Happy Black Friday. This Sunday marks three years since ChatGPT first appeared: a toddler in human years, already learning to run, leaving a mess in its wake, and showing signs of what it might grow into. It has even added a new word to our vocabularies—slop—and several of this week’s links explore whether AI-generated content has any value or is just that. ​ ChatGPT introduced a new shopping research feature this week, which matches products to a user query. I tried using it to find some gifts and it did a pretty good job of matching recently published books to recipients, though it pulled pricing and availability from a range of bookshops and publishers. It’s also unclear how frequently this data is refreshed or how well it handles backlist titles. These are questions anyone who cares about book discoverability should be thinking about too. ​ The new 2025 Edelman Trust Barometer on Trust and AI has some really interesting conclusions for anyone implementing AI in the workplace: about 60% of employees would accept AI aimed at productivity rather than cost saving, and the provision of high quality training increased employee willingness to use AI (unsurprisingly, I endorse that message). ​ Google Labs launched a new pedagogical experiment called Learn Your Way, which uses AI to transform linear textbooks into interactive learning materials. They claim an 11% improvement in retention scores for the AI texts over traditional ebooks. There’s a waitlist signup for users to upload their own PDFs: for publishers, that might be an experiment to consider, but it will also be interesting to see what copyright guardrails are built in to control use of third-party content. It also raises rights questions: at what point does an AI-modified textbook become a derivative work, and who owns those adaptive outputs? ​ On the subject of education, EdTechnical is running a forecasting competition on the impact of AI on education to the end of 2028—the same timeframe forward as from ChatGPT’s release to now. I’m sure plenty of subscribers have a view on this, and there are prizes for the best contributions. ​ Rahim Hirji’s newsletter has a fantastic list of nearly sixty AI habits that would get you sued, fired or embarrassed. Based on your score, you can determine whether you’re a cautious sceptic, a normal human or a walking liability according to Rahim’s scale. There’s a part of me that thinks that with such a fast-moving technology, if you’re not experimenting—and occasionally making mistakes—you’re not learning. But it’s certainly safer to learn from other people’s errors. ​ The AI platform Descript has published a useful guide to slop-free content creation, in particular repurposing an existing asset into different media formats. This is something content and marketing teams in publishers do all the time, and the guide provides some clear, practical advice. ​ New research suggests that AI-produced adverts can’t be dismissed as slop, as they perform considerably better than traditional commercial messages. I have questions about the research methodology, particularly the sample size. And the study measures perceived effectiveness rather than real-world conversion—still, it’s a sign that AI-generated creative may not be as disposable as many assume. ​ On the subject of AI slop, The Wrap returns to a subject that I’ve discussed before: the AI podcast studio Inception Point, now generating 3,000 podcast episodes a week, with a team of eight people. It’s easy to dismiss this as slop, and as I’ve previously argued, it hurts the signal to noise ratio for traditional podcast publishers. But it’s working, as Inception Point has over 400,000 subscribers. The piece goes into new detail about how the company operates. What’s striking is how tightly their production model is tied to algorithmic opportunity—filling keyword gaps with astonishing speed. It’s not hard to imagine the same volume x velocity playbook applied to ebooks. ​ A more traditional publisher, The Atlantic, has struggled with AI platforms crawling its site for data: one company tried to crawl over half a million times in a week. This piece looks at its strategy for managing access to its content. What’s particularly useful is the data-led approach that the Atlantic took, using its logs to determine which bots brought referral traffic and which should be blocked (less than a third brought any value). On that point, I’ve spoken to two publishers in the last six months who were proposing to make decisions about their websites without even reviewing their logs. Be more Atlantic. ​ Finally, I don’t think I’ll ever be comfortable listening to my own voice, but I did a very traditional podcast interview with the brilliant Alison Jones this week, talking about our respective careers in books, digital change, and the impact of AI on publishing.

This week has been full of stories that show how fast the conversation around AI, authorship, and creative integrity is moving. From new research on writers’ concerns to real-world disputes over AI-generated artwork, it’s clear that evidence and transparency matter more than ever. ​ A new research report from the Minderoo Centre for Technology & Democracy at the University of Cambridge received significant media attention this week for its headline claim that half of UK novelists believe AI will replace their work (there’s a lot more beyond the headline and I really encourage you to read it, especially if you’re a trade fiction publisher). It’s a strong piece of exploratory, qualitative research, though its focus on novelists alone excludes the equally important perspective of non-fiction writers (particularly since many authors work across both fiction and non-fiction). I have expressed some doubts about the methodology and whether one can reasonably draw population-level inferences from a convenience sample of 258 authors. But this is really to say that I hope it demonstrates the topic is important enough to do a larger scale study across types of authorship. ​ Coincidentally there’s a very useful piece by Marc Zao-Sanders in HBR on how to make sense of research on how people use AI, which makes important points about vested interests and inherent bias. For clarity, I’m not suggesting these are problems with the Cambridge research, only that the principles are worth keeping in mind with every data source on the subject (including what I write). I think I’m going to take this sentence from Marc’s piece as the mission statement for this newsletter: “The path to a sensible, defensible, and useful view of what’s going on lies in the synthesis of many different sources.” ​ Second only to the Cambridge research in press coverage this week was the news that two eminent authors were disqualified from a leading literary prize in New Zealand for the use of AI in their cover artwork, after new rules were instituted by organisers. This highlights a number of issues: the fact that the authors were unaware of the use of AI by their publisher, the concomitant need for transparency between authors and publishers, and the practicality of applying rules on this fairly and consistently. ​ On this subject, I came across an interesting practical AI feature this week: Google Gemini now has the ability to look at an uploaded photo and detect SynthID watermarks that are added by Google’s own image generator to determine whether it is likely to be real or generated. It takes one to know one? This could become a helpful tool for publishers trying to verify the provenance of submitted images. ​ However good automated detection gets, it’s never going to be completely foolproof in detecting AI, and there’s a real problem with false positives. How do you defend yourself if you’re accused in error of using AI? (This is far from a theoretical problem: I know book publishers this has happened to in the last year.) This is a really interesting case study from the brilliant Watershed in Bristol, which was accused of using AI in its marketing. Their response is really clear, and includes an explanation from their designer. It’s a model of clarity, and it raises an uncomfortable question: how many of us could offer an equally confident and well-documented rebuttal of our creative processes? ​ I suspect Google Scholar is one of the company’s lesser-known offerings, but it’s an essential tool for many researchers and academic publishers. This week Google released an updated, AI-powered search called Scholar Labs in limited preview. This is particularly helpful in providing a short summary of relevance to a search topic for each item returned, and could be especially valuable in the exploratory stages of research or literature review. ​ I’m always interested in AI case studies from other industries, and this post from broadcasting about developing a complex content workflow in under thirty minutes offers a compelling look at how AI can accelerate production. Of course, the prerequisite for doing this was having an MCP server that already interacted with key systems: the book or journal publishing equivalent would first require an existing integration with bibliographic databases, content management systems and other infrastructure. But the underlying principles hold true. I particularly liked this assessment of the developer’s role in the results: “To be honest, I don’t see a world where AI replaces engineers. It’s more about all engineers operating at a fundamentally different velocity, albeit constrained by purpose. The knowledge I’ve accumulated over three decades didn’t become irrelevant—it became leverage. I knew what to ask for. I could evaluate whether what [AI] produced was sensible… The AI handled the tedious translation of intent into implementation, yet the customer still owns the ‘purpose’ that drives the intent.”

There’s an interesting new report out from the Minderoo Centre for Technology and Democracy at Cambridge University on the impact of AI on the novel, authored by Dr Clementine Collett. There’s much that I completely agree with and that accords with my experience of working with book trade on AI. But I have some constructive thoughts about the framing/communication.

Hello from Dublin, where I’ve been speaking at the Publishing Ireland conference. It’s been a really excellent day and good to see many subscribers and friends here. The big theme this week is AI developments from Big Media: new features and guidelines from Spotify, Netflix and Time all have implications and lessons for publishers of all sizes. ​ Spotify has introduced a new feature called Recaps, which uses AI to generate a short narrative reminder for listeners when they come back to an audiobook after a while. The carefully worded announcement states clearly that book content is not used for LLM training—though it seems likely that it is processed by an LLM for generation, even if the data isn’t retained or used to train the model. Functionally, this is similar to Amazon’s recent Story So Far feature. There are two immediate implications for publishers. With two of the leading retail platforms offering this feature, similar functionality is likely to come to other reading systems. Second, the tight integration of AI into core platform functionality shows how difficult it is becoming to accommodate requests from authors who want to avoid any AI use associated with their work. ​ Generation of summaries is also the focus of this opinion piece from the Authors Alliance, which highlights an implication of the recent court ruling in the OpenAI class action: that certain short summaries of fictional works might, in some circumstances, be interpreted as infringing derivative works. This isn’t an issue for Spotify or Amazon, who work directly with rights holders, but the piece speculates about potential risks for platforms like Wikipedia. ​ AI audio platform ElevenLabs has launched a new marketplace for ‘legendary voices’, synthetic versions of leading figures such as Maya Angelou, Michael Caine, Laurence Olivier and Judy Garland for text-to-speech applications. Most of the featured voices are no longer dead, with relatively few contemporary figures. It will be interesting to see whether more living rights holders choose to participate, given the varying legal frameworks around voice likeness and posthumous rights. ​ Netflix has published a set of guidelines for the use of generative AI in creative applications, which is a useful thought starter for publishers. What’s particularly relevant is the thinking on ethics and how AI works with creative workflows and third party intellectual property. Ideally publishers should have policy documents that are internally facing like this one, and for key external partners like authors (as in the Wiley examples last week). ​ Google has introduced a new retrieval augmented generation (RAG) functionality to the Google Gemini API. Put simply, the new File Search tool allows Gemini to interact with your own repository of files rather than relying solely on its general training data and web search. This is priced aggressively at $0.15 per million tokens (roughly 5-6 non-fiction books). ​ Google has also introduced a series of improvements to one of my favourite AI tools, NotebookLM, including a Deep Research model and better integration with PDFs and other files in Google Drive. This makes it significantly more useful as a research tool. ​ As an example of a really expansive publisher AI strategy, Time magazine has introduced an AI Agent offering interactivity, summaries, translation and audio versions alongside its reporting. ​ Helen King’s PubTech Radar has an interview with Jonathan Woahn, the founder of AI content management platform Cashmere, which sits between publishers and AI companies. It’s all useful context, but the key takeaway for me is that publishers can either engage with licensing and shape how it works, or watch it happen to them.

I sent the first of these newsletters a year ago this week, to twenty-seven friends and colleagues. Since then, it’s grown to over 1,500 readers and has become one of the highlights of my work. The cadence of researching and publishing weekly keeps me up to date before I hit send, and I really value all of the comments and connections that have come from it. Thank you for your time and attention, and I hope you’ll stay with me for another year. ​ Thad McIlroy has an excellent, thought-provoking piece on the publishing industry and technology adoption, using the slow take-up of ONIX 3.0 as a frame to ask, what if publishing is equally dilatory in adopting AI. Thad evidences his argument in part with the absence of AI requirements in current job listings—to back up that argument, I looked at a number of open roles at UK publishers that talk a good game on AI, and even in technology-forward areas such as digital marketing and analytics, there’s not a mention of AI skills… ​ Authors and publishers suing OpenAI have gained access to internal company discussions on the use and deletion of books from LibGen, which could be seen as destruction of evidence. The plaintiffs are a long way from their day in court, let alone damages or an Anthropic-type settlement, but it’s not a stretch to imagine that as an outcome. ​ Getty Images largely lost its UK lawsuit against Stability AI. The court found only limited, historic trademark infringement relating to Getty watermarks and rejected secondary copyright claims. For rights holders, the UK still lacks a definitive legal position on whether training AI models on copyrighted works is infringement—meaning policy developments and future cases will likely shape the landscape more than this ruling. ​ One of the fundamental challenges for publishers in the last year has been balancing practical opportunities from AI with litigation over use of content in training. Litigation requires confrontational positioning, but companies have to be careful not to box themselves into a corner. That said, I’m not sure I’ve seen anything quite as quick-footed as Universal Music announcing the settlement of litigation and a strategic partnership with the opposing party in the same press release… ​ Amazon filed a new lawsuit against AI platform Perplexity for allowing its AI agents to shop on behalf of users (Amazon is, of course, developing similar functionality itself). Perplexity responded with an understated argument that this is a threat to all internet users. For publishers who are grappling with issues of AI agents accessing information, it’s a small foretaste of the bigger arguments when agents are transacting with websites. ​ Separately, on a more practical note, Perplexity published a new set of guidelines on AI in the workplace, built around its own tools but with some useful general advice on prompts and capabilities for any AI user. ​ Slate uses recent discussions between local history publisher Arcadia and its authors as the starting point for a piece on publisher licensing to AI companies. Besides providing general context, it’s also helpful in highlighting the opacity of a lot of licensing deals and other friction points for authors. ​ A week after a series of largely incremental product updates from Adobe, Canva announced a complete overhaul of its product line, now described as a Creative Operating System. AI tools are present throughout, including a proprietary design model, integration with LLMs and AI-powered analytics for marketing campaigns. And Affinity, the InDesign competitor acquired by Canva last year, is being made free in perpetuity (and has been downloaded over a million times in less than a week). Overall, this looks like a really compelling alternative to Creative Suite for publishing design and marketing teams. ​ For academic and educational readers, Sage published a new white paper by Tom Chatfield on AI and the future of pedagogy. It strikes a good balance of highlighting issues and opportunities, particularly the potential for AI to be a guided learning partner, not merely a source of content. Anyone developing courseware and textbooks could get a lot from it. ​ On that theme of AI as partner not replacement, belated thanks to Shimmr founder Nadim Sadek for sending me a copy of his excellent new book, Quiver, don’t Quake, a combination of philosophical musing and practical guidelines on AI and creativity. It made for a thought-provoking return journey from New York last week. ​ John Wiley published a new set of guidelines on the use of AI for journal authors, editors and peer reviewers. This complements their earlier guidelines for book authors, which I’ve often held up as the gold standard for publisher policy and communications. Both sets of guidelines are essential reading and Wiley has done the entire ecosystem a service by making them publicly available. It would be good to see other publishers being similarly proactive (if your publisher has a set of guidelines, let me know and I’ll share it). ​ The Wiley guidelines underpin clarity and transparency on where AI is being used, which seem essential principles. But there’s a tension in this: new research suggests that readers’ perceptions of content shift when they are made aware of AI involvement, with lower levels of trust and engagement—though this is offset when readers have greater levels of AI literacy. To be clear, I do not think anyone should take this as justification to obscure AI use, but it’s a reminder that AI remains a nuanced and contested topic. ​ Overdrive recently added an AI book curation and recommendation feature to its library app Libby: in this interview, CEO Steve Potash discusses the feature, dealing with user scepticism, and whether it can help to arrest the decline in reading.

Greetings from New York City, where I’ve been on a working vacation for the last week. It’s my first time back since Covid, and besides the inevitable changes to the city (I could date the last fifteen years of photos by the maturity of the foliage on the High Line) the thing that’s struck me is the ubiquity of technology. Every billboard in Midtown is for an enterprise AI tool, and while this was primarily family time, I had some good conversations with publishers about their use of AI.

I’m in New York with the family. We were up early for Brooklyn Bridge Parkrun—a very enjoyable, fast, flat course along the waterfront—followed by a cooldown walk around Cobble Hill and Brooklyn Heights.

For the first time in a while, I didn’t go to Frankfurt Book Fair and experienced it vicariously through Slack, WhatsApp and press updates. My impression was a lot of conversation about AI, and a lot of publishers talking more than doing. Many years ago I was introduced to Seth Godin. After our mutual friend had explained my role at a major publisher, Godin smiled and replied with one of his catchphrases: “Great, but what have you shipped?” I thought of that moment while reading some of the CEO platitudes from the Fair. So what did I miss? If you shipped something new this week, hit reply and let me know.