Mialet is a fellow on The Body in Translation: Historicising and Reinventing Medical Humanities and Knowledge Translation at CAS.

Abstract: My presentation is based on an ethnographic study I am currently conducting in a California facility that trains dogs to recognize hypoglycemic episodes for people with Type 1 Diabetes. I follow how dogs’ noses are transformed into ‘reliable sensors’ capable of alerting and giving feedback to human beings about the state of their bodies in situ—a specific form, I argue, of what we call the Quantified Self. I explore how these dogs are trained to manage 'the self' though the use of disciplinary methods, statistical methods (borrowed from the National Institute of Standards and Technology), and ethology. I show how dogs’ behavioral and emotional reactions are constructed in relation with the environment they inhabit, and calibrated against numbers produced by machines (e.g., glucose meters) that are themselves used to calibrate the scent patches upon which the dogs' noses are trained. If the facility I’m currently studying is adopting scientific methods and is run like a ‘lab', it is also a non-profit organization based on the work of volunteers. It was created against the idea of making a financial profit (e.g., their dogs are given away at no charge); moreover, this organization offers something that they see as being neglected by the big corporations that design the machines that manage Type 1 diabetes: the ‘love’ of a dog, compassion, shared information, etc. By following the creation of a management tool composed of a human, a dog and a machine—a symbiotic tool—I propose the emergence of a new definition of the self that doesn’t stop at the boundary of the flesh. I argue that this distributed self could have practical implications about how we design machines and, at a theoretical level, about what kind of political system we could imagine.