"AI", students, and epistemic crisis

Original Article ↗ Hacker News Discussion ↗

Perceived Epistemic Crisis

  • Several commenters fear students treating LLMs as infallible authorities, even against teachers and primary sources.
  • Others argue the rhetoric is exaggerated: people must simply learn “LLMs are not reliable sources,” like earlier warnings about “it’s on the internet so it must be true.”
  • Some see this as part of a broader trend: people outsourcing thinking to institutions, search, or AI instead of developing critical judgment.

Reliability of LLMs vs Wikipedia, Search, and Journals

  • Many view Wikipedia and peer‑reviewed articles as far more reliable than LLMs, largely due to transparent sourcing and correction mechanisms.
  • Counterpoints: peer review has its own flaws (retractions, replication crisis, gaming of journals). Wikipedia has bias and vandalism issues.
  • Some say LLMs with citations (Perplexity, Copilot, Brave) narrow the gap; others note LLM citations can be fabricated.

Education, Teaching, and Assessment

  • Commenters stress teaching cross‑referencing, source evaluation, and the idea that “sounding right ≠ being right.”
  • Concern that students using AI to generate essays skip the thinking that writing is supposed to develop.
  • Suggested responses: stricter non‑multiple‑choice exams, individual projects, explicit instruction on AI limitations, and embracing AI as a tool rather than banning it.

How to Use LLMs Responsibly

  • Proposed strategies:
    • Demonstrate hallucinations live to students.
    • Require checking AI outputs against external sources.
    • Use AI for outlining, organization, and clarity, with students filling in detailed reasoning and evidence.

Hallucinations and Model Behavior

  • Experiences vary: some rarely see hallucinations; others encounter them regularly, especially on niche or config‑level tasks.
  • Worries center less on blatant errors and more on subtle, incremental falsehoods that users can’t easily detect.
  • Criticism that LLMs are “sycophantic” and rarely say “I don’t know,” making up plausible‑sounding but wrong content.

Broader Reflections on Technology and Knowledge

  • Comparisons to earlier shifts: calculators, early web search, and Wikipedia each triggered similar anxieties.
  • Some think LLMs must eventually become nearly perfect; others insist the scalable solution is teaching verification and skepticism.
  • There is debate over whether AI will erode deep skills (research, language learning) or simply change how and where those skills are applied.