ChatGPT Is a Gimmick

What “gimmick” means in this debate

• Many interpret “gimmick” as tech that looks impressive but doesn’t fundamentally change important work; others say that bar is too high given how much value they personally get.
• Some argue the author really means: AI cannot replace the human, effortful process of learning and thinking, especially in education, not that it has zero utility.

Education, cheating, and learning

• Several commenters agree that students using LLMs to bypass learning is a real problem, analogous to older forms of cheating but cheaper and easier.
• Others ask for empirical evidence that cheating has increased, not just shifted form.
• Strong concern that edu hype frames AI as making learning “effortless,” which is seen as dishonest and infantilizing.
• Pushback: AI can be a powerful tutor, explainer, and “rubber duck,” especially for those without access to good teachers; the right question is how to teach students to use it well.

Practical usefulness vs. frustration

• Heavy users describe clear wins:
  • Drafting and tightening emails, docs, and reports.
  • Explaining math/physics proofs, checking derivations, and catching reasoning mistakes.
  • Coding scaffolds, refactors, one-off scripts, and unfamiliar stack “on-ramping.”
  • Advanced thesaurus, language learning aids, data cleanup, and search replacement where web search is SEO-spammed.
• Others say they “can’t get anything valuable”: hallucinated APIs, kernels, flags, math errors, overconfident nonsense, and brittle “agentic” loops. They see usefulness only when answers are easy to verify.
• A recurring heuristic: LLMs help when it’s slow to produce a plausible answer but fast to check it; they’re poor when verification is hard.

Reliability, hallucinations, and epistemics

• Multiple comments stress hallucinations, fabricated citations, and misrepresented sources as dangerous, especially where domain knowledge is weak.
• Some suggest treating LLMs as “compressed Google” or recommendation engines: good at pointing to ideas, not as authorities.
• Others complain about the obsequious style and tendency to reinforce user assumptions instead of challenging them.

Hype, markets, and capitalism

• Many see a gap between corporate/VC “near-AGI” hype and the modest, fragile reality of current tools.
• Some worry AI is pushed to cut labor costs and concentrate wealth, using unpaid human-created training data, while displacing illustrators/writers.
• Others argue markets will eventually sort out what genuinely works, but that hype-driven overinvestment and “enshittification” are already obvious.

Use in creative/ordinary life

• Examples include cooking with limited ingredients, generating language-learning imagery, creative brainstorming, and casual explanation of physics or philosophy.
• Critics call many of these uses “gimmicky” or niche; proponents counter that small, messy boosts across many tasks are still transformative.