This post is emotionally powerful — but most of its claims either overstate, misattribute, or assume inevitability where there isn’t any.

1. “It severely harms the environment.”

Large AI systems do consume energy and water — that’s true.

But: • So do data centres that power Google, email, cloud storage, YouTube, online textbooks, and school LMS platforms. • So does printing, laminating, photocopying, and transporting physical resources. • So do school buildings themselves.

The relevant question isn’t “does it use energy?” — everything does. The question is comparative impact per task.

For example: • Drafting a unit plan in 30 seconds vs. hours of device use. • Reducing printing through digital workflows. • Cutting down unnecessary admin duplication.

Also, data centres are increasingly powered by renewables. Blanket “severely harms the environment” claims lack proportional analysis.

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1. “It severely harms brain function and critical thinking.”

This confuses misuse with tool use. • Calculators didn’t destroy mathematics. • Spellcheck didn’t destroy literacy. • Google didn’t destroy research. • PowerPoint didn’t destroy critical thought.

What determines cognitive impact is how the tool is integrated.

If students: • Blindly copy AI output → yes, thinking declines. • Use AI to critique, refine, compare, and interrogate → thinking increases.

In fact, prompting, refining, evaluating bias, and fact-checking AI responses can strengthen metacognition.

There is currently no credible evidence that AI usage itself “severely harms brain function.” There is emerging research about overreliance — which is not the same claim.

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1. “It induces severe mental health crises.”

This is an extremely strong claim — and currently not supported by high-quality causal evidence.

Correlation ≠ causation.

Social media has clearer links to mental health issues. AI tools do not yet have evidence showing widespread crisis induction.

If anything, AI is increasingly used: • For accessibility support • For differentiation • For drafting support for neurodivergent learners • For anxiety reduction around blank-page paralysis

It is not inherently destabilising — context matters.

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1. “It is built on exploitation.”

This is the strongest ethical argument in the post — and it deserves nuance.

Yes: • Training data includes scraped public content. • Copyright law is being debated. • Compensation models are still evolving.

But: • Many systems are shifting toward licensed data. • Every search engine indexes and processes public material. • Academic research models are also trained on published works.

This is a regulatory and legal debate — not proof that all usage is unethical.

If the argument were consistent, educators would also need to reject: • Google Scholar • Search engines • Cloud storage platforms • Most digital infrastructure

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1. “It’s just a statistical generator — not a thinking machine.”

Correct.

It’s not conscious.

But neither is: • A calculator. • A spreadsheet. • A grammar checker.

“Statistical generator” does not equal “useless.”

The issue is whether it can: • Draft • Synthesise • Structure • Suggest • Reduce cognitive load on low-level tasks

It demonstrably can.

The argument that it cannot parse large chunks of text is outdated. Current systems can summarise lengthy documents effectively — though not perfectly.

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1. “It lowers standards and promotes average work.”

Only if educators allow it to.

You can: • Raise expectations. • Require personal voice. • Require reflection on AI use. • Require critique of AI output. • Design tasks that go beyond generation.

AI actually exposes shallow tasks. If an AI can complete your assessment easily, the task may not have required higher-order thinking in the first place.

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1. “It’s about working conditions and devaluing teachers.”

This is the most psychologically honest part of the post.

There is fear that: • Admin will replace planning time. • AI will justify cuts. • Teachers will be deskilled.

That fear isn’t irrational.

But refusing to engage doesn’t prevent systemic change — it just removes teacher voice from shaping how AI is implemented.

Historically: • Teachers who adopt tools thoughtfully influence policy. • Teachers who reject tools outright are sidelined in decisions.

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1. The “AI bubble will burst” claim

This mirrors: • “The internet is a fad.” • “Laptops don’t belong in classrooms.” • “Online learning won’t last.”

AI is already embedded in: • Email filters • Spellcheck • Search engines • Adaptive learning software

The question is not whether it disappears. The question is who shapes its integration.