Pre-2022 Books

Perceived Flood of AI-Generated “Slop”

• Many see post-2022 content (books, posts, docs) as increasingly AI-written, shallow, and cliché—“good-looking” but empty.
• Concern that production has been accelerated 1000x while human reading capacity is fixed, so consumers now do unpaid filtering.
• Some argue this is just an amplification of pre-existing slop, not something fundamentally new.

Pre-2022 Cutoff & “Low-Background Steel” Analogy

• Several commenters now prefer books, posts, and references dated before ~2022/23, treating them as “pre-contamination.”
• The “low-background steel” metaphor is repeatedly invoked for uncontaminated content.
• Others note AI-written books existed before 2022, so the cutoff is somewhat arbitrary.

Fiction vs Non-Fiction and Tech Books

• Multiple people report obvious AI “smell” primarily in non-fiction/technical books (e.g., programming, cybersecurity), especially from some publishers and Amazon self-publishing.
• Several say they haven’t yet detected AI in recent fiction, or believe it’s rare because “literature is hard.”
• Some technical writers explicitly refuse AI assistance despite the market’s devaluation of post‑2022 books.

Curation, Gatekeepers, and Discovery

• Expectation that traditional gatekeepers (publishers, editors, talent scouts) and reputational cues will regain importance to filter AI slop.
• Others counter that publishers have pushed mediocre work for decades and often prioritize sales over quality.
• Self-publishing is seen as becoming harder to trust, but not dead; authors will need stronger reputations.

Authenticity, Detection, and Demoralization

• People share that AI-detection tools flag human-only writing, including pre-1900 books, and are likened to polygraphs.
• Some track drafts in git or propose proof-of-work systems, but others note these can’t prove absence of AI help.
• Creators describe being demoralized both by LLMs’ existence and by reflexive accusations of AI use.

Counterarguments & Nuanced Uses of AI

• A minority dismiss the fear as overblown: most things were always bad; just keep judging by quality.
• Some use LLMs narrowly (phrase recall, sentence splitting, business boilerplate) while insisting on keeping their own “voice.”
• Others argue society should not tolerate AI in creative fields at all.

Coping Strategies and Outlook

• Strategies: buying older/used books, relying on recommendations, university presses, archives, and time as a filter.
• Several note there is already a lifetime’s worth of good pre‑2020 material; others say clinging to old works isn’t sustainable long term.
• Mixed optimism: some think we’ll adapt and build better fact-checking/curation; others foresee deep, lasting trust collapse in online text.