Tag Archives: philosophy

AI is the Opium of the people – Cognitive Dependency

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A dramatic headline for what I believe could become a significant and damaging problem. Amid all the noise around AI, there’s something creeping up on us, it’s not making headlines or trending on social media but it is reshaping the architecture of the human mind – it’s called Cognitive Dependency.

It was of course Karl Marx, who famously said that religion is the opium of the people, not as a criticism but to highlight the comfort and relief religion brought by distracting from the hardship people experienced in everyday life. However much like opium, religion didn’t eliminate suffering, it simply made it easier to bear. The problem was that over time people lost their capacity to think for themselves, becoming reliant and potentially addicted.

TL;DR – the short audio version

Stay with me….

We live in a world that prizes answers over thought, output over process, and fast is always better than slow. Add to that the relentless pressure to succeed or in some instances simply survive, it becomes not only understandable but logical that people will reach for the easiest solution, regardless of the consequences.

And this is where I hope the parallels can be drawn. Just as opium offered relief in the 19th century from the challenges faced at that time, AI can do the same with the cognitive demands of a world moving too fast to keep up with. This is not about being lazy; the catalyst is exhaustion and a need to be successful or, at least seen to be so.  The danger may not at first be obvious, but similar to the observations of Marx, what begins as an easy solution becomes a quiet dependency and ultimately an amnesia. Over time, not only do you become devoid of your own ideas, but you completely forget what it means to think for yourself.

AI’s potential impact could be even more severe… AI undermining cognitive development, human agency, and critical learning processes for young people. Anthony Seldon, educator and historian

Cognitive offload or Cognitive dependency
But we need to make sure we don’t throw the baby out with the bathwater. This is not a general criticism of AI and its potential to erode our capacity to think, Its far more specific. AI in itself is not harmful, for now at least but, to better understanding how to work with AI and avoid creating problems for ourselves in the future we need to make a clear distinction between the two very different ways in which we use it. The first, as a tool to free up our mental power, this is called Cognitive offload. The second, as a surrogate for thinking, this is the more sinister Cognitive dependence.

Cognitive offload – The mental effort required to process and hold information in working memory is referred to as cognitive load. One of the reasons people struggle to learn is because they are trying to deal with too much information at any one time, reduce the load and learning becomes easier. A calculator is a good example of how technology can help. By outsourcing or offloading mental arithmetic, the mind is freed to focus on higher-order thinking. This is the use of AI to extend human capability, but without replacing human thought.

Cognitive dependency – Where cognitive offload removes some of the “clutter” freeing the brain to focus on more important ideas, cognitive dependence is far more invasive and results in a situation where the brain’s capacity to think deteriorates because AI is doing all the hard work. In this study Jinrui Tian and Ronghua Zhang) from Wuhan University found that greater AI dependence was associated with lower levels of critical thinking.

The sat nav is a good example of what this looks like in practice. When we follow a voice telling us where to turn, we are not navigating, we are being navigated. Over time, the mental map we once built through attention and experience becomes redundant. Studies (Louisa Dahmani & Véronique D. Bohbot) have shown that regular sat nav users demonstrate measurably reduced spatial awareness and struggle to recall routes they have driven down many times before.

This distinction really matters. A calculator leaves your mathematical reasoning intact, simply handling the “grunt work”.  But continual use of a sat nav, removes our capacity to orient ourselves possibly forever.  There is also something far deeper potentially happening, it’s what Andy Clark and David Chalmers called their extended mind theory. Eventually the tools we rely on stop feeling like tools, and become extensions of our cognitive selves, as intimate as memory or perception. This leads to a difficult question, if the machine is part of who we are, what happens when it’s taken away?

No sleepwalking please
AI is arguably the most transformative technology we have ever seen, and its potential to enhance learning, expand access, and accelerate understanding is genuinely exciting. But as educators and learners, we need to be aware of the problems. A generation that outsources its thinking doesn’t just lose a skill, it loses a sense of self, that quiet certainty that your thoughts are your own.

The good news is that we can do something about it. The question is not whether AI belongs in education, it clearly does. But we need to recognise that there is a problem and then begin to change attitudes and methodologies to combat the negative implications. In practice this might look like designing assessments that reward process over output, asking students to show their reasoning before they reach for AI assistance, or building in regular “unplugged” tasks where thinking has to take place without the support of technology. It means teaching students not just how to use AI but when not to, and helping them to develop the self-awareness to know the difference.

We built tools to save us time so we could think more. Let’s make sure that’s still what we’re doing.

Dedicated to Clare Finch – Wife, Mother, Friend, Educator and a great teacher.

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

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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. 

If you dont have time to read this months blog – listen to my AI alter ego summarise the key points.

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. 

“I think the problem, to be quite honest with you, is that you’ve never actually known what the question is.” So, once you know what the question actually is, you’ll know what the answer means.” Deep Thought

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.

“Millions saw the apple fall but Newton was the one who asked why.” Bernard Baruch

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.

“Successful people ask better questions, and as a result, they get better answers.” Tony Robbins

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

“A prudent question is one half of wisdom.” Francis Bacon

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.

“True genius resides in the capacity for evaluation of uncertain, hazardous, and conflicting information.” Winston Churchill

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.

“All human knowledge takes the form of interpretation.” Walter Benjamin

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.

The purpose of learning – Wisdom? Reflections on 30 years

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I have always thought that wisdom was something slightly magical, even biblical, reserved for those who have travelled the world in search of the secrets and meaning of life.

But in reality, it’s far less mystical and is more likely the result of a lifetime or simply a longtime of “good learning”. 

This year marks my 30 years with Kaplan a professional education company here in the UK and I am leaving for pastures new. This has inevitably meant I have been doing a lot of thinking about the past, reflecting, and asking some fundamental questions such as, what do I know now that I didn’t know 30 years ago, what has been my most important lesson, and of course the classic, what do I know now that I would share with my younger self? So, I hope you will allow me this slightly self-indulgent post about wisdom.  

What is wisdom?
There seems to be no single definition of wisdom, although all agree that it is much more than simply possessing knowledge. There is also a commonly held view that intelligence plays a part largely because if you are intelligent you are able to solve problems and learn from experiences, but it would be wrong to conclude that intelligent people are wise.

“A Clever person solves a problem. A wise person avoids it.” Albert Einstein

A simple definition is probably all we need – “Wisdom is the ability to make sound judgments and decisions based on knowledge, experience, and understanding.” And when you read that back, wisdom becomes far more accessible and less mysterious. In fact, who wouldn’t want to make sound judgments every single day – We all need wisdom.

“Knowledge is knowing a tomato is a fruit. Wisdom is not putting it in a fruit salad.”

But the definition gives little away in terms of what is meant by knowledge, experience and understanding.  John Vervaeke, the philosopher, and cognitive scientist goes a little further by saying that to be wise you need the ability to identify what is relevant from the vast amount of information we are exposed to. “Relevance realisation” helps us navigate complexity and make sense of our world, but to do this you need to pay attention and challenge what you see, continually looking for feedback. This is an example of thinking about how you are thinking or metacognition, reflecting on what was momentarily in your mind and asking questions as to its accuracy, your bias and prejudice. And when you can do that, it becomes possible to develop insight, the aha” moment that comes from a deep understanding, revealing previously unseen connections.  

Okay, that might be a little too much detail but I think it shows that in order to develop wisdom you need the ability to challenge your own thinking, in search of a greater and deeper understanding.

Wisdom and age

“Knowledge in youth is wisdom in age.” Proverb

The relationship between age and wisdom is nuanced and multifaceted. While age can contribute to wisdom, it is not an absolute guarantee. Wisdom, can be accumulated over time as a result of having different life experiences, but its not necessarily the experience that creates wisdom, it’s what you learn from it. Additionally, with age often comes a greater capacity for reflection, you may simply have more time to integrate your experiences into a broader understanding and as consequence develop that all important insight. Emotional regulation also tends to improve with age, contributing to more thoughtful and less emotional and reactive decision-making.

However, it is important to acknowledge counterpoints that some cognitive abilities for example problem-solving and processing speed, decline with age. In fact, studies from the Berlin Wisdom Project suggest there is a plateau of optimal wisdom performance in middle and old age, with some evidence of wisdom decline starting at the age of 75.  One interesting aside, wisdom tends to correlate with less loneliness. In a study from the University of California, San Diego, in 2020 researchers found that for middle-aged and older adults wisdom warded off the worst effects of loneliness.

In conclusion, it’s not necessarily age that helps you develop wisdom. Its just that you have had more life experience and time on which to reflect together with a greater inclination to do so.

How to acquire wisdom
To think that you can provide an instruction manual for wisdom is at best ambitious and more likely foolish, but there might a few lessons we could learn that will move us in the right direction. A good starting point might be to ask a couple of experts:

  • Confucius said “By three methods we may learn wisdom: First, by reflection, which is noblest; Second, by imitation, which is easiest; and third by experience, which is the bitterest.”
  • And Socrates “I am the wisest man alive, for I know one thing, and that is that I know nothing.”

From these “wise words” we can perhaps extract some of the traits of wise people. Wisdom comes from:

  • Reflection – is the process of introspectively examining and evaluating your thoughts, experiences, and actions. It’s a continuous process requiring a creative and inquisitive mind, questioning assumptions and seeking new perspectives. Reflection is an essential component of both learning and wisdom.
  • Experience – you need to have had some interesting life experiences on which to reflect. It is however not necessary to have “seen it all,” only that you questioned, challenge and thought about the experiences you have had.
  • Humility – Socrates went around asking people questions about justice, truth, and wisdom and found that despite them thinking they knew lots, in reality they were ignorant. To be wise you need to reach a sufficiently high level of questioning that you find your own level of ignorance, whilst at the same time not slipping into becoming arrogant.
  • Although not derived directly from the quotes, we should include Virtue – this is about consistently choosing to do what is right and good. It requires perspective, the ability to see things from the point of view of others as well as honesty, courage, kindness, and fairness.

“Wisdom is not a product of schooling but of the lifelong attempt to acquire it.” Albert Einstein

30 years later
What a long time 30 years is, but so far it has been a real privilege to work with good people in an industry that helps people learn, and get a chance to change lives for the good. If I’m honest It wasn’t what I set out to do but its not worked out to badly.

And now to the hardest part, how would I answer those three questions I posed at the start?

  • What do I know now that I didn’t know 30 years ago – in some ways this is the easiest one because I have learned so much. But if I had to pick one thing it would be the understanding I now have as to how learning works. This has served me well in both my teaching and wider career in education.
  • What has been my most important lesson – work hard, have focus and purspose but try to be kind, make friends, and don’t fall out with people, life’s too short.
  • What do I know now that I would share with my younger self – A couple of things I guess, firstly that Socrates was right, “I know that I know nothing.” This is not so much about humility but a recognition that even when you get to a level of competence or expertise, there is always another higher-level waiting for you. And secondly don’t compare yourself with others, only with yourself, if you’re moving forward that’s good enough.

I cant claim the above as wisdom, but give me another 30 years and maybe I will have something for you.