Who decides what AI tells you? Campbell Brown, once Meta’s news chief, has thoughts

As artificial intelligence increasingly shapes how people access news and information, a fundamental question emerges: who decides what AI systems tell us? Campbell Brown, former head of news partnerships at Meta, is raising urgent concerns about the disconnect between how technology companies view AI transparency and what consumers actually need to understand.

Brown's perspective highlights a critical divide in how the AI industry approaches information governance. While Silicon Valley engineers and executives focus on technical parameters and algorithmic optimization, everyday users remain largely unaware of how AI systems curate, filter, and present information to them. This gap between corporate understanding and public knowledge has significant implications for media literacy, trust in technology, and democratic information access.

The core issue centers on accountability and disclosure. Technology companies operating large language models and AI systems make editorial decisions about what information gets prioritized, suppressed, or presented—yet most users don't recognize these as editorial choices at all. Brown's observation that conversations "in Silicon Valley" differ fundamentally from conversations "among consumers" underscores how the industry has failed to communicate the human judgment embedded in supposedly neutral systems.

This distinction matters because AI systems aren't objective arbiters of truth. They reflect training data, design choices, and business priorities set by their creators. When consumers don't understand this reality, they may attribute false authority to AI outputs or fail to apply appropriate skepticism.

• AI systems make editorial decisions that affect information access and public discourse
• Significant knowledge gap exists between tech industry understanding and consumer awareness
• Current transparency measures fail to bridge communication between companies and users
• Media literacy regarding AI curation requires public education initiatives
• Regulatory frameworks may need to clarify accountability for AI-generated information
• Corporate incentives don't necessarily align with public information interests

As AI integration accelerates across news, search, and information platforms, establishing clear accountability becomes increasingly urgent. Brown's insights suggest that closing the gap between Silicon Valley's technical perspective and public understanding isn't merely beneficial—it's essential for maintaining informed societies. Without transparent, accessible explanations of how AI systems shape information, users cannot make informed decisions about what they consume.