The AI Education Paradox: Answers are cheap, questions are priceless

After 7.5 million years of computation, Deep Thought reveals the answer: “forty-two.”

This was the “Answer to the Ultimate Question of Life, the Universe, and Everything” in The Hitchhiker’s Guide to the Galaxy. 

Coming up with answers to questions is reasonably easy, especially for such a big computer as “Deep Thought,” although in fairness taking 7.5 million years is a little slow by modern standards! When I asked ChatGPT it only needed a few seconds, although it did eventually ask me what I thought the answer was. 

What is far more difficult than answering questions is asking them. Which is why in Hitchhikers they go on to ask Deep Thought if it can produce “The Ultimate Question” to go with the answer 42. See* – spoiler, it doesn’t end well.

AI has all the answers?
Historically it could be argued that the educational model has been largely focussed on knowledge transfer, requiring students to absorb and regurgitate pre-determined facts and solutions. This model, while valuable when information was not so accessible, is however starting to creak under the pressure of new technologies such as GenAI. After all, what’s the point of teaching facts, and answers to questions when you have ChatGPT?

Although you could have made a very similar point about the internet, large language models are different. They are far more accessible and provide credible, if not always correct answers instantly, requiring little or no effort by the individual, which is of course is part of the problem.

This is not however a good argument to avoid teaching knowledge, because without it as a foundation it becomes almost impossible to develop those hugely important higher-level skills such as critical thinking and problem solving.  Dan Willingham, the Cognitive Scientists is very clear on this:

 “Thinking well requires knowing facts, and that’s true not simply because you need something to think about. Critical thinking and processes such as reasoning and problem solving are intimately intertwined with factual knowledge” Dan Willingham (edited).

But that’s not all, in addition to continuing to teach knowledge we need to pivot away from what GenAI does best, e.g. data analysis, repetitive tasks and answering questions, to focus on the areas in which humans excel.

Learning…….to beat AI
There is little doubt that GenAI is eroding human skills and as a consequence reshaping labour markets. The Tony Blair institute (The Impact of AI on the Labour Market) estimates something in the region of one to three million jobs could be displaced**. Take for example my own industry, Finance. GenAI can analyse bank statements, matching transactions with internal records, it can review historical financial data and identify trends and patterns as well as produce forecasts to support financial planning.

However, it’s not all bad news, although GenAI is excellent at processing vast amounts of data and providing rapid output, the quality of what is produced is very dependant on the questions asked, and humans are capable of asking great questions.

The three AI proof human skills

Skill no 1 – Asking the right questions. This may seem counterintuitive, surely “any fool can ask a question” – but can they ask a good one? The ability to ask the right question is far from trivial, it’s a spark for curiosity, and leads to growth and critical thinking. Socrates, built his entire philosophy on the principle of asking questions, he challenged assumptions looking for the underlying truth, and in so doing fostered a deep understanding of the subject.

Questions aren’t merely tools for obtaining answers, they are catalysts for refining our thinking, discovering new perspectives, and embracing intellectual humility.  

How to ask questions:

  • Move beyond simple “what” and “how” questions, ask “why and what if”
  • Break down complex inquiries into smaller, more manageable parts
  • Challenge assumptions, for example, “what are the counterarguments to this idea?” or “What would someone with a different perspective say?”

Skill no 2 – Evaluating the answer. While AI can produce insights, summaries, or responses that may seem well crafted, it lacks the uniquely human ability to contextualise, empathise, and discern subtleties. Think of evaluation in this context as – the “human act” of applying critical thinking, professional judgment, and emotional intelligence to assess the relevance, accuracy and practical value of AI generated content.

This process goes beyond mere interpretation. Human evaluation is, in essence, the bridge that ensures AI contributions remain meaningful and grounded in purpose. In simple terms, interpretation focuses on meaning, while evaluation focuses on judgment.

How to evaluate:

  • Have a clear criterion, be specific and decide on the method of prioritisation
  • Use multiple sources of evidence, combine numerical data with qualitative insights
  • Distinguish facts from assumptions, being careful to separate what you can prove from information that is speculative or anecdotal

Skill no 3 – Maintaining agency and an ethical perspective. Human agency requires the individual to act independently and make informed decisions about the AI output. Agency involves understanding AI’s capabilities and limitations, questioning its outputs, and actively deciding how it is applied rather than passively following its suggestions. By retaining oversight and exercising judgment, we ensure that AI remains a tool serving human needs, rather than a means for delegating responsibility.

Equally important is the ethical perspective. AI is devoid of inherent morality, able only to reflect the values embedded in its training data. Humans must actively define and enforce ethical boundaries, addressing biases and prioritising human values such as compassion and social responsibility.

How to maintain agency and an ethical perspective.

  • Educate yourself about AI, understanding how it works, including its capabilities, limitations, and potential biases
  • Develop an ethical framework. Create a set of guidelines to assess AI use, including its long-term impact on individuals, communities, and the environment
  • Be the Human in the Loop. Remember that you have ultimate responsibility both for the final decision and the ethical impact. This should never be delegated

Conclusion
While AI delivers instant results, true education goes beyond merely retrieving information. It requires deep understanding, a spirit of inquiry, and continuous personal growth. For students, this translates to mastering the art of asking thoughtful, probing questions, and developing the ability to critically evaluate responses.

Educators, have a more complex role. They must not only provide the necessary foundational knowledge base, but also teach and assess those uniquely human skills that AI will find hard to replicate – the ability to ask good questions, judge answers wisely, and maintain ethical agency.

Footnotes
*In Hitchhikers’ Deep Thought is unable to come up with the ultimate question, it needs a bigger and better computer, however it can buid it “one of such infinite complexity that life itself will form part of its operational matrix.” It’s called earth!
**The Impact of AI on the Labour Market report goes on to say that the job displacements will not occur all at once, but instead will rise gradually with the pace of AI adoption across the wider economy. Moreover, the rise in unemployment is likely to be capped and ultimately offset as AI creates new demand for workers, which pulls displaced workers back into the workforce.

Trust me …….. I’m a teacher

This month’s blog is about something especially important to me just now, its an essential component of any real and meaningful relationship – TRUST. Ask yourself how many people do you really trust, three, four probably not that many, a few close friends, and family perhaps. If you trust someone, you believe they are honest and sincere and wont deliberately do anything to harm you, in fact they will always have your best interests at heart. As a consequence, you are more likely to listen carefully to what they say, giving them significant influence over what you think and do.

Trust takes years to build, seconds to break, and forever to repair.” Amy Rees Anderson

Trust is also one of those intangible qualities that companies and organisations crave, and yet when it matters most, they often fail to keep their end of the bargain. A recent survey by PwC concluded that the trust gap is widening, here are a few other headlines:

  • 93% of executives agree that building and maintaining trust improves the bottom line
  • It’s getting even harder to build trust – executives are facing more hurdles than before
  • 86% of executives say they highly trust their employees, but only 60% of employees feel highly trusted

Who can you trust?
Ipsos the market research company has run a poll on trust in the professions for many years. Their 2023 report identified that the most trusted professions in Britain were: nurses, airline pilots, librarians, doctors, engineers, teachers, and professors. Perhaps not surprisingly the bottom three were politicians, government ministers and advertising executives. Business leaders somewhat disappointingly scored only 30%, just above estate agents! Looking at the list it seems that trust takes a backseat when power and money are part of the equation.

Trust is the glue of life. It’s the most essential ingredient in effective communication. It’s the foundational principle that holds all relationships.” Stephen Covey

Trust in education
Trust plays a pivotal role in education, influencing various aspects of the learning process. When you think about it students don’t know if what they are being taught is actually worth knowing. They simply trust that the teacher will select relevant content and use the best learning methods to deliver it.

We should probably distinguish trust from respect, authority, and reliance. Respect is where you hold someone in “high regard,” recognising their worth, you might of course trust them as well but its not essential. Authority on the other hand is more about power, a student will “do as they are told” but that doesn’t mean they will see the value in what they are doing. And lastly reliance, this is closer to trust but its still not the same, you can rely on a calculator to come up with the correct answer but you cannot trust it, that’s because there is no relationship.

Think of a situation where the teacher asks the whole class to attempt 10 questions for homework, the problem is that the students don’t see any value in this and think it’s a waste of time. But when they get home, they reflect on what they have been asked to do and complete the questions, not because they have changed their mind but because they believe that the teacher wouldn’t want them to do something that wasn’t in their best interests. The result is that the next time the student is asked to do something, they are more likely to oblige. Okay so this is a rather idealistic view of the teacher, student relationship but hopefully it shows that trust can reach well beyond the walls of a classroom.

What about the neuroscience
Trust is much greater in people with higher levels of oxytocin (OT), which although not classed as a neurotransmitter, (chemicals in the brain that help link neurons) for our purposes we can think of it as being similar. In one experiment individuals administered with OT were more inclined to trust others with their money compared to those given a placebo. If you want to increase levels of OT, but don’t want to give a massage! (physical contact can help), you should demonstrate that you care about the individual and are kind to them. Which when you think about it makes a lot of sense.

Trust is like the air we breathe – when it’s present, nobody really notices; when it’s absent, everybody notices.” Warren Buffett

Increased engagement and communication
In terms of evidence studies have shown that when students trust their teachers, they are more likely to engage in learning activities, seek feedback, and participate in class discussions (Roorda et al., 2011). This trust enables educators to create supportive learning environments where students feel safe to take risks, ask questions, and explore new ideas. In addition, trust between students and educators facilitates effective communication and collaboration. Research by Bryk and Schneider (2002) suggests that high levels of trust in schools are associated with improved teacher morale and greater job satisfaction.

Conclusions
You can of course be a good teacher without building trust, and a student doesn’t need to trust their teacher to learn but it can be empowering, motivational and in some situation’s life changing. After all, as a teacher what do you have to do, simply have the students’ best interests at heart, and take an interest, and any good teacher will do that. As for the student your role is to trust, which is of course is far more difficult.

To learn more about trust in learning – watch the 4m video – The key role trust plays in learning

My thanks to Monika Platz and her paper on Trust Between Teacher and Student in Academic Education at School which provided inspiration and insight for this blog.