Which news publishers are blocking OpenAI? These are 497 news organizations (and counting) that have told GPTBot not to scan their sites, according to a survey by homepages.news. They make up 44.3% of the 1,123 online publishers surveyed. palewi.re/docs/news-homepage…

AI-Imagined Newsroom Interiors by Renowned Architects: Which Would You Choose to Work In? 1. Zaha Hadid

What if you could get tomorrow's news today? I've been reflecting on the idea of "pre-news" ever since I came across this illustration detailing the amount of time the Associated Press took to publish the iconic photograph of the self-immolating monk, captured in June of 1962 by American journalist Malcolm Browne in Saigon. Back then, it required 9,000 miles of wire cable and over 15 hours for that image to become "breaking news." Over the following decades, technological advancements have drastically reduced the time needed for a news event to be transmitted. If that event were to happen today, we'd likely witness it in real-time via live streaming, bringing the time required to disseminate information close to zero. Yet, technology's march forward hasn't halted. The correlation between technological innovation and the speed of information dissemination persists, which means we are now venturing into negative time frames. But what does this "negative time" imply? It suggests the potential to identify early signals before an event transpires. With AI's increasing ability to capture, quantify, and comprehend chains of vents, we're moving from breaking news to calculating it. Will you trust predictive journalism?

AI feeding on itself leads to 'information inbreeding,' which can cause models to collapse. Journalism could be the lifeline! News organizations provide a rich variety of training data that enhances large language models, but this resource is finite. If we consider AI as a living organism, there comes a time when it has consumed all available human-generated information — and this will be accelerated if we don’t have a sustainable model for journalism. At that point, the AI may depend solely on synthetic, AI-generated data, creating a closed loop of information. This can be likened to biological inbreeding, where reproduction occurs only within the same genetic pool of data. Much like how inbreeding weakens an organism's genetics, leading to a less healthy population, AI using only its own data can result in "information inbreeding”, which is most commonly referred as model collapse. This leads to a decline in the richness, diversity, and quality of AI's output, similar to the health deterioration seen in biological inbreeding. Information inbreeding can extend beyond AI, influencing society by creating uniform, AI-generated information that lacks human perspective. This may cause the public to have a limited and repetitive perspective, hindering how connect and evolve together — creating a world stuck in a loop of monotonous, unoriginal thinking. That’s why AI companies must have a vested interest in the sustainability of diverse information sources like journalism. This is not only ethically sound, but also the best strategic bet in the long run. Without diverse, fresh, human-driven data, tech companies risk endangering the well-being of their models and leading to stagnant or even regressive AGI development.

I finally touched the physical copy of my new book for the first time, a nice surprise to brighten my quarantine days 🙏 Newsmakers: Artificial Intelligence and the Future of Journalism is a practical guide about news technology and the innovators implementing it 💪