Ideas Weave Every Narrative with AI.
AI chatbots confidently generate historical facts that are often wrong. Asking ChatGPT ‘Who was the first Indian PM to visit Palestine?’ gave the wrong answer—erasing Nehru’s 1960 visit. This isn’t a bug; it’s the core design of probabilistic text generation. In a world of synthetic confidence, primary sources like newspaper archives become more valuable than ever. Trust the archive, not the algorithm.
Google Earth now integrates AI-generated imagery as default, turning a trusted mirror of the world into a synthetic canvas. This erosion of geographic truth isn’t a bug—it’s a deliberate strategy to prioritize aesthetics over accuracy. Readers are left to wonder: if the map is a lie, what else is?
Treating AI-generated code like a junior developer’s work is a dangerous oversimplification. Junior developers learn from feedback; AI silently hallucinates new errors without memory. You need a different pipeline: isolate AI code behind strict contracts, use property-based testing, and track it as a separate artifact. The real risk isn’t bad code—it’s unpredictable, non-learning errors that only surface in production.
AI hallucinations aren’t bugs — they’re the system working exactly as designed. Large language models are probabilistic text generators that guess the next most plausible word. The real danger isn’t the lies they tell, but our willingness to believe them because they sound so confident. We must stop trying to fix hallucinations and instead build systems that treat all AI output as inherently unverified.