Embodied cognition is an interpretative—or hermeneutical—cognition inherent in motor-sensory perception intrinsically informed by biological and sociocultural memory, a cognition embedded in the organism as well as the socio-cultural environment interacting with it (Ward et al. TOPOI 36:365–375, 2017), of which technologies are a part. Yet, smart machines are advancing on human abilities to perceive and interpret concerning the accuracy, quantity, and quality of the data processed. Machines process and categorize images, perform classification tasks, they calculate and perform pattern analysis, all machine
learning processes are task-specific. Machine learning processes resemble human interpretative processes; however, these are two very different ways of “dealing with something,” although both can be said to be hermeneutical, one enactive, the other material; the first is a meaning-generating interpretative process, the second a statistics-based information output. The information extracted from all the data fed into the computer is the end-product of machine learning, whereas human interpretative enactments are continuous and necessary for any application of the information output.