Cheena Srinivasan @_csri

By the late 2020s, AI cumulative written output--every postcard, memo, whitepaper, and business-document--should be surpassed by AI. We left a written record; that record will be synthetically surpassed.

Check out my latest article: Your work used to speak for itself. With AI, it no longer does. linkedin.com/pulse/your-wor… via @LinkedIn

I wrote about the deluge of AI slop that is drowning scientific journals and preprint servers theatlantic.com/science/2026/0…

“Slop” is the term for the rising tide of low-quality, AI-generated content flooding digital platforms—think hastily assembled eBooks, generic cookbooks, or recycled summaries churned out by tools like ChatGPT. It’s not just noise; it’s a calculated exploit of scale, prioritizing volume over value. According to an investigation by 404 Media earlier this month, the problem has hit public libraries, prompting action from Hoopla, a major eBook provider. The exposé uncovered hundreds of AI-made titles—like IRB Media’s 600+ summaries—clogging Hoopla’s catalog, misusing public funds and taxing librarians. Hoopla’s fix: purge the slop, tighten curation, and offer libraries an opt-out for AI-tagged content. The problem isn’t new or confined to eBooks—Amazon’s KDP capped uploads at three titles daily back in 2023 and websites are drowning in AI-generated articles and clickbait, diluting search results and user trust. All are reacting to a clear trend: AI’s low barrier to entry is overwhelming ecosystems built on quality. The stakes are high. Readers lose time, authentic authors lose visibility, and curation crumbles. Hard stats on slop’s scale are scarce, but its impact isn’t. Hoopla’s cull helps, but it’s a patch, not a plan. Platforms thrive on volume, not vetting. AI tools fuel the flood unchecked. We need smarter filters—labeling, detection, something—to safeguard quality. -s

John Herrman explores what AI firms’ “deep research” tools tell us about the future of AI — and the internet. nymag.com/intelligencer/…

Reddit mods are fighting to keep AI slop off subreddits. They could use help. arstechnica.com/gadgets/2025/0…

I asked DeepSeek vs ChatGPT a series of ethical questions — and the results were shocking tomsguide.com/ai/i-asked-dee…

Exclusive: A @GPTZeroAI analysis shows that AI writing is commonplace in top Substack newsletters: wired.com/story/substack…

The Hidden Costs Of AI Ethics: Understanding Reputational Risk forbes.com/sites/jasonsny…

creative.salon/articles/featu…

80% Of Surveyed Businesses Don’t Have Plans For An AI-Related Crisis forbes.com/sites/edwardse…

Top 5 potential implications of AI-generated prior art on patent law reuters.com/legal/legalind…

Zuckerberg: The AI Slop Will Continue Until Morale Improves "I think we’re going to add a whole new category of content, which is AI generated."

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We’re at a critical moment in web content attribution and compensation.

MIT Technology Review @techreview

2 years ago

AI search could break the web trib.al/kX897mc

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Jodi Picoult ‘dismayed’ at AI advert for By Any Other Name | @thetimes buff.ly/3AetZj6

The blogging platform Medium is facing an influx of AI-generated content. CEO Tony Stubblebine says it “doesn’t matter” as long as nobody reads it. buff.ly/3AjsHDk #technology #content #digitalexperience

CEO Steve Huffman on How Reddit Fits Into the AI World wsj.com/tech/ai/ceo-st…

I enjoyed @jwherrman insights in his article -- a significant disconnect between how AI companies envision their technology being used versus how it's actually being deployed in practice: often for generating large quantities of passable but uninspired content rather than revolutionary applications.

MediaREDEF @MediaREDEF

2 years ago

Is That AI? Or Does It Just Suck? (@jwherrman - @NYMag) redef.com/item/66eb3616b…

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More than 13,000 creatives (including some famous authors, musicians, and actors) signed a statement that expresses their growing concerns over the unauthorized use of copyrighted works to train generative AI models. The one-sentence statement published by Fairly Trained, an advocacy group founded by former Stability AI executive Ed Newton-Rex, reads: “The unlicensed use of creative works for training generative AI is a major, unjust threat to the livelihoods of the people behind those works, and must not be permitted.” Newton-Rex told The Guardian, “There are three key resources that generative AI companies need to build AI models: people, compute, and data. They spend vast sums on the first two – sometimes a million dollars per engineer, and up to a billion dollars per model. But they expect to take the third – training data – for free.” Like I said yesterday, this is the fight of the year (maybe the next five years). Fairly Trained’s idea is to have a universally enforceable method to prevent creative content from being used for AI training without permission and compensation. This might be possible, but anything that was ingested prior to the most recent cutoff date is already part of the collective body of knowledge of every foundational model (no matter the AI company). You can push back and say that there are ways to force this issue, that there are methods where you could extract specific artist’s works or fine tune a model to ignore requests to create new work product “inspired” by a particular artist’s work. You might even be able to figure out a way to prove that a particular model was trained on something specific and, if it can’t be extracted, force some kind of royalty payment. In practice, where there’s a will, there’s a way. First, we need to agree that the content (data) required for training should not be free. Then, as we fight the fight, we have to hope that new technologies and synthetic data don’t obviate the need for organic, real data. It’s hard to look toward the future through the lens of the present. It’s even harder to look through the lens of the past. Here’s my question (challenge) to each of you: For AI platforms, what is the right way to compensate content creators for the use of their works? How should AI platforms compensate content creators? There are two areas to consider: 1) training and 2) output. Please share your thoughts below. -s

This week, @NYMag published a very good feature story on low-grade AI-created content taking over the Internet and making it worse. It’s about what happens when human-made content gets replaced by AI slop: nymag.com/intelligencer/…