Abstract: Provided is a trained artificial intelligence for detecting non-stationarity of an object, which accurately functions even in the presence of an environmental sound. Stationary vibration feature data generated from stationary vibration data that is data about stationary vibration including vibration generated in a stationary state from an object for which detection of non-stationarity is performed based on sound, the stationary vibration feature data being data about a feature of stationary vibration identified by the stationary vibration data, is input to an autoencoder to cause the autoencoder to output estimated stationary vibration feature data. A loss function between the stationary vibration feature data and the estimated stationary vibration feature data is generated, and the autoencoder is trained to minimize a difference therebetween. By repeating the above-mentioned processing, the trained autoencoder is obtained from the autoencoder.