The AI Stories We Tell – and the Ones We Don't

Why It Matters

Accurate AI reporting is essential for informed public debate, regulatory oversight, and preventing hidden environmental costs.

Key Takeaways

• Media frames AI with hype, fear, and opaque jargon.
• Journalists urged to treat AI like any other human‑built system.
• Coverage often omits data sources, labor practices, and investor motives.
• AI’s climate impact estimates vary wildly, highlighting accountability gaps.
• Global governance frameworks are missing, hindering coordinated AI regulation.

Summary

The session titled “The AI stories we tell – and the ones we don’t” convened a panel of journalists from Politico, the Bureau for Investigative Journalism, Bloomberg, and a climate author to interrogate how media narratives shape public perception of generative AI. The moderators framed AI not merely as a tech beat but as a societal issue demanding rigorous, evidence‑based reporting.

Panelists agreed that current coverage is dominated by hype about breakthroughs and fear of disruption, often cloaked in jargon that obscures the underlying systems. They stressed the need to ask mundane questions about design choices, training data, outsourced labor, investors, and client relationships, rather than presenting AI as a magical black box.

Notable remarks included Neve’s warning that mystification serves corporate interests, Joanna’s observation that stories frequently label anything as “AI” without specifying the technology, and Akalrai’s climate analogy pointing to wildly divergent emission estimates—80 million tons versus 24 million tons for 2025—underscoring a transparency crisis.

The discussion concluded that journalists must build collaborative networks, develop clear metaphors, and push for global governance mechanisms akin to climate accords to hold tech firms accountable. Without such rigor, public understanding remains skewed, policy lagging, and environmental externalities unchecked.

Original Description

Artificial intelligence is one of the defining stories of our time. It is reshaping the knowledge ecosystem, and journalism is both reporting on these changes and navigating them directly as it experiments with how AI can support its own work. This session takes a step back to examine how the media is framing AI and how those narratives shape public understanding. Which angles dominate coverage? Which structural questions receive less attention? Are we asking enough about power and accountability, about infrastructure and labour, about climate impact? We explore what more rigorous, evidence-based coverage could look like in practice, and what it might mean to get this story right.

Speakers: Joanna S. Kao (Senior Editor, Information and Artificial Intelligence, Pulitzer Centre), Niamh McIntyre (reporter on Big Tech team, TBIJ), Akshat Rathi, (senior climate reporter, Bloomberg). Chair: Federica Cherubini (Director of Leadership Development, RISJ)

From our AI and the Future of News 2026 conference, 17 March 2026