Why I Resist Generative “AI” – Esther Weidauer

Esther Weidauer, a software developer with roughly 15 years of professional experience and 25 years of programming, published a collection of arguments against generative AI, arguing the current hype conflates a half-century of disparate technologies under one label. She defines today’s “AI” as generative systems producing text, images, and other media from prompts, plus derivatives such as AI agents, and traces the term through 1950s–60s formal-logic systems, the subsequent “AI winter,” 1980s expert systems, and the present neural-network revival. Weidauer, who has built search engines and implemented neural networks and is completing a psychology degree with a statistics thesis, attributes the revival to neural networks’ strength at statistical pattern recognition when fed massive datasets and computing capacity. The piece responds to common pro-AI claims and supplies sources, with sections designed to be read independently. It matters as a practitioner’s structured counterpoint amid accelerating enterprise adoption of generative tools; watch whether her critiques gain traction among technical audiences and influence procurement and disclosure debates.