Most organizations still make big decisions the same way they did decades ago: meetings, slides, peer reviews, and a lot of confident opinions. Yet some of the world’s most sophisticated companies — from Big Tech to pharma — quietly use a very different tool when forecasting matters: prediction markets. These systems look like “betting,” but they’re really about one thing: extracting honest probabilities from people who know more than they’re willing (or able) to say in meetings. This post explains what prediction markets are, how they compare to the Delphi method, and why modern organizations increasingly blend both. What does “betting” at work actually mean? A prediction market is an internal marketplace where employees trade on future outcomes , such as: Will a product ship by a certain date? Will revenue exceed a given target this quarter? Will a clinical trial reach its next phase? Each outcome has a price between 0 and 1 (or 0–100). That price represents the collective probabilit...
Moravec’s Paradox: What It Means for Engineers, AI, and Our Kids Artificial intelligence keeps surprising us. It writes code, trades stocks, beats world champions at chess — yet struggles with things a toddler does effortlessly: recognizing context, moving in the physical world, or understanding common sense. This contradiction has a name. What is Moravec’s Paradox? Moravec’s Paradox states: Tasks that are easy for humans are hard for computers, and tasks that are hard for humans are often easy for computers. In simple terms: Computers excel at logic, calculations, and formal rules Humans excel at perception, intuition, movement, and social understanding This feels backwards — and that’s why it’s called a paradox. Why is it called “Moravec’s” Paradox? The concept was articulated in the 1980s by Hans Moravec , a robotics researcher at Carnegie Mellon University. At the time, most AI researchers believed that: Once we solve high-level reasoning (chess, math, logic), everything else will...