An information processing method implemented by a computer, the information processing method comprising: obtaining a piece of first data and a piece of second data, the piece of second data being not included in a training dataset, said training dataset used for training an inferencer, and the inferencer configured to output a recognition or detection result for one or more pieces of data, wherein each of the piece of first data and the piece of second data is a piece of sensing data comprising a piece of image data obtained through sensing by a camera; wherein the piece of first data is a piece of data for which a false recognition or detection result is output; calculating, by using a piece of first relevant data, a first contribution, to a first recognition or detection result output, representing respective contributions of portions constituting the piece of first data, to a piece of first output data output by inputting the piece of first data to the inferencer, the piece of first relevant data being obtained by inputting the piece of first data to the inferencer trained by machine learning using the training dataset; calculating, by using a piece of second relevant data, a second contribution, to a second recognition or detection result output, representing respective contributions of portions constituting the piece of second data, to a piece of second output data output by inputting the piece of second data to the inferencer, the piece of second relevant data being obtained by inputting the piece of second data to the inferencer; and determining whether to add the piece of second data to the training dataset for the inferencer, according to a degree of similarity between the first contribution and the second contribution, wherein, if the second contribution comprises a higher degree of similarity to the first contribution, the piece of second data is added to the training data, or, if the second contribution does not comprise a higher degree of similarity to the first contribution, the piece of second data is not added to the training data. obtaining a piece of first data and a piece of second data, the piece of second data being not included in a training dataset, said training dataset used for training an inferencer, and the inferencer configured to output a recognition or detection result for one or more pieces of data, wherein each of the piece of first data and the piece of second data is a piece of sensing data comprising a piece of image data obtained through sensing by a camera; wherein the piece of first data is a piece of data for which a false recognition or detection result is output; calculating, by using a piece of first relevant data, a first contribution, to a first recognition or detection result output, representing respective contributions of portions constituting the piece of first data, to a piece of first output data output by inputting the piece of first data to the inferencer, the piece of first relevant data being obtained by inputting the piece of first data to the inferencer trained by machine learning using the training dataset; calculating, by using a piece of second relevant data, a second contribution, to a second recognition or detection result output, representing respective contributions of portions constituting the piece of second data, to a piece of second output data output by inputting the piece of second data to the inferencer, the piece of second relevant data being obtained by inputting the piece of second data to the inferencer; and determining whether to add the piece of second data to the training dataset for the inferencer, according to a degree of similarity between the first contribution and the second contribution, wherein, if the second contribution comprises a higher degree of similarity to the first contribution, the piece of second data is added to the training data, or, if the second contribution does not comprise a higher degree of similarity to the first contribution, the piece of second data is not added to the training data.