論文アブストラクト： In this paper we explore the motivations for, and practicalities of, incorporating "implications for adoption" into HCI research practice. Implications for adoption are speculations which may be used in research projects to scrutinize and explore the implications and requirements associated with a technology's potential adoption in the future. There is a rich tradition within the HCI community of implementing, demonstrating, and testing new interactions or technologies by building prototypes. User-centered design methods help us to develop prototypes to and move toward designs that are validated, efficient, and rewarding to use. However, these studies rarely shift their temporal focus to consider, in any significant detail, what it would mean for a technology to exist beyond its prototypical implementation, in other words how these prototypes might ultimately be adopted. Given the CHI community's increasing interest in technology-related human and social effects, the lack of attention paid to adoption represents a significant and relevant gap in current practices. It is this gap that the paper addresses and in doing so offers three contributions: (1) exploring and unpacking different notions of adoption from varying disciplinary perspectives; (2) discussing why considering adoption is relevant and useful, specifically in HCI research; (3) discussing methods for addressing this need, specifically design fiction, and understanding how utilizing these methods may provide researchers with means to better understand the myriad of nuanced, situated, and technologically-mediated relationships that innovative designs facilitate.
論文アブストラクト： Machine learning (ML) is now a fairly established technology, and user experience (UX) designers appear regularly to integrate ML services in new apps, devices, and systems. Interestingly, this technology has not experienced a wealth of design innovation that other technologies have, and this might be because it is a new and difficult design material. To better understand why we have witnessed little design innovation, we conducted a survey of current UX practitioners with regards to how new ML services are envisioned and developed in UX practice. Our survey probed on how ML may or may not have been a part of their UX design education, on how they work to create new things with developers, and on the challenges they have faced working with this material. We use the findings from this survey and our review of related literature to present a series of challenges for UX and interaction design research and education. Finally, we discuss areas where new research and new curriculum might help our community unlock the power of design thinking to re-imagine what ML might be and might do.
論文アブストラクト： This paper offers a new theoretical frame for those interested in poverty and design. As digital access rates peak, technology maintenance argues that the digital divide will increasingly manifest in the (in)ability to stay connected. As a novel and conservative test, open-ended data from a 748-person university student survey of technology maintenance were analyzed. Use and ownership were ubiquitous, but students demonstrated variability in coping with the inevitable; disconnection was more burdensome for low-resourced students. Findings extend technology maintenance and are leveraged as a starting point for three calls for action in HCI: 1) the CHI community should research the burdens of poverty in poor and wealthy contexts; 2) new HCI projects should accommodate inconsistent access; and, 3) new design choices should minimize disruption and optimize stability. This requires action at the individual and organizational level as designers create products that consider marginalization but also use expertise to influence policy.