Cheap Forecasts, Expensive Verification: Who Pays for AI Fear

The article explores the economics of content creation and verification in the age of neural networks. The core argument is that AI has drastically reduced the cost of generating forecasts and expert-sounding texts, making them mass-produced and accessible. However, verifying such information remains an expensive process requiring human effort. Unlike software code, which has automated tests and objective success criteria, AI forecasts often lack an 'anchor'—they cannot be verified instantly. This creates a situation where producing irresponsible claims is cheap, while the burden of refutation falls on experts and the community. The author emphasizes that the lack of accountability for erroneous forecasts, combined with the ease of their creation, leads to the spread of misinformation, requiring readers to take a more critical approach to sources and the motivations behind research reports.