 Phenomenology has not only been used to address questions of philosophical anthropology, as one might suggest is the case with Heidegger and Stiegler. Hubert Dreyfus (1992) has used it very effectively to provided a devastating critique of the classical program in artificial intelligence (AI) research. In his critique Dreyfus (1992) argues that the way skill development has become understood in the past has been wrong. He argues—using the earlier work of Heidegger in Being and Time—that the classical conception of skill development, going back as far as Plato, assumes that we start with the particular cases and then abstract from these to discover and internalize more and more sophisticated and general rules. Indeed, he argues, this is the model that the early artificial intelligence community uncritically adopted. In opposition to this view he argues, with Heidegger, that what we observe when we learn a new skill in everyday practice is in fact the opposite. We most often start with explicit rules or preformulated approaches and then move to a multiplicity of particular cases, as we become an expert. His argument draws directly on Heidegger’s account in Being and Time of humans as beings that are always already situated in-the-world. As humans ‘in-the-world’ we are already experts at going about everyday life, at dealing with the subtleties of every particular situation—that is why everyday life seems so obvious. Thus, the intricate expertise of everyday activity is forgotten and taken for granted by AI as an assumed starting point.