We keep giving machines mountains of data and then act surprised when they still fail basic reasoning. Large models can summarize entire libraries but miss a simple yes-or-no instruction. The problem is not the data. It is our belief that scale equals sense.
Yearly Archives: 2025
105 posts
Humans trust confidence more than truth, which is why AI sounds wiser than it is. The problem is not that machines act certain. It is that people keep mistaking certainty for intelligence.
People keep waiting for AI to start “thinking,” as if a text generator is one epiphany away from enlightenment. It is not thinking. It is autocompleting, and the myth says more about us than the machine.
We built machines to think for us, and then forgot how to ask better questions. This is not a story about intelligence — it’s about the danger of confusing fluency with thought.
Machines can mimic care with perfect timing, but never with consequence. What we’re calling empathy is really performance—fluent, tireless, and hollow.
AI doesn’t make us smarter; it just makes our mistakes faster. What we call intelligence has become a performance, and the audience keeps applauding the algorithm.