Over the last half century, global healthcare practices have increasingly relied on technological interventions for the detection, prevention, and treatment of disability and disease. As these technologies become routinized and normalized into medicine, the social and political dimensions require substantial consideration. Such consideration is particularly critical in the context of ableism, in which bodily and cognitive differences such as disabilities are perceived as deviance and demand intervention. Further, neoliberalism, with its overwhelming tendency to privatize and individualize, creates conditions under which social systems abdicate responsibility for social issues such as ableism, shifting accountability onto individuals to prevent or mitigate difference through individualized means.

It is in this context that this dissertation, informed by critical disability studies and feminist science and technology studies, examines the understanding and enactment of disability and responsibility in relation to biomedical technologies. I draw from qualitative empirical data from three distinct case studies, each focused on a different biomedical technology: prenatal genetic screening and diagnosis, deep brain stimulation, and do-it-yourself artificial pancreas systems. Analyzing semi-structured interviews and primary documents through an inductive framework that takes up elements of Grounded Theory and hermeneutic phenomenology, this research demonstrates a series of tensions. As disability becomes increasingly associated with discrete biological characteristics and medical professionals claim a growing authority over disabled bodyminds, users of these technologies are caught in a double bind of personal responsibility and epistemic invalidation. Technologies, however, do not occupy either exclusively oppressive or liberatory roles. Rather, they are used with full acknowledgement of their role in perpetuating medical authority and neoliberal paradigms as well as their individual benefit. Experiential and embodied knowledge, particular when in tension with clinical knowledge, is invalidated as a transgression of expert authority. To reject these invalidations, communities cohering around subaltern knowledges emerge in resistance to the mismatched priorities and expectations of medical authority, creating space for alternative disabled imaginaries.

Usability in the Internet of Things (IOT) in the Smart Home is a new concept with limited current research, especially in user perception. User perception is an important aspect in the development of Smart Home Internet of Things systems, including smart home products and devices and in the design of the Smart Home experience. The aim of my thesis is to investigate user perceptions of Smart Home Internet of Things systems to understand how usable current Smart Home Internet of Things systems are from the perception of the user and how that impacts the Smart Home experience. By understanding the usability of Smart Home Internet of Things systems, we can better design Smart Home devices and products for a user-centered experience. My thesis informs the design of user-centered Smart Home Internet of Things systems and experiences.

This study includes a literature review and an empirical study. The empirical study is a usability testing survey that investigates user perceptions of Smart Home technology that make up the Internet of Things system in the Smart Home. Both closed-ended questions and open-ended questions are included in the survey for a comprehensive study. Main results showed that current smart home systems are somewhat usable. Results also showed that smart home users are satisfied with current smart home systems, believes that smart home technology adds value to their lifestyle, and will continue to use smart home technology. Main results showed that the strengths of current smart home systems design are efficiency, learnability, memorability, and enjoyability. Main results showed that there is a trend between age group and smart home user perceptions. These findings inform the design of user-centered smart home systems.