Context Window 46
This edition covers Judge Alsup’s preliminary approval of the Bartz v. Anthropic settlement and the eligibility rules for authors, Google’s new Mixboard AI moodboard tool for creative teams, the 2025 DORA report on AI in software development, fresh Tony Blair Institute polling on UK attitudes to AI, HBR on AI-powered personalised coaching, an AEO piece for publishers in The Bookseller, Cloudflare’s annual letter on the future of the open web and a counter-argument from Paul Ford, a comparison of AI strategies at the NYT and Washington Post, and a tongue-in-cheek Latin phrase from Ethan Mollick for crediting AI.
The approval of the settlement in the Bartz v. Anthropic litigation overshadows most other developments for publishers this week. But elsewhere the week has seen new research, strong opinions on LLMs and web traffic, and a new creative AI tool that could get traction with creative teams in publishing. Have a good weekend. Big news overnight: Judge Alsup has given preliminary approval to the copyright infringement settlement in Bartz v. Anthropic. There will be more information on the operation of the settlement in coming days, and I’ll be covering this in detail in my next policy update for IPG members. As a reminder, it’s not enough for works to be within LibGen: eligibility for the settlement depends on copyright having been registered within five years of publication and before August 2022 (the date of Anthropic’s infringement). It’s also worth reiterating that the settlement is about copyright infringement, not the subsequent training, which Judge Alsup found to be Fair Use. In considering the sufficiency of the roughly $3,000 per author, the Judge asserted that Anthropic could have paid as little as $1 for a (presumably used) copy of a book and trained from that. I was talking to a client this week about how publishing breaks down into individual and group tasks. Most of the successful AI use cases I’ve seen have been about making individuals more productive—fewer have addressed collaborative working. So I was interested to see the latest experiment from Google Labs: Mixboard, an AI-powered mood board tool. It’s currently only available in the US, so American friends, have at it, while the rest of us wait or VPN. But this looks like a really interesting way for design, marketing and other creative teams to collaborate on visual tasks, and it’s the first AI tool I can imagine seeing on meeting room screens. Useful snapshot data in Google Cloud’s 2025 DORA report on the state of software development: 90% of software developers are using AI, 80% reported increased efficiency, and 59% claimed increases in code quality from using AI tools. Research from the Tony Blair Institute tends to divide opinion. But its latest report on AI usage and attitudes, based on polling by Ipsos, also gives a useful contextual snapshot. Some highlights: more than half of UK adults have used Generative AI tools in the last year, and just under a quarter use Gen AI weekly; two thirds of people who feel confident in their AI skills expect it to help them at work while leaving core responsibilities intact, but only 45% of people with lower confidence are optimistic; and looking at secondary education, 37% of respondents were comfortable with the idea of AI tutors compared to 32% against, with 33% in favour of AI taking on some routine teaching tasks versus 38% against. Lots of undecideds on both, but even small moves in this direction would have far-reaching implications for the sector and for educational publishing. On the education theme, HBR has an interesting report on an experiment using Generative AI for professional training which found significantly better outcomes from personalised AI coaching. It’s interesting but all a bit vague: I’d love to know more about the model they used, as opposed to generic references to a Gen AI Tutor. But it’s an interesting direction. I’m curious to see who is the first self-help author to release an AI coaching tool alongside their books and courses. Continuing the theme of discovery and web traffic from LLMs from last week, my friend Ani Attamian has a great piece in The Bookseller on AI optimisation, including recommendations for tools to monitor performance and visibility. I’ve known Ani since she was working with publishers at Google, and if you’re looking for help in this area, she’d be a great person to talk to. Cloudflare’s annual letter outlines a future where AI agents, not humans, are the main readers of the open web, and traffic-based business models continue to erode. Their proposed fix is to facilitate AI companies paying creators. But as Paul Ford points out in his newsletter, that vision turns writers into prompt-chasing content suppliers. The real lesson for publishers? Paywalls work. In a world of aggressive scraping and vanishing referral traffic, subscription models—not scale—are becoming the most reliable path to sustainability, leverage, and autonomy. Nieman Lab has a piece comparing the AI strategies of the New York Times and Washington Post, which provides some helpful advice on AI deployment for publishers: I was particularly taken by the Post’s policy that while generic information can be processed through enterprise AI tools like ChatGPT, sensitive data can only be used with internally hosted language models. Few publishers will need that level of security, but I suspect if you’re writing about All the President’s Men, sensitive data really is quite sensitive (RIP Robert Redford). Finally, since we’ve established that a non-trivial proportion of you are classics nerds, you might enjoy this tongue-in-cheek suggestion from Ethan Mollick for properly acknowledging the role of AI in work: tagging it with the Latin phrase, Fieri iussit.
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