My favorite slide from @masonyoungblood.bsky.social ‘s talk that pretty much summarizes @asaakyan.bsky.social ‘s new paper on Novelty vs Creativity in LLM generated text :-)

While we do not account for additional costs of human effort required to transform raw AI output into cohesive, publishable prose, the median fine-tuning and inference cost of $81 per author represents a dramatic 99.7% reduction compared to typical professional writer compensation. 6/n

Fine-tuned AI outputs fooled best AI detectors 97% of the time vs. just 3% for prompted ones.

Why?

Because Fine-tuning removes telltale AI quirks like clichés that detectors flag and readers dislike, flipping the detectability-preference link. 5/n

Results: Incontext prompted text was strongly rejected by Experts but showed mixed results w/ lay readers.

Fine-tuning #ChatGPT on authors’ ouevre completely reversed the findings: Experts now favored AI for style (OR=8.16) and writing quality (OR=1.87), with lay readers showing similar shifts. 4/n

MFA trained writers emulated 50 award-winning authors in reproducing 450-word excerpts.
150+ readers blindly compared human vs AI versions.

Two AI methods tested:
- In-context prompting (ChatGPT, Claude, Gemini)
- Fine-tuning on complete works.

Both used same prompts for fair comparison. 3/n

Why “market harm” matters? If an AI output becomes a close substitute for the original, it can hurt the market for those books. This is directly relevant to the fourth fair-use factor.

US Copyright Office recently acknowledged this 2/n

🚨New paper on AI & copyright

Authors have sued LLM companies for using books w/o permission for model training.

Courts however need empirical evidence of market harm. Our preregistered study exactly addresses this gap.

Joint work w Jane Ginsburg from Columbia Law and @dhillonp.bsky.social 1/n🧵

Very happy to see "Can AI writing be salvaged? Mitigating Idiosyncrasies and Improving Human-AI Alignment in the Writing Process through Edits" get a Best Paper Honorable Mention and is in the Top 5% of submissions for #CHI2025! 🎉 @chi.acm.org

Check it out here: arxiv.org/pdf/2409.14509

In the light of bullshit about AI being creative I got 10/10 in the poetry turing test.

I am yet again telling you that please evaluate your AI outputs by human who have expertise.

Not to say the AI poetries were so bad I wanna smash my head on the wall