The common ground starts with patterns. Actuaries use data to identify patterns in risk and help determine how insurance should be priced. Musicians work with patterns in rhythm, harmony and melody. Akur8 Senior Actuarial Data Scientist Leonardo Stincone sees a particularly direct mathematical link. “Music is math. If you look at it with an actuarial eye, you basically have rhythm, harmonies, they are all based on proportions.”
Data
Why the next AI data race will be for human expertise and knowledge
LLMs can process financial reports, legal documents and scientific papers at enormous scale. But access to that material does not reproduce the judgement of someone who has spent years working in the field. Demand for specialized human input is already supporting a substantial commercial market. A fast-growing segment of companies now connects AI developers with doctors, lawyers, scientists and other specialists who can create and evaluate professional tasks.
Source: Why the next AI data race will be for human expertise and knowledge
Can SME licensing deals be bigger for publishers than AI?
Publishers are already adapting to a distribution environment in which search and AI increasingly mediate how audiences find information. Reuters Institute’s 2026 report found that publishers expect search referrals to fall 43% over the next three years, while Google organic search traffic to more than 2,500 news sites fell 33% globally between November 2024 and November 2025. That pressure is making licensing more relevant.
Source: Can SME licensing deals be bigger for publishers than AI?
How AI Watermark Mandates Could Unmask Journalists Who Never Touched AI
Imagine a scenario where a documentary filmmaker, in the course of making the documentary, captures some damning footage of corporate malfeasance, which she wishes to share with an investigative reporting organization anonymously. Should we be concerned that mandates on AI watermarking might reveal who she is, even if she’s not using AI at all? This doesn’t mean that watermarking shouldn’t be used, but rather, as WITNESS notes, we should be aware of the risks, and seek to counter them.
Source: How AI Watermark Mandates Could Unmask Journalists Who Never Touched AI
Do watermarks spell the end of AI content proliferation?
AI companies are now required to make model outputs detectable as AI-generated under Article 50 of the EU AI Act – or, in other words, watermarked. Responses, however, have been mixed. While Anthropic stated it has seen no notable drop in usage, sentiment has reportedly been shifting, as per Forbes. Some users are concerned that the watermark can appear on text they have only used Claude to edit, making it indistinguishable from wholly generated text and resulting in reputational decline.
Source: Do watermarks spell the end of AI content proliferation?
Does generative AI actually copy artists? Researchers say it’s up for debate
In the study, published in Nature, the MIT researchers Zheng Dai and David Gifford set out to to test whether a generated image can be traced back to a single piece of training data. They were looking specifically at diffusion models, the systems most often used for generating images and video. Their finding? It comes down to how big the training data set is. They found that the more data a model is trained on, the harder it becomes to attribute its output to any particular piece of training data.
Source: Does generative AI actually copy artists? Researchers say it’s up for debate
Apple Music to slap AI labels on Suno tracks
Apple Music has told partners that music “materially generated” on AI platforms such as Suno will carry a “Made With AI” label on the service from later this year. At least, that is, if record labels and distributors tag the music with the relevant metadata before it reaches the platform. It will make a tagging system visible to listeners that Apple Music has run behind the scenes since March, when it introduced what it calls AI Transparency Tags.
Study finds generated images often can’t be traced to training data
When an artificial intelligence image generator produces a portrait, whose work went into it? The question sits at the center of lawsuits, licensing deals, and proposed regulations worldwide. Artists want credit. Companies want clarity. Policymakers want a way to assign responsibility. New work from a team of researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) suggests that for models trained on large datasets, the question may often have no answer.
Source: Study finds generated images often can’t be traced to training data
Hidden Airtag reveals Amazon is trashing rare books to train AI
On Monday, 404 Media revealed that it had connected with a bookseller who agreed to plant an Airtag in a rare book that was part of a bulk order. That Airtag was then tracked to an Amazon AI training facility in Las Vegas that housed a team focused on tearing books from their spines and scanning pages. Apparently tone-deaf to the escalating backlash over destructive book scanning, a logo on the door of that team’s warehouse, VGT3, showed a Tyrannosaurus rex preparing to devour a book.
Hidden Airtag reveals Amazon is trashing rare books to train AI
Anthropic Is Watermarking Every Claude AI Output. Builders Are Already Trying to Break It
Anthropic has begun embedding an imperceptible watermark in all text its newest Claude models generate. The change took effect for models launched in the EU on August 2, 2026, and Anthropic says it will apply worldwide. Anthropic laid out the plan in a support article after signing the EU AI Act’s Code of Practice on transparency. In other words, it’s not exactly volunteering to do this.
Source: Anthropic Is Watermarking Every Claude AI Output. Builders Are Already Trying to Break It