Meta’s decision to end its professional fact-checking program sparked a wave of criticism in the tech and media world. Critics warned that dropping expert oversight could erode trust and reliability in the digital information landscape, especially when profit-driven platforms are mostly left to police themselves.

What much of this debate has overlooked, however, is that today, AI large language models are increasingly used to write up news summaries, headlines and content that catch your attention long before traditional content moderation mechanisms can step in. The issue isn’t clear-cut cases of misinformation or harmful subject matter going unflagged in the absence of content moderation. What’s missing from the discussion is how ostensibly accurate information is selected, framed and emphasized in ways that can shape public perception.

Large language models gradually influence the way people form opinions by generating the information that chatbots and virtual assistants present to people over time. These models are now also being built into news sites, social media platforms and search services, making them the primary gateway to obtain information.

Studies show that large language models do more than simply pass along information. Their responses can subtly highlight certain viewpoints while minimizing others, often without users realizing it.

My colleague, computer scientist

© The Conversation