First the Google Effect and Now This: Will AI Diminish Our Ability to Reason?

Introduction: The Google Effect and Its Legacy

When search engines like Google revolutionized access to information, they brought unprecedented convenience but also unforeseen consequences. As people began relying on external sources to store and retrieve knowledge their ability to retain and deeply process information diminished. Not only that, people’s attention spans shortened. This phenomenon, now known as the “Google Effect,” demonstrated how tools designed to enhance our thinking can sometimes erode it.

Today, artificial intelligence (AI) is poised to transform education and productivity on an even greater scale. AI promises not only convenience but also the ability to tackle complex problems, generate insights, and accelerate creative work. But this promise comes with deeper risks, not just to memory and attention, as with the Google effect, but to our capacity for reasoning and creative problem-solving.

A recent study by the University of Toronto highlights these concerns. While participants using AI demonstrated increased efficiency, without it they produced similar, predictable answers modeled after the AI's logic, a phenomenon called homogenized thinking. That is, their thinking became uniform and formulaic. The findings raise a critical question: as we integrate AI into education and everyday life, are we at risk of losing the very skills that define human intelligence?

This article explores that question, examining the interplay between creativity and reasoning, the limitations of AI, and how educators may find themselves on the front lines when it comes to fostering the uniquely human skills that AI cannot replicate. It’s not about resisting AI but about embracing it thoughtfully, putting thinking first to ensure that we, not the tools we create, remain the architects of our future.

The University of Toronto Study: What’s at Stake

In 2024, researchers at the University of Toronto released a groundbreaking study that examined how large language models (LLMs), such as ChatGPT, influence human problem-solving. The study was straightforward and its results significant.

The researchers designed tasks requiring participants to tackle a battery of problems. 1100 participants were randomly split into three groups, with two groups receiving AI assistance and the other working independently. Of the AI-assisted groups, one was given unrestrained access to the AI tool, the other group was coached by the AI model to arrive at the answers themselves. Predictably, the groups using AI completed their tasks more efficiently. However, this efficiency came with a cost. When asked to approach similar problems without the help of AI, the participants who had previously benefited from AI assistance performed badly compared to the participants who’d had no AI help in the preliminary exercises. Not only that, their solutions were notably less original and more uniform compared to those who’d never used AI. It was found that the participants who worked with AI mirrored the patterns and logic modeled by the AI tool, creating solutions that, while efficient, lacked the creative diversity demonstrated by their peers.?

These findings highlight a critical concern, that reliance on AI can homogenize thought processes, even when the AI is removed. This observation is understandable given AI’s strengths - it excels at producing logical, safe outputs based on established patterns. But also reveals AI’s limitations as a source of genuinely creative output.

The implications extend far beyond the study itself. Creativity and critical thinking are not optional skills, they are - and always have been - the backbone of human innovation and adaptability. The risk of developing homogenized thinking is particularly troubling in education, where developing critical thinking skills is - or should be - a fundamental goal. If students come to rely too heavily on AI, they may never foster the ability to think independently, solve complex problems, and approach challenges with originality.

This risk, however, is not confined to the classroom. Industries that rely on creativity and innovation, from technology to design and beyond, may also face challenges if AI-driven efficiency begins to overshadow originality.

But what if the problem isn’t inherently in the AI models, but how we choose to use them? Many advocates claim that when integrated thoughtfully, AI can become a powerful ally in both innovation and education. Perhaps the greater challenge facing us then, greater than the AI models themselves, is how to define AI’s role in the creative process, ensuring it complements rather than replaces the cognitive processes that make us uniquely human.

Given the risks, it’s most critical now more than ever that our schools and colleges lead the way in shaping how the next generation of innovators and leaders approach the use of technology.

Homogenization in Learning: Rooted in an Outdated Model

The idea of homogenized thinking isn’t new, it has deep roots in the traditional education system. Modern education, as we know, was shaped during the Industrial Revolution, a time when efficiency and standardization were paramount. Schools were designed to produce workers who could follow instructions, retain information, and perform repetitive tasks with precision. This system valued rote learning and conformity, rewarding students who excelled at memorization and discouraging creative or unconventional approaches.

Over time, this model of education led to a narrow definition of intelligence, one that equates academic success with the ability to memorize facts and reproduce them accurately. Students who thrived in this system were praised and rewarded, while those who struggled to conform were often overlooked or undervalued. The emphasis on memorization often came at the expense of fostering critical thinking, creativity, and problem-solving skills. These lost traits are hard to quantify but vital for success in an unpredictable world.

The University of Toronto study highlights how these patterns persist, even in the context of AI. The participants who worked with AI tools mirrored the models’ structured, predictable outputs, much like students who learn to mimic the methodologies taught by their instructors. In both cases, the result is efficiency at the cost of originality. Standardized testing further reinforces this trend, training students to solve problems in ways that align with “correct” answers while discouraging risk-taking and exploration.

AI’s reliance on predictable, logical outputs amplifies this tendency. As the study revealed, participants who relied on AI not only adopted its structured approach but struggled to think creatively when the AI was removed. This mirrors the limitations of the traditional education model which teaches students to arrive at answers by the shortest, most predictable path, rather than encouraging diverse and unconventional problem-solving strategies.

But here’s an open secret, one we’ve known for almost as long as there’s been an education system: Many of history’s most innovative thinkers, from entrepreneurs to artists, have succeeded precisely because they didn’t conform to traditional metrics of success. The success stories of multiple school ‘underachievers’ and rebels who went on to build thriving businesses or create groundbreaking art underscore an important truth: intelligence is not necessarily defined by the ability to follow tried-and-trusted rules, but by the capacity to make non-obvious connections and think beyond the expected.?

Along with the rise of AI we’ve seen an ample and public celebration of its undeniable strengths and advantages. But left unchecked, especially in education settings where reason is nurtured and developed, AI could reinforce tendencies inherent in outdated education practices. Tendencies that produce students who excel at mimicry but lack the ability to think independently or creatively.?

In considering all that AI means for us and what it offers, we should also take the opportunity to rethink how we are to define and nurture human intelligence.?

Creativity and Reasoning: The Cornerstones of Intelligence

What does it mean to be intelligent? Historically, intelligence has been associated with academic achievement or the ability to solve complex problems. But intelligence is much more dynamic and multifaceted. It emerges in the interplay between creativity and reasoning, two of the cornerstones that define our capacity to innovate, adapt, and thrive in a complex world.

At its heart, creativity is the ability to combine or connect things in novel ways, producing results that are unexpected or original. It’s the spark that drives breakthroughs in fields as diverse as mathematics, music, and sports. A mathematician might explore a radical new theory, just as a musician might compose a piece unlike anything heard before, or an athlete might develop an unconventional strategy that shifts the course of a game. What unites these examples is the ability to see possibilities beyond the obvious, to reach for connections that others might overlook.

Reasoning, on the other hand, is the framework that gives creativity its power. It involves recognizing and validating each step in a process, ensuring that ideas move from the abstract to the actionable. Without reasoning, creativity risks becoming chaotic or unproductive, a burst of inspiration that lacks direction or impact. Together, creativity and reasoning form the foundation of intelligence, each informing and strengthening the other in a dynamic, iterative process.

This synergy between creativity and reasoning is essential for what we often call “creative problem-solving.” The University of Toronto study highlights how participants who worked independently and without AI assistance leaned toward this approach. They tackled their problems with originality, generating diverse solutions that reflected a balance of imaginative thinking and logical evaluation. In contrast, participants who relied on AI tended to mimic its structured approach, producing results that were efficient but lacking in creativity.

AI’s limitations here are not surprising. AI generates outputs based on patterns and probabilities, making it an invaluable tool for analyzing data or testing hypotheses within established frameworks. But while AI excels at logical progression and structured reasoning - following logical steps to solve problems efficiently - it struggles with the kind of non-linear thinking that characterizes human creativity. AI cannot originate the surprising or novel connections that define creative breakthroughs. This distinction is critical for understanding both the potential and the limitations of AI in creative problem-solving.

When AI is overused or relied upon too early in the learning process, it ingrains a process of structured reasoning at the expense of originality. Think of it as taking the high-speed train from Paris to Bordeaux on a regular basis. If this is the only way you travel between the two cities you’ll soon be thinking of this as the only logical way to travel. You’ll become familiar with the route and the stations along the way. You and everyone else who uses the train the way you do. The result is homogenized thinking, not unlike those students in the University of Toronto study, who became so accustomed to AI’s structured patterns that they struggled to think differently when the AI was removed.

Recognizing these dynamics is the first step. By nurturing creativity and reasoning together, educators can prepare students for challenges that require more than rote learning or automated responses. The goal is not to dismiss AI but to integrate it in ways that complement human intelligence, allowing creativity and reasoning to thrive as cornerstones of innovation.

AI as a Tool

AI holds immense potential as a tool, but like any tool, its value depends on how and when it is used. The plow revolutionized agriculture, but a farmer who begins by plowing without understanding the soil, the climate, or the crop they want to cultivate is unlikely to succeed. Similarly, if educators and students design learning processes around what AI can do, rather than focusing on the human intellectual effort that must come first, they risk losing the deeper purpose of education.

The true strength of AI lies in its ability to complement human ingenuity, not replace it. Tools like ChatGPT or other large language models can analyze vast datasets, offer insights, or explore patterns in ways that enhance what humans already bring to the table. However, for AI tools to be at their most effective, we first need to grapple with questions, ideas, and problems independently. This foundational work is the intellectual planning - the equivalent of understanding the soil before the plow touches the earth.

If AI is introduced too early in a learning or innovation process, it risks short-circuiting this essential stage. We end up bypassing the struggle of working through ideas, and instead rely on AI to generate “solutions” for the sake of efficiency. These solutions may appear complete but they will inevitably lack depth and originality. Over time, this can erode our ability to think critically and creatively, leaving us dependent on the tool rather than empowered by it.

Our focus then, whenever innovation or novel solutions are called for, must be to cultivate a mindset where AI is used only after we have engaged deeply with the challenge in front of us. In education settings, educators can encourage this by designing learning activities that begin with independent exploration. This approach ensures that AI serves as a partner in inquiry, not a substitute for intellectual effort.

What happens before AI is engaged is just as important as what happens after. When students approach AI with their own groundwork already laid, they are better positioned to evaluate its outputs critically. They can question the validity of its suggestions, identify where it aligns with or diverges from their thinking, and use it as a springboard to take their ideas further. In this way, the tool amplifies their creativity rather than steering or limiting it.

Ultimately, the value of AI in education depends on educators’ ability to put thinking first. The tool should be an enabler, not a driver. By prioritizing human-led inquiry and emphasizing the role of independent intellectual effort, educators can ensure that AI supports learning in a way that aligns with its true potential, enhancing rather than replacing the uniquely human processes of creativity, reasoning, and exploration.

The Risks of AI Over-Reliance

When it comes to AI, over-reliance is not just a question of “how much” but also “how often” and “how early.” As with any powerful tool, the temptation to lean heavily on AI can overshadow its potential to complement and enhance human effort. The risks of this dependency are significant and multifaceted.

One of the most immediate risks is homogenized thinking. AI models, by design, generate outputs that are predictable and logical, often reflecting patterns and norms in their training data. When we rely too heavily on these outputs, our own problem-solving begins to mimic the tool’s structured approach. The result? Uniformity in thought and a diminishing ability to think creatively or take intellectual risks. As the University of Toronto study showed, even when AI is no longer present, its influence lingers, shaping how the participants approached problems in ways that lacked originality.

This risk is compounded by AI’s propensity for generating false or misleading information, and for the biases inherent in its training. When we uncritically accept AI outputs, we may inadvertently perpetuate inaccuracies or reinforce stereotypes, creating a cycle where flawed reasoning goes unchallenged. Worse, this can erode our ability to discern credible information, a skill that is increasingly vital in today’s information-rich world.

Mitigating these risks requires both vigilance and strategy. In class, educators should equip students with the skills to recognize bias and misinformation, encouraging them to question AI outputs critically and challenge their assumptions. Activities such as debating the validity of an AI-generated response or exploring its potential biases can foster deeper engagement and sharpen critical thinking.

In addition to teaching students how to navigate these challenges, educators can turn to technological solutions to reduce risks. Closed AI systems, for example, offer a safer alternative to open models in educational settings. These systems provide more controlled environments, aligning their outputs with educational values and reducing the likelihood of hallucinations or exposure to harmful content. By combining the thoughtful use of technology with critical engagement, educators can ensure that AI supports learning without undermining its goals.

It doesn’t serve us to reject AI outright, but rather to integrate it in ways that maintain the primacy of human reasoning and creativity. By addressing the risks of over-reliance head-on, educators can ensure that AI serves as a complement to learning, not a crutch. This balance is crucial for preparing students to navigate a world where innovation depends on their ability to think critically, challenge assumptions, and take intellectual risks.

Head First Into Creativity and Reasoning

Fostering creativity and reasoning isn’t about following a rigid formula, it’s about creating an environment where exploration and critical engagement are rewarded. Educators and corporate trainers don’t need to reinvent the wheel; small, intentional changes can make a significant difference. The goal is to spark curiosity, encourage diverse perspectives, and encourage the confidence to engage in independent thought.

Start With Open-Ended Challenges One way to stimulate creativity is to present challenges with no single “right” answer. Open-ended challenges invite students to think divergently and explore possibilities rather than search for predetermined solutions. For example, a prompt like, “How might we improve on this design?” pushes students to combine creative thinking with practical reasoning as they imagine, hypothesize, and evaluate their options.

The Power of Inquiry-Driven Learning Inquiry-driven learning is a well-known classroom strategy that encourages students to engage deeply with questions. But watch out for traps. The question “Why is this the way it is?” is firmly rooted in the ‘knowledge’ paradigm and may encourage learners to just ‘look it up’. “How would you achieve the same result with different resources?” helps learners break out of rote responses and approach problems from fresh perspectives, opening the door to unexpected ideas while fostering a sense of curiosity.

Provocations That Break Patterns Edward de Bono’s concept of “provocation” is a powerful tool for disrupting conventional thinking. The idea is to make a preposterous or illogical statement and then ask the kinds of questions you normally would make if the statement was true. For example, posing a provocation like “Trees talk!” to a class of fourteen year old students might seem whimsical, and since trees don't have mouths and ears it encourages them to consider in what ways this could be true. Thinking of these things may lead? to ‘accidental’ learnings in areas such as communication, ecosystems, or the ethics of interaction.

Provocation is just one tool worth developing into a creative habit that teaches students to think beyond and before the use of AI. Educators should be on the lookout for others that resonate with their learners.

Leveraging AI as a Thought Partner When integrated thoughtfully, AI can play a role in fostering creativity and reasoning, provided it’s introduced after students have wrestled with ideas on their own. Once students have brainstormed ideas independently or in groups, they can then use AI to refine their ideas or explore alternate perspectives. This sequencing keeps learners in control of the creative process while using AI as a partner for deeper inquiry.

Teaching Learners to Critique AI An essential skill in the age of AI is learning to challenge its outputs. Activities that involve evaluating AI-generated responses for bias, limitations, or inaccuracies can sharpen students’ critical thinking. For instance, a “debate the AI” exercise might have students argue for or against an AI’s suggestion, teaching them to engage with technology critically and thoughtfully.

Play and Collaboration as Learning Tools Games and collaborative activities are often overlooked as educational strategies, but they are fertile ground for developing creativity and reasoning. Strategy games like chess or Settlers of Catan encourage planning and decision-making, while cooperative projects emphasize teamwork and diverse perspectives. Analogue games, in particular, remove AI from the equation entirely, allowing students to focus on their innate problem-solving abilities.

Creating a Culture of Exploration Building an environment where learners feel safe taking intellectual risks is key. This means encouraging autonomous inquiry within structured challenges. It also means celebrating the process of exploration by valuing how students approach problems rather than just rewarding them for the solutions they arrive at.

Educators Need to be Equipped for the Journey Many of the activities that support the development of creative reasoning would be out of place in a traditional ‘right answers rewarded’ classroom. For the shift in focus to happen, educators will need support from administrators and parents. Trailblazers are also going to need each other’s support as it’s unlikely that many professional development programs yet exist to offer guidance on integrating AI thoughtfully while prioritizing human creativity. Networking with like-minded educators to share strategies and successes will foster a collaborative approach to re-imagining education.

A Final Thought on Balance Creativity and reasoning are not opposing forces, they’re partners. By diving headfirst into activities that nurture both, educators can ensure students are prepared for a future that demands not just knowledge, but ingenuity, adaptability, and critical insight.

Conclusion: Shaping the Future of Education in the Age of AI

As we navigate an AI-driven world, the role of educators has never been more critical. The opportunities AI presents are vast, it can enhance learning, expand inquiry, and provide tools to tackle complex challenges. But these opportunities come with risks, particularly the danger of homogenized thinking and over-reliance on AI’s structured outputs. The challenge for education is clear, embrace AI’s potential while ensuring that human creativity and reasoning remain at the forefront.

In the early days of computers, knowing how to use one was an advantage. But that advantage was short-lived. Soon, such knowledge became essential, and the real advantage lay in understanding and knowing how to manipulate the complexities of software. The same will be true for AI. Understanding the basics of AI will become commonplace and the key transferable skill will be the ability to outperform AI’s basic outputs by adding uniquely human ingenuity and creativity. Teaching this skill will prepare students not just to coexist with AI but to excel in partnership with it.

Understanding the basics of AI will become commonplace and the key transferable skill will be the ability to outperform AI’s basic outputs by adding uniquely human ingenuity and creativity.

AI has also transformed the way we interact with information. Before AI, machines and the internet merely stored information, leaving users to provide context and purpose. Now, AI can interpret context and deliver targeted results faster and more efficiently than ever. This evolution renders old teaching paradigms, such as a focus on memorization and information retrieval, obsolete. Instead, educators must prioritize teaching students how to use information creatively, making connections and generating insights that go beyond AI’s capabilities. Creativity, as much as reasoning, can be taught, and must be taught, to avoid the stagnation that comes from uncritical reliance on AI.

Creativity and reasoning are the cornerstones of human intelligence, enabling us to navigate complexity and lead with ingenuity. More than just preparing students for a future with AI, educators have a pivotal role in ensuring learners transcend AI’s logic to become active creators and critical thinkers.

What Do You Think?

As a parent or educator, do you believe it’s important to bring these kinds of interventions into the education system? Would you like to see the direction of education shift to prioritize creativity and critical thinking alongside AI integration? Feel free to share your thoughts below!