It’s still worth blogging in the age of AI

Why People Still Blog

• Writing forces slower, clearer thinking; exposes gaps in understanding and biases. Many see “writing is thinking” as the core benefit, regardless of audience.
• Blogging pushes exploration: people tackle topics they wouldn’t touch otherwise, and public posts invite corrections that accelerate learning.
• Blogs act as a personal archive/portfolio and memory aid; several noted often re‑finding their own posts via search.
• Some use blogs to escape constrained genres (e.g., academic passive voice) and to write in a more human, coherent style.
• A number of commenters say they blog simply because it’s fun or creatively satisfying, with little concern for readership or branding.

Blogging vs Private Writing

• Some argue you can get the “thinking benefit” from a local journal; others say publishing adds pressure to be precise, and occasional readers, friendships, or career benefits justify going public.
• Lack of feedback and the effort per post (often many hours) are major reasons people don’t blog more.

Impact of AI on Motivation

• One camp: AI makes blogging more important—models need high‑quality human text, and blogs help shape what AIs “learn.”
• Others: they’ve reduced or stopped blogging to avoid their work being “slurped” into commercial models without consent, pay, or attribution; some move to mailing lists or private spaces.
• Debate over whether this stance is “dismal excuse” vs rational response to exploitation and information “grey goo.”
• Some are excited that their writing might influence future models and indirectly help many more people.
• Concern that AI regurgitates ideas as if new, erases provenance, and competes with original authors for attention.

Ethics, Attribution, and “Theft”

• Strong disagreement on whether training on public text is akin to theft/piracy or just reading at scale.
• One side stresses: copying for training without permission or compensation wrongfully appropriates effort and can undercut creators’ livelihoods.
• The other side: humans and organizations have always learned from public work without granular attribution; LLMs mainly change scale, not principle.
• Related disputes over idea ownership vs cultural progress, and whether comparisons to open‑source licensing are valid or misleading.

Quality, Novelty, and Trust

• Skepticism that LLMs generate truly novel ideas; counter‑point that most human blogging also rehashes existing themes, and value ≠ novelty.
• Example cited of an AI‑generated Java article confidently describing a language feature that doesn’t exist, reinforcing trust in identifiable human authors.
• Many say they increasingly seek out small, clearly human blogs as AI spam grows.

AI as Tool for Writers

• Several use LLMs as assistants: proofreading, grammar, tone suggestions, citation formatting, or custom tools that search their own blogs.
• Caution that AI can over‑rewrite into generic “corporate drone” style; helpful when constrained to low‑level edits or critique.

Community, Meaning, and Non‑Economic Value

• Recurrent theme: not everything must be “optimized for money” or personal brand; writing, like playing music or doing woodworking, can be worthwhile for its own sake.
• Still, some emphasize that external validation and being concretely useful to others matter; a world of purely private creativity feels impoverished.
• Multiple people report that reading a random, personal blog post has meaningfully changed their interests or career, encouraging bloggers to keep going.

Infrastructure and Privacy

• Favorable mentions of simple, markdown‑based static blogs and privacy‑friendly hosting services; dislike for ad‑tech, bloat, and tracking.
• Suggestions to block AI crawlers via robots.txt, services tracking AI user agents, or Cloudflare rules—but acknowledgment that enforcement is imperfect.