OpenAI, the leading company behind the viral ChatGPT AI chatbot, announced a new partnership with Axel Springer, one of the world’s biggest news publishers.
The collaboration aims to enhance ChatGPT’s knowledge and capabilities around current events and real-time information.
Under the deal, Axel Springer will provide summaries and extracts from its reporting to OpenAI, including articles from major titles like Politico, Business Insider, BILD, and WELT. OpenAI plans to use this content to train its AI systems, as well as surface relevant Axel Springer articles to ChatGPT users when they ask questions tied to recent news.
The summaries provided to ChatGPT will contain attribution back to the full Axel Springer articles, essentially providing publicity and traffic for the publisher. Users will also be able to ask ChatGPT questions that reference the information contained across the German media conglomerate’s journalism brands.
OpenAI and Axel Springer bring news to ChatGPT
The collaboration appears aimed at addressing one of the main criticisms of ChatGPT — its lack of up-to-date knowledge on current events. Services like xAI’s new Grok chatbot boast more real-time intelligence by tapping social media data streams. By licensing recent and archival content from major newsrooms, OpenAI hopes to match and exceed these capabilities.
The Springer deal builds on past OpenAI partnerships with the Associated Press and American Journalism Project to train AI models using journalism. As OpenAI continues to face questions around copyright infringement for scraping content without consent, licensing agreements with major publishers provide legal coverage — but also draw criticism around fairness and compensation for smaller sources.
While the partnership provides clear financial value to Springer, questions remain whether it’s ethical for OpenAI to strike such deals with large publishers while scraping content from independent creators and denying compensation. Striking the right balance around sourcing training data continues to be a complex challenge for even the most well-resourced AI companies.
