🔍 Trust Is a System, Not a Feeling
We often talk about trust in AI as if it is an emotion we either have or do not have. But trust does not scale through feelings. Trust scales through systems, the visible structures that tell us what happened, why it happened, and what we can do when something goes wrong. ------------- Context: Why “Just Be More Careful” Is Failing ------------- As synthetic content becomes more common, many people respond with a familiar instruction: be more careful, double-check, trust your gut. That advice sounds reasonable, but it quietly shifts the entire burden of trust onto individuals. In practice, individuals are already overloaded. We are navigating faster communication, more channels, more content, and more urgent expectations. Adding constant verification as a personal responsibility does not create safety. It creates fatigue, suspicion, and inconsistent outcomes. The deeper issue is that the internet and our workplaces were built for a world where content carried implicit signals of authenticity. A photo implied a camera. A recording implied a person speaking. A screenshot implied a real interface. We are now in a world where those signals can be manufactured cheaply and convincingly. So the question becomes less about whether people can detect fakes, and more about whether our systems can support trust in the first place. When trust is treated as a personal talent, it becomes fragile. When trust is treated as an operational design problem, it becomes durable. ------------- Insight 1: Detection Is a Game We Cannot Win at Scale ------------- It is tempting to make trust a contest. Spot the fake. Find the glitch. Notice the strange shadow. Compare the audio cadence. This mindset feels empowering because it suggests that skill equals safety. But detection is inherently reactive. It assumes the content is already in circulation and now we need to catch what is wrong with it. As generation quality improves, the tells become fewer, subtler, and more context-dependent. Even if some people become excellent at detection, the average person will not have the time, tools, or attention to keep up.