5 Questions to Ask Before You Trust an AI Answer
AI tools are fast, fluent and almost always confident. That last part is the problem.
An AI answer that is wrong usually looks exactly like one that is right. Same tone, same neat structure, same certainty. There is no warning light when a chatbot invents a statistic, cites a source that does not exist, or explains a rule that changed last year.
That does not mean you should stop using AI. It means the skill that matters is no longer finding an answer. It is judging one. Here is a simple way to fact-check AI answers. Before you paste one into an assignment, a report or a decision, run it through these five questions.
1. Where did this actually come from?
Ask the tool for its sources, then open them yourself. This step catches more problems than any other.
AI models can produce references that look completely real: a plausible title, a real-sounding journal, a believable author. Sometimes the source exists but says something different. Sometimes it does not exist at all.
Try this: for any fact you plan to use, find it on the original page, in the original report, in the original wording. If you cannot find it, you cannot use it.
2. Would this pass a common-sense check?
Before checking the details, check the shape of the answer. Does the number sound roughly right? Do the dates line up? Would someone who works in this field nod or frown?
AI is good at producing text that sounds reasonable and weaker at noticing when a figure is ten times too big or a timeline does not add up. You often know enough to spot that, if you slow down and look.
Try this: before you read the AI answer, write down what you expect it to say. If the answer surprises you, that is exactly where to dig.
3. Is this still true today?
Most AI tools learn from information up to a certain date, and the world keeps moving after that. Fees, deadlines, visa requirements, regulations, company policies and even job titles change all the time.
For anything time-sensitive, especially in Singapore, go straight to the official source: the government agency, the institution's own website, or the organisation's latest announcement.
Try this: ask yourself, "Could this have changed in the last year?" If the answer is yes, verify it before you rely on it.
4. What did it leave out?
AI tends to give the most common answer, not the most relevant one for you. Ask about a career, a market or a regulation, and you will often get the global, generic version, missing the local detail that actually matters.
It is also usually one-sided unless you ask otherwise. The answer you get is rarely the whole debate.
Try this: follow up with "What would someone who disagrees with this say?" and "How is this different in Singapore?" The gaps you find are often the most useful part of the exercise.
5. Can I explain it in my own words?
This is the question that separates using AI from being used by it.
If you cannot explain an answer without looking at the screen, you do not understand it yet. You also cannot defend it in a class discussion, a presentation or a job interview, which is exactly where people will ask you to.
Try this: close the chat, then explain the answer out loud or on paper in three sentences. Whatever you cannot explain is what you still need to learn.
A quick checklist
Source: Have I found it in the original?
Sense: Does it pass a common-sense check?
Current: Could it have changed recently?
Complete: What is missing, especially locally?
Clear: Can I explain it without the screen?
A note on coursework: every institution and module sets its own rules on AI use. Check the guidelines for your course, and ask your lecturer if you are unsure.
Checking AI is one skill. Knowing what it can't do for you is another.
These five questions help you catch AI when it is wrong. But there is a bigger question underneath them: if AI can answer almost anything, what is left that only you can do? And how do you prove it to an employer?
That is the question Professor Tim Boatswain, Chairman of TMC Academy, takes on in his upcoming seminar. His starting point is deliberately provocative:
"Banning AI in higher education is like banning the calculator in the 1970s."
If that line makes you want to argue, you are exactly who this talk is for.
What AI Can't Teach You, Build for You, or Take from You
Date: Friday, 30 October 2026
Time: 2pm to 3pm
Venue: Classroom 201, TMC Academy, 805 Geylang Road, Singapore 389683
Cost: Free. About 70 seats only.
The session ends with a live Q&A, so bring your hardest question about AI and your future.
FAQ
Why does AI sometimes give wrong answers so confidently?
AI language tools generate text by predicting what a good answer should look like, based on patterns in the information they learned from. They are not checking facts as they write, so a wrong answer can sound just as fluent and certain as a correct one.
What is the fastest way to fact-check an AI answer?
Find the key claim in its original source. For facts, go to the report, study or official page it came from. For anything time-sensitive in Singapore, such as fees, rules or deadlines, check the relevant government agency or organisation's own website.
Can I use AI for my assignments?
It depends on your institution and your module. Each sets its own academic integrity rules on AI use, so check your course guidelines and ask your lecturer if you are unsure. Whatever the rules, you should always be able to explain your work in your own words.
Is it still worth learning things if AI can look them up?
Yes. You need your own knowledge to judge whether an AI answer is right, to ask better follow-up questions and to explain your thinking to others. The bigger question of what AI can't do for you is the focus of Professor Tim Boatswain's seminar on 30 October.
Comments