A method for detecting an unbalance error of a machine-learning-based washing machine and the washing machine are provided. The method identifies whether laundry is within an inner drum of the washing machine using a laundry movement identifying model provided in an AI device of a server or the washing machine, measures an unbalance value on the basis of data of unbalance when the laundry is not moving, and then detects an unbalance error. The unbalance error can be more precisely detected without using additional components. The AI device for detecting the unbalance error of the present disclosure can be associated with drones (unmanned aerial vehicles (UAVs)), robots, augmented reality (AR) devices, virtual reality (VR) devices, devices related to 5G service, and the like.