1. A computer-implemented method for data classification and identification, the method comprising: providing, over a computer network, data corresponding to a plurality of training objects to a plurality of training devices each associated with one of a plurality of human annotators, each of the training objects comprising features for classification; displaying the training objects on a display of each of the training devices; receiving, via communication interfaces of at least some of the training devices, classification data comprising at least some of the training objects annotated, via annotation interfaces of the training devices, by at least some of the annotators with classifications for features thereof; acquiring psychometric data characterizing the annotation of the training objects by the annotators; computationally deriving a human-weighted loss function based at least in part on the classification data and the psychometric data, the loss function comprising penalties for misclassification, magnitudes of the penalties increasing with increasing deviation from the classification data; receiving, by a classification device, data corresponding to a query object different from the plurality of training objects; and thereafter, computationally classifying, by a computer processor, at least one feature of the query object based at least in part on the human-weighted loss function.