The More Young People Use AI, the More They Hate It

Class, labor, and coercion

• Several argue AI most readily automates upper‑class “knowledge work” tasks (summarizing, synthesizing, boilerplate writing) but its coercive impact falls hardest on lower-level workers and freelancers.
• Freelancers report effective rate cuts: work that used to take months is now expected in weeks for the same pay, with another “step down” likely. Demand is also seen as softening.
• AI becomes a required survival tool (to meet new speed/price baselines) while being culturally framed as low-status, lazy, or inauthentic.
• Others see disdain for AI as a “luxury belief” of people rich or skilled enough not to need it, or of white‑collar workers suddenly facing the same automation pressure earlier directed at blue‑collar jobs.

Capabilities and limitations

• Many posters stress current LLMs are not general intelligence; they statistically model language, often echoing prevailing or user‑desired opinions rather than thinking.
• AI is described as very effective for preparation work: collecting, organizing, and synthesizing material; weak at original insight, nuanced writing, or simple architectures without overcomplication.
• Consensus that AI is only useful with informed human oversight; “bare” use by non‑experts can mislead or inflate complexity.

Youth attitudes and generational framing

• Younger people are depicted as both beneficiaries and “damaged subjects”: AI lowers learning/creation barriers but can bypass genuine thinking.
• Some older commenters report Gen Z/Alpha peers and kids distrusting AI, mocking it, or worrying about dependency and cognitive decline; others see many young people eagerly using it or giving up on learning (“what’s the point?”).
• There’s concern that future generations will grow up with AI as mandatory, like social media for Gen Z.

Regulation, power, and infrastructure

• A minority advocates making AI illegal; most replies argue this is impractical due to global competition, local models, VPNs, and state/corporate incentives.
• Comparisons to nuclear arms and child pornography laws are debated; some emphasize that any ban would likely hit individuals while governments and large firms kept privileged access.
• Others urge “weaponizing” AI against incumbents via local/open models, but skeptics point to compute centralization and corporate/government pushback.

Education, cognition, and dependence

• Multiple anecdotes from education: students using AI for group work struggle with follow‑up questions, suggesting shallow understanding.
• Some limit AI use (e.g., avoiding chatbot answers in favor of traditional research) to protect cognitive skills and autonomy.
• Others believe AI can be a powerful learning amplifier—like an interactive tutor—if used for interrogation and exploration rather than shortcutting effort.

Bias, critical thinking, and media

• Some use LLMs to analyze articles and polls for bias, but others warn this can outsource critical reasoning and that AI itself is biased and sycophantic.
• A meta‑example in the thread shows an LLM critiquing an article’s bias, then critiquing its own critique, illustrating both usefulness and self‑inconsistency.
• There is broad concern that AI‑generated “slop” will dominate online content, further enshittifying the internet and eroding meaningful communication.