Distraction Machines? Machine Learning and the Conditions for Attention

In recent years, it has been argued that something has happened to our capacity to be attentive, as a consequence of the ubiquity and power of digital technology. Are computing machines distraction machines? This paper takes this question as its starting point, in order to argue that the conditions for the capacity to pay attention in a digital age need to be analysed vis-à-vis the emergence of artificial cognitive agents driven by computational technologies. In the twenty-first century, we pay attention alongside machines that are already, in a sense, paying attention. What happens when we are distracted, and machines select and order information not with us, but for us?

M. Beatrice Fazi is Research Fellow in Digital Humanities & Computational Culture at the Sussex Humanities Lab (University of Sussex, UK). Her primary areas of expertise are the philosophy of computation, the philosophy of technology and the field of media philosophy. Beatrice’s current work investigates the limits and potentialities of formal reasoning in relation to computation, and aims to offer a re-conceptualisation of contingency within formal axiomatic systems vis-à-vis technoscientific notions of incompleteness and incomputability. This research is part of a forthcoming monograph that considers how indeterminacy shapes the ontological foundation of computational aesthetics.