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You are listening to Smarter

Articles, long form writing on

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technology, governance, and the

human cost of the things we build.

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This week's article is AI Exposed the Lie.

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Schools never taught critical thinking.

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The relationship between artificial

intelligence and critical thinking in

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education has sparked intense debate.

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With recent surveys and studies shedding

light on the paradoxical dynamics at

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play, students, teachers and educational

institutions are grappling with the

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implications of AI tools like Chat, GPT,

which offer unprecedented capabilities,

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but also raise profound questions about

the future of learning and cognition.

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To understand the full scope of

this issue, we must examine systemic

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flaws in education, the role of AI

and the potential paths forward.

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A December, 2025 survey conducted by

the Rand Corporation's American Youth

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Panel revealed a striking paradox.

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Nearly 70% of middle and high school

students believe AI is eroding

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their critical thinking skills.

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Yet their use of AI for homework

continues to rise in just seven months.

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AI usage among students

climbed from 48% to 62%.

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This is not a case of

simple cognitive dissonance.

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Students clearly understand the

problem, but feel trapped in a

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system that incentivises AI use.

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The logic from a student's

perspective is straightforward.

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Grades determine university

admissions, which are perceived

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as crucial for life outcomes.

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If peers are using AI to achieve

higher grades, opting out feels

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like a competitive disadvantage.

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For example, a 16-year-old juggling

multiple GCSEs, a part-time job and

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extracurricular activities, sees

classmates producing polished coursework

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in half the time by using chat GPT.

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Teachers, overwhelmed and underresourced,

often cannot distinguish between AI

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generated and student generated work.

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In this environment, refusing to use

AI is seen less as a principled stand

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and more as an act of self-sabotage.

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Teachers are also acutely aware of

the challenges posed by ai, but their

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concerns reflect a different perspective.

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A 2025 survey by the American

Association of Colleges and Universities.

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Found that 95% of faculty feared

that generative AI would increase

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student overreliance on technology.

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Additionally, 90% believed AI

would diminish students' critical

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thinking skills, and 83% worried

about its impact on attention spans.

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Cheating has also become a significant

concern with 78% of faculty reporting

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an increase in academic dishonesty.

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Since AI tools became widely accessible,

unlike students who see AI adoption

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as a rational response to systemic

pressures, teachers are often surprised

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by the extent of its impact, yet their

reactions highlight a deeper issue.

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The educational system's longstanding

failure to prioritize critical thinking,

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a failure that predates the advent of ai.

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The erosion of critical thinking

in education did not begin with ai.

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Decades of policies emphasising

standardised testing over meaningful

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learning have systematically devalued

higher order thinking skills.

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In the United States, the No Child Left

Behind Act of: 2001

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Schools were judged based on students'

performance, on standardized tests with

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poor scores leading to funding cuts, staff

dismissals, and even school closures.

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The predictable result was teaching to the

test where instruction focused narrowly

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on the content and formats of state exams.

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This approach have

devastating consequences.

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Subjects not covered by standardized

tests such as art, music, and physical

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education were marginalized or eliminated.

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Recess was sometimes cut to allow

more time for test preparation.

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The cycle of sit, get, spit, forget

became the norm where students passively

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received information, regurgitated

it on exams and promptly forgot it.

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The United Kingdom followed a similar

trajectory with successive reforms

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emphasizing accountability metrics.

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Teachers in England report spending

significant time on assessment,

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preparation, and administrative tasks,

leaving little room for inquiry driven

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teaching while the Department for

Education issued guidance in: 2025

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emphasizing the importance of critical

thinking alongside AI structural reforms

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to support this goal, remain lacking.

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Paolo Freire's concept of the

banking model of education

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described in his 1968 work.

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Pedagogy of the Oppressed

aptly captures this dynamic.

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In this model, teachers deposit

knowledge into passive students who

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are expected to memorize and repeat it.

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Freire argued that this approach

stifles critical consciousness and

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prevents students from becoming active

participants in their own learning.

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The accountability frameworks of NCLB

and similar policies reinforce this

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model, prioritizing compliance over

curiosity and memorization over analysis.

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AI tools exacerbate these systemic

issues by enabling cognitive

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offloading the process of delegating

mental tasks to external resources.

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A 2025 study by Michael

Gerlich found a strong negative

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correlation between frequent AI

use and critical thinking skills.

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Younger participants age 17 to

25 were particularly affected

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showing higher dependency on AI

and lower critical thinking scores.

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However, the study also revealed that

advanced educational attainment correlated

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positively with critical thinking.

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Suggesting that education can mitigate

some of the cognitive costs of AI

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reliance if it is designed to do so.

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The distinction between scaffolding

and substitution is crucial here.

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Scaffolding supports learning by

temporarily aiding students, helping

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them develop internal capacities.

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Substitution, on the other hand, replaces

the need for those capacities altogether.

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The current educational system in its

rush to adopt AI has done little to

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ensure that these tools act as scaffolds.

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Rather than substitutes

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Teachers are at the center of this

complex dynamic facing, contradictory

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demands with limited resources.

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Nearly half of teachers in the

United States and the United

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Kingdom report chronic burnout.

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They're expected to integrate

AI into their teaching while

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managing large class sizes, meeting

accountability targets, and addressing

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students' mental health challenges.

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AI tools are often marketed as solutions

to these challenges promising to save

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teachers time by automating tasks

like grading and lesson planning.

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While this potential is real, the lack

of consistent AI policies and training

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means that many teachers are unprepared

to use these tools effectively.

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As a result, AI adoption often

occurs out of necessity rather

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than careful pedagogical planning.

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The rapid adoption of AI in schools

has been marked by inconsistency.

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In early 2023, New York City's Department

of Education banned ChatGPT citing

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concerns about academic integrity.

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Yet within months, the ban

was reversed as schools faced

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pressure from industry lobbying.

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Parental expectations and

the realization that students

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were already using AI at home.

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This pattern of banning and then

embracing AI reflects a lack of clear

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strategy and highlights the influence

of market forces on educational policy.

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The AI in education market valued

billion in: 2025

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to grow to $137 billion by 2035.

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Major tech companies like Microsoft

and Google are heavily investing in

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this space, shaping the educational

landscape in ways that prioritize

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efficiency and scalability, over the

deeper, more human process of learning.

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Not all AI tools are created equal.

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Khan Academy's Khanmigo launched in 2023,

offers a Socratic approach to learning.

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Guiding students with questions and hints

rather than providing direct answers.

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This design encourages active engagement

and reduces the risk of cheating

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Students who use Khanmigo report

feeling a sense of accomplishment

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as they actively participate

in the problem solving process.

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This example demonstrates that AI

can support critical thinking when

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designed with educational goals in mind.

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However, such tools require institutional

investment teacher training and a

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supportive pedagogical framework.

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Resources that many

schools currently lack.

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International comparisons reveal

stark differences in how countries

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approach AI in education.

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Finland and Singapore, for example, have

integrated AI into their systems while

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maintaining a focus on critical thinking.

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Finland emphasizes teacher autonomy,

minimal standardized testing and

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holistic education, while also

investing in AI literacy programs.

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Singapore aligns AI adoption with

its broader smart nation strategy,

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focusing on customization and

critical use rather than replacement.

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In contrast, the United States and

United Kingdom have prioritized rapid AI

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adoption and market-driven solutions often

at the expense of thoughtful pedagogy.

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The OECD's PISA 2022 assessment highlights

the consequences of these choices showing

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that countries with inquiry-based learning

frameworks produce students better

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equipped for higher order cognition.

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The Rands data reveals a systemic trap.

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Students are not failing the system.

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The system is failing them by

prioritising measurable outputs

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over meaningful learning.

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The educational model has created

conditions where using AI for

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polished outputs is the most

rational choice for students.

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The issue is not laziness or

moral weakness, but a rational

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response to systemic incentives.

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Addressing these challenges

requires systemic change.

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Banning AI is neither

practical nor effective.

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Instead, education systems must reduce

reliance on standardized testing

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and foster inquiry-based learning.

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Invest in AI tools designed to scaffold

learning like Khanmigo, provide

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comprehensive teacher training on

AI integration, rethink assessment

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frameworks to award the process of

thinking rather than the final product.

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Ultimately the goal must be to

cultivate independent thinkers

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capable of navigating complexity

without over-reliance on technology.

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This requires a fundamental

shift in the values and

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priorities of education systems.

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The most striking insight from the

Rands data is the honesty of students.

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They see the systemic flaws more

clearly than the adults in charge.

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Their concerns about AI reflect a deeper

awareness of an educational model that has

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long prioritized outputs over learning.

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Addressing this challenge demands

not just technological solutions,

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but a structural reckoning with the

purpose and values of education itself.

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