(Re)computing Electronic Waste: Computational Approaches to Reducing, Reusing, and Recycling E-Waste

Over the past sixty years, computers have dramatically changed in form, first emerging as the whole room sized ENIAC and now into something we can fit in our pockets. Computing has dramatically changed the world we live in, too. Whereas previously, immense resources, time, labor, and energy had to be dedicated to performing computational programs, now we expect computing to be seamlessly integrated into our daily lives, unobtrusive, and from the `cloud'. Within this dramatically changing landscape of computing technologies, there remains a constant: the rapid generation of new computing devices shadowed by the rapid generation of electronic waste. Computing research has advanced the development of new devices without addressing old devices that become wasted as a result. By contrast, this dissertation examines how computing research can be employed in addressing new strategies for reducing, reusing, and recycling electronic waste. This dissertation presents four research projects that employ different research methods and computational strategies to probe into alternative strategies to address electronic waste. These projects scaffold new pathways to recycling, reusing, and reducing electronic waste. First, in studying existing practices in reusing electronic waste across a diversity of practitioners and geographic contexts. Second, exploring the development of two computational systems that demonstrate how we can leverage computational capabilities to enable reuse of e-waste material (electronic components and printed circuit boards) that would previously be untenable. Finally, in exploring how novel devices can serve as design probes into alternative human-device relationships, eliciting new perspectives into designing for care in interactive devices. By leveraging perspectives across computer science, electrical engineering, computer engineering, media studies, human-computer interaction, and sustainability studies, this work attends to the complexity of the e-waste issue and lays the groundwork for envisioning how computational systems can be employed in managing e-waste responsibly.