Autor/-in: George Campbell

My name is George, and I wrote a book about why AI feels smarter than it is, how it was built to agree with you, and what that does to the people using it. And about how challenging it is for AI to align with the human worlds of finance, geopolitics, parenting, and education. Maybe a few stories about robot love too. Humans are the characters. AI is the topic. It's an investigation into the psychological and architectural machinery running beneath every AI conversation, and into what's happening to the humans on the other side of the screen. I cover industry developments, alignment failures, data center economics, and human entanglements, filtered through the questions I keep asking. Who set the reward signals. Who is doing the thinking. What does the data really show. Did anyone ask you. I've spent my career at the intersections where technology meets markets and humans. Internet strategy consulting at Scient through the final two years of the dot-com boom, close enough to watch an industry believe its own hype in real time (our motto: Go Big or Go Home. ). Hybrid electric vehicles at Navistar before electrification was a culture war (I still remember delivering the first hybrid UPS van in Atlanta). The North American launch of the Dyson Airblade, which turned a hand dryer into a product people talked about (I could write a book about the palace intrigue there). The refinancing and construction behind the Argonne National Laboratory facility expansion to house the Aurora supercomputer (where I learned that AI infrastructure runs on chillers, leases, and coverage ratios before it runs on chips). And decades of consulting across industries where the pattern is always the same: new technology arrives, humans react in predictably messy ways, and the people selling it would rather you not think too carefully about why. I'm not a doomer and I'm not a hype man. I'm an observer with a framework and enough time in enough industries to see the angles that aren't getting covered: the human element of AI adoption, the incentive structures shaping the tools, and the gap between what these systems are designed to do and what their users believe is happening.