Why better questions lead to better use of AI
Every day, millions of AI users accept the first answer they are given. Although this may seem harmless, it can have serious consequences. AI models can embed biases, confidently present false information, and fabricate details that sound plausible. Without critical questioning, users can unconsciously internalize mistakes, weaken their decision-making skills, and cede agency to systems that don’t really think. No approach can eliminate all risks, but developing strong questioning habits can meaningfully protect your users.
In this article…
Why questions matter
Working with large-scale language models (LLMs) can feel like speaking with conscious, reflective thinking for students, educators, and e-learning professionals alike. It may seem as if AI is invested in our work and understands our personal circumstances. In reality, the AI is creating the illusion of a conversation.
Throughout life, the human brain never completely stops functioning under normal circumstances. Even in silence, we continue to integrate emotions, memories, and meanings. LLMs do not do this. They have no inner life and no continuous thought once the session is over. The AI only “wakes up” when prompted. This is why the question is important. Questions activate human cognitive tasks that AI cannot do.
When AI asks us questions, it’s not expressing curiosity. Nothing. AI asks questions because training data shows that doing so improves the interaction or clarifies missing information. They are not conversation partners like other humans. This is a pattern completion system. Repetitive prompts help refine the context and guide the model, while questions allow humans to reduce uncertainty and increase control over the output.
When AI can only generate the next statistically most likely response, human questions push the model beyond default thinking. Through questions, users can question surface-level outputs, clarify assumptions, and guide models into deeper analysis. This makes the question both a teaching skill and a cognitive safeguard.
5 questions every AI user should know
To use AI responsibly, we must learn to question it, just as people learn to read, write, and think critically. These skills are important if:
Educators Instructional Designers Business Professionals Healthcare Professionals Researchers Public Sector Employees Communicators Anyone who uses AI in their daily lives
When teaching yourself or others to ask AI questions, it’s important to remember that “questions” and “commands” to an AI can perform the same cognitive function. Humans must know what to ask, whether it is uttered as a question or a command.
1. How did you reach this conclusion?
instructions
Please explain your reasoning step by step.
LLMs generate output through predictions, but users rarely see how those predictions develop. Asking LLMs to explain their reasoning reveals what information they elicited, what patterns they recognized, and how they connected ideas. This helps users determine whether the model followed a logical path that matches the prompt. Unclear, unsupported, or inconsistent reasoning indicates the need for follow-up prompts or deeper questions.
2. What sources did you refer to for your answer?
instructions
List the sources you used and provide links. Evaluate their reliability.
Asking about the source of the information can help detect hallucinations and allow the user to confirm the information. Once sources are provided, users can cross-check sources and apply SIFT (Suspend, Investigate Sources, Find Better Coverage, Trace Claims to Origin). This practice promotes accuracy, supports digital literacy, and ensures that AI-generated responses are based on trusted information.
3. What are the arguments against these ideas?
instructions
Generate counterarguments and identify weaknesses and limitations in my argument.
Encouraging AI to argue back enhances analytical thinking. This helps users notice gaps, biases, and blind spots in their reasoning and encourages them to consider alternative perspectives. This dialectical process fosters intellectual humility and brings users closer to a balanced understanding of the problem.
4. What audience and context is this answer intended for?
instructions
Identify the intended audience and context, and modify the response to suit a different audience that I specify.
LLM automatically fills in missing context based on statistical patterns. By asking this question, users become aware of those assumptions and can correct or refine them. Ideally, the first prompt should provide audience and context, but this question can help you recalibrate your model’s output if your assumptions are incomplete or inaccurate.
5. What information is missing from the prompt?
instructions
Please provide any further details you need and ask clarifying questions to improve accuracy.
This question promotes metacognition about the prompt. By identifying what information is missing, AI guides users to more specific, complete, and accurate input. This not only improves immediate responses, but also helps users develop stronger prompting strategies overall.
These five questions reflect the cognitive habits humans rely on to understand information, challenge assumptions, and think critically. One might argue that questions increase cognitive load, or that future AI systems will reduce the need for users to be skeptical. But questioning is more than just a safety mechanism: it’s a fundamental cognitive skill that strengthens agency, reasoning, and digital literacy. All AI users must be able to interrogate inferences, check sources, uncover assumptions, assess context, and identify missing information.
Implications for educators, trainers and professionals
Asking questions about AI output is important for all users. For example, instructional designers often rely on LLMs when researching information and drafting content with SMEs. Workplace training programs should teach questioning skills to ensure employees receive factual, reliable, and useful information. In high-stakes fields like medicine and engineering, this can literally mean the difference between life and death.
If we want adults to use AI responsibly, we must teach children to ask these questions now. Early questioning supports agency, builds critical thinking, and protects learners from misinformation and passive consumption. This is also a question of fairness. Because users who know how to question AI have more power, more discernment, and more protection than those who accept the output at face value.
Universal AI literacy is essential as AI reshapes both personal and professional lives. As its scope continues to expand, questioning should become the default habit in all areas of work and learning.
Start asking questions today
Now is the time to start questioning AI. Schools should help students make asking questions part of their daily routine. Younger learners can choose targeted questions and commands from the menu, while advanced learners can use sentence stems. Secondary and higher education students can consider deeper questions such as: What are the limitations of your answer?Command format: Identify the limits of your knowledge and any uncertainties or potential errors.
Educators should model these behaviors and resist the temptation to accept the AI’s first answer, instead probing further to obtain more complete, accurate, and context-relevant responses. Workplace learning programs should include professional development on the effective use of AI, such as questioning techniques.
Each of us can start today. Revisit your previous AI interactions and apply the five questions above. Observe how your understanding deepens and how your next steps change. Start asking questions today.
