The deadline isn't when AI outsmarts us – it's when we stop using our own minds

AI as Tool vs Mental Crutch

• Many see LLMs as powerful accelerators for learning, prototyping, and “mechanical” work, letting them reach problems they’d never have touched before.
• Others report clear cognitive atrophy: over-reliance for coding, writing, or reasoning leads to weaker recall, poorer debugging, and shallow understanding.
• Several frame this as a distribution: a minority will use AI as a serious tool; the majority as passive entertainment or shortcut—much like internet vs web developers, readers vs writers.
• Analogies: alcohol (small dose helpful, large dose addictive), processed food (convenient but harmful as a default), and GPS (great when you can still navigate without it).

Historical Parallels and “Is AI Different?”

• Commenters invoke Socrates on writing, worries about TV/Internet/Google, and John Henry–style automation fears.
• One side: every major technology was accused of making people stupid, and we “turned out okay.”
• Other side: those earlier tools didn’t so directly automate knowledge work or both production and consumption simultaneously; social media is cited as precedent that tech can degrade cognition at scale.

Education, Learning, and Youth

• Multiple reports of students using AI for essays and homework, with teachers unable to keep up; concern that post-AI diplomas may signal weaker skills.
• Proposed fixes: less take‑home writing, more in‑person exams and oral defenses; radically new curricula, possibly AI-personalized but supervised by human teachers.
• Disagreement over long-form reading: some say deep engagement with hard texts trains attention; others see concision as preferable and view long books as partly historical artifact.

Work, Hiring, and Skill Atrophy

• Several hiring managers claim a large fraction of “senior” engineers now can’t perform basic coding or problem-solving without AI, leading to more rigorous in-person tests.
• Others counter that titles are inflated and AI may simply expose existing incompetence; or that seniors can quickly “re-warm” manual skills if needed.
• Debate over whether future “senior” value will shift toward architecture, system design, and orchestrating AI agents rather than line-by-line coding.

Dependence, Inequality, and Governance

• Navigation via GPS is used as a concrete example of lost skills; some see this as acceptable delegation, others as dangerous helplessness.
• Concerns about AI controlled by capital: habit-forming design, job displacement without safety nets, unequal access to high-quality models, and repetition of social media’s harms.
• A minority argue that compared to war, climate change, and demographic issues, AI‑induced stupidity is a secondary risk, though others respond that these risks interact.