7arXiv cs.AI (Artificial Intelligence)·
Empirical study finds generative AI books flood Amazon self-publishing market, diluting revenue per title
A new arXiv paper analyzes 14,419 self-published genre-fiction books on Amazon from 2023–2026, using AI detection to measure the commercial impact of AI-generated content. Books with substantial AI text (>25%) grew to occupy a large catalog share and a growing fraction of sales and top-rank positions, even without disclosure. The market saw a 19.2x increase in selling books but only 8.9x revenue growth, meaning revenue per book fell — with human-authored books losing the most ground in high-AI-diffusion genres. The authors argue generative AI reshapes creative markets through scale rather than quality, with direct implications for copyright fair use doctrine.
Related guides (2)
Related events (8)
Generative AI Advertising as a Problem of Trustworthy Commercial Intervention
This paper argues that generative AI fundamentally transforms advertising by enabling interventions on the generative process itself rather than discrete content placement. The authors introduce a taxonomy of influence tiers—product mentions, information framing, behavioral redirection, and long-term preference shaping—and analyze how these manifest across RAG and agentic pipelines. They find that deployed systems focus on the most observable tier while more consequential, latent forms of commercial influence lack detection, measurement, or disclosure frameworks. The central challenge posed is whether commercial influence in generative systems can be made attributable, measurable, contestable, and aligned with user welfare.
Empirical study finds ChatGPT, Perplexity, and Gemini driving measurable traffic to academic library repositories
A preprint analyzes web analytics from August 2023 to October 2025 to quantify AI-mediated referral traffic to an academic library's institutional repository. ChatGPT, Perplexity, and Gemini are identified as the primary platforms driving this traffic, with open-access theses and dissertations being the most commonly surfaced resources. The study finds that structured metadata and stable permalinks correlate with higher AI retrieval rates, suggesting that resource discoverability in AI ecosystems depends on metadata quality and open-access status.
Large-scale study finds AI supply chain license obligations rarely survive redistribution
A new arXiv paper traces 232,270 dataset→model→application chains across Hugging Face and GitHub to measure license propagation fidelity in AI supply chains. The authors identify two forms of 'license laundering': unlicensed artifacts acquiring definitive labels downstream, and declared licenses being replaced during redistribution. Key findings include that 62.3% of chains pass through at least one artifact with no declared license, and every obligation-bearing license category (e.g., copyleft, attribution-required) falls below 7% end-to-end survival while permissive licenses reach 95.1% survival. The paper offers recommendations for practitioners, model publishers, rights holders, and platform operators.
Real AI Agents and Real Work
A commentary piece from One Useful Thing examining the practical deployment of AI agents in real work contexts, framing the tension between human-centered work and AI-generated productivity outputs. The piece appears to analyze how autonomous AI agents are changing knowledge work workflows. Published by a Tier 2 source known for applied AI analysis aimed at practitioners and researchers.
Your AI Use Is Breaking My Brain
Simon Willison comments on the phenomenon of AI-generated or AI-assisted content degrading the quality of online discourse and information environments. The piece reflects on how widespread AI use is affecting the experience of consuming internet content. This is a commentary piece from a prominent developer/blogger on the social and epistemic effects of AI proliferation.
Anthropic Launches Economic Index: First Large-Scale Empirical Study of AI's Labor Market Impact
Anthropic has released the Anthropic Economic Index, an initiative tracking AI's effects on labor markets using anonymized data from approximately one million Claude.ai conversations matched to U.S. Department of Labor O*NET occupational tasks. Key findings show AI use is concentrated in software development and technical writing, with 36% of occupations seeing AI use in at least 25% of their tasks, and usage skewing toward augmentation (57%) over automation (43%). The underlying dataset is being open-sourced to enable independent research, and Anthropic is inviting economists and policy experts to contribute to the ongoing initiative. The analysis was enabled by Clio, Anthropic's privacy-preserving internal conversation analysis tool.
Internet Traffic Driven By AI Tripled Last Year, Study Shows
Human Security's 2026 State of AI Traffic and Cyberthreat Benchmark Report, based on over 1 quadrillion internet interactions, found AI-driven traffic nearly tripled in 2025, with agentic browser-style traffic growing ~80x year-over-year (though still only 1.7% of AI-driven traffic by December). OpenAI accounted for ~69% of automated traffic, Meta 16%, and Anthropic 11%. The report also flags a 47% rise in malicious scraping and new security challenges as legitimate AI agents increasingly mimic historically suspicious bot behaviors like account creation and transaction completion.
Large-scale study of AI nudification on 4chan finds majority of targets are now non-celebrities
A new arXiv paper presents a large-scale empirical study of AI-generated non-consensual sexually explicit imagery (SNEACI) on 4chan, identifying 24,105 items. A key finding is a demographic shift: non-celebrity individuals now constitute 55.8% of targets, up from 4.7% in prior studies, indicating the harm has expanded from public figures to people in users' personal social circles. Open-source models dominate production, with Stable Diffusion generating 42.7% of images and Wan 66.5% of videos, enabled by thousands of shared fine-tuned models and tutorials. The study characterizes the community dynamics, finding a small cohort of prolific producers drives most content and lowers barriers for new participants.