The AI for Media Network is proud to present its first publication: The whitepaper “How Media Can Remain Visible in the AI Era” examines the challenges posed by AI to the production and distribution of journalistic content and provides actionable recommendations for media companies on how to navigate this disruption.
On November 13 and 14, 2024, the AI for Media Network, in collaboration with the Akademie für Politische Bildung in Tutzing, hosted a symposium titled “AI-Mediated Media Environment: Boosting Media for an AI-Driven Information Ecosystem.” The event focused on how quality media can maintain their relevance in an age where media content is increasingly created, curated, and disseminated with the help of AI, and how they can adapt both organizationally and technically to this disruption. The English-language symposium was attended by 60 AI experts from various media companies and academia.
Recommendations and Product Ideas
The findings from the symposium have been compiled in our whitepaper “How Media Can Remain Visible and Contribute to a Trustworthy AI Ecosystem.” The whitepaper analyzes how media consumption is evolving in the AI era and offers media companies recommendations on how to continue, or even improve, their reach with high-quality content. One chapter presents ideas for infrastructure projects and user-centric products.
Collaboration with Media Lab Bayern
The whitepaper is a collaborative effort with Media Lab Bayern, an initiative of Medien Bayern GmbH, which supports startups and media companies in developing and implementing innovative ideas. Media Lab contributed a chapter to the whitepaper, featuring insights from five projects supported by the lab, detailing the lessons learned during the development of their AI solutions.
The whitepaper is complemented by a glossary explaining key AI terms and concepts. An English version will be available shortly.
The 48-page German version paper is available for free download via this form.
Audio version created by Google Notebook LM
We also uploaded the whitepaper to Google’s notebook LM, here you can listen to the result:
