Crackdowns on writers during wartime emerged as a key trend in PEN America's 2025 data gathered for the latest annual Freedom to Write Index.
Writers at Risk Archive
PEN America champions the freedom to write, recognizing the power of the word to transform the world. The bedrock work of the global PEN network is advocacy and assistance on behalf of individuals persecuted for their use of the written word or other forms of expression. PEN America’s Writers at Risk Database is a searchable catalog of the writers, journalists, academics, public intellectuals and others under threat around the world. The database includes historical cases PEN America has worked on from 1987 onwards; non-active cases are color-coded black. PEN America is grateful to the John Templeton Foundation for support that enabled the establishment of the Writers at Risk Database and to PEN International for their collaboration in assembling this database.
Freedom to Write Index 2025
For the first time ever, the Freedom to Write Index documented more than 400 writers in prison in 2025, including in the United States.
The Freedom to Write
PEN America stands at the intersection of literature and human rights to protect free expression in the United States and worldwide.
The social contract of writing | jola.dev
About the value of genuine writing in a world being drowned in slop.
Scientific production in the era of Large Language Models
Large Language Models (LLMs) are rapidly reshaping scientific research. We analyze these changes in multiple, large-scale datasets with 2.1M preprints, 28K peer review reports, and 246M online accesses to scientific documents. We find: 1) scientists adopting LLMs to draft manuscripts demonstrate a large increase in paper production, ranging from 23.7-89.3% depending on scientific field and author background, 2) LLM use has reversed the relationship between writing complexity and paper quality, leading to an influx of manuscripts that are linguistically complex but substantively underwhelming, and 3) LLM adopters access and cite more diverse prior work, including books and younger, less-cited documents. These findings highlight a stunning shift in scientific production that will likely require a change in how journals, funding agencies, and tenure committees evaluate scientific works.
The artificial intelligence disclosure penalty: Humans persistently devalue AI-generated creative writing.
How the AI Writing Panic Is Making Us All Worse Writers
This applies to those who use AI to write and those who don’t
supernote-cli: pen, paper, and a pipe
A recent NYT piece argued we need a mental fitness revolution to combat the cognitive decay caused by algorithmic feeds and generative AI. It's an efficient one-two punch. If you're not brainrotting on short form video content, you're outsourcing all of your thinking to an LLM. The result is a kind of cognitive strip-mining. What's left requires active defense. For me, one way of defending that capacity for deep work is with a pen on e-ink. Whether it's annotating a paper or starting a sketch from scratch, I'm intentionally making room for focused thought. My army of clawed Claudes and Codexes will just have to wait.
More Typos, Fewer Em Dashes: Writers Are Creating an Anti-AI ‘Literary Counterculture’
Novelists, journalists, and power LinkedIn posters are embracing first-person narratives and idiosyncrasies to avoid being mistaken for chat bots.
Minimum Queue Publishing - Wesley's notes
A strategy for writing more often without losing momentum
Beating the drums for independent press, publishers, and writers
Whose news? Whose story? Who gets to tell it?
Thousands of AI-written, edited or ‘polished’ books are being sold – an eerie echo of Orwell’s ‘novel-writing machines’
In ‘1984,’ George Orwell envisaged a world in which books were a mass-produced commodity no different from ‘jam and bootlaces.’
Homepage - J-Source
The past two years have seen a record number of media workers killed Continue Reading If killing journalists is a war crime, why isn’t anyone stopping it?
Protocolized Writing Workshop
Your chance to race to the frontier of modern AI-forward writing and publishing
Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers
Large language models (LLMs) are dramatically influencing AI research, spurring discussions on what has changed so far and how to shape the field's future. To clarify such questions, we analyze a new dataset of 16,979 LLM-related arXiv papers, focusing on recent trends in 2023 vs. 2018-2022. First, we study disciplinary shifts: LLM research increasingly considers societal impacts, evidenced by 20x growth in LLM submissions to the Computers and Society sub-arXiv. An influx of new authors -- half of all first authors in 2023 -- are entering from non-NLP fields of CS, driving disciplinary expansion. Second, we study industry and academic publishing trends. Surprisingly, industry accounts for a smaller publication share in 2023, largely due to reduced output from Google and other Big Tech companies; universities in Asia are publishing more. Third, we study institutional collaboration: while industry-academic collaborations are common, they tend to focus on the same topics that industry focuses on rather than bridging differences. The most prolific institutions are all US- or China-based, but there is very little cross-country collaboration. We discuss implications around (1) how to support the influx of new authors, (2) how industry trends may affect academics, and (3) possible effects of (the lack of) collaboration.