Knowledge Silos as a Barrier to Responsible AI Practices in Journalism

As AI systems increasingly intertwine in newsroom workflows, concerns about transparency, accountability, and ethical decision-making continue growing. While governments, academia, industry, and civil society work to establish guidelines and governance frameworks, journalists on the front lines still face technical and cultural challenges when integrating these technologies into their daily workflows.

In this talk, I'll tap into the concept of "knowledge silos" in news organizations to explain how they pose a significant barrier to responsible AI adoption. Essentially, knowledge silos occur when various teams, be it reporters, editors, data analysts, or business strategists, operate in isolation, with minimal communication or information sharing between them. This fragmentation means that while one group might lead the use of new AI tools inside the newsroom, another may lack the context or expertise needed to understand the ethical and editorial implications fully. The result is a disjointed decision-making process that can compromise journalistic integrity and public trust.

I'll explore how breaking down these silos can pave the way for more cohesive and ethically sound AI practices in journalism, ensuring that technological advancements improve rather than undermine the core values of each individual newsroom.

Programme