In this Substack post, Mia Kotalik explains how a recently introduced Google feature—powered by AI—produced strange or misleading outputs, sparking online backlash. Rather than treating it as proof that AI is reckless or sentient, she frames the incident as a predictable outcome of deploying probabilistic language systems at scale inside products people rely on for authoritative answers. The episode exposed a deeper tension: users expect certainty and reliability from search, while AI systems generate responses based on patterns, not grounded understanding.

Mia argues that the controversy says as much about public expectations and platform incentives as it does about the technology itself. When companies integrate generative AI into core infrastructure without clearly communicating limitations, errors feel like betrayals. The takeaway isn’t that AI is “out of control,” but that product design, transparency, and incentive structures determine whether these systems clarify information—or amplify confusion.