and cross check anything that matters with sources you trust.

This is especially important for facts that are time sensitive, technical, or likely to change. A quick comparison with reputable news outlets, official guidance, or well established reference material can reveal errors that are easy to miss when the writing sounds polished.

This habit is not about distrusting the tool, it is about protecting yourself from mistakes that come from outdated information, missing context, or confident AI guesses. When accuracy matters, a second source is not optional, it is part of the process.

Keep an Eye Out for Gaps or Oddities

A useful habit when reading AI generated answers is to notice when something feels slightly off. This might be an explanation that is too vague, a claim that is oddly specific without support, or a confident statement that does not match what you know.

When you see these signs, pause and ask a follow up question or check the detail elsewhere.

Recent reporting shows how easily small oddities can signal a deeper problem. The Guardian described how a senior European journalist was suspended after using AI tools to summarise material and then publishing quotes that the people involved had never said. The investigation found dozens of invented statements that looked polished and authoritative but were entirely false, and the journalist admitted he had fallen into the trap of trusting text that only sounded right.

Examples like this show why readers should stay alert to gaps, inconsistencies, or moments when an answer feels too neat. These are cues to check the AI's output.

Stay Aware of the Limits of AI

AI does not understand meaning, it has no lived experience, and it cannot draw on intuition or common sense.

AI works by recognising patterns in data and producing text that fits those patterns, not by grasping the reality behind the words. This means it can miss context, overlook nuance, or present something that sounds authoritative without any understanding.

AI cannot feel uncertainty, it cannot judge what is important, and it cannot tell when it has made a mistake. Keeping these limits in mind helps you use the tool for what it is good at and avoid expecting it to behave like a person.

Related Work

• An explanation of how large language models actually function and why they should not be treated as miniature humans.
• A practical guide to assessing the quality, reliability, and safety of AI chat session outputs.
• Ten simple AI workflows that save minutes each day and compound into hours each week, helping people work more efficiently.