Hybrid Methodology: Combining Ethnography, Cognitive Science, and Machine Learning to Inform the Development of Context‐Aware Personal Computing and Assistive Technology

Abstract

The not‐too‐distant future may bring more ubiquitous personal computing technologies seamlessly integrated into people's lives, with the potential to augment reality and support human cognition. For such technology to be truly assistive to people, it must be context‐aware. Human experience of context is complex, and so the early development of this technology benefits from a collaborative and interdisciplinary approach to research—what the authors call “hybrid methodology”—that combines (and challenges) the frameworks, approaches, and methods of machine learning, cognitive science, and anthropology. Hybrid methodology suggests new value ethnography can offer, but also new ways ethnographers should adapt their methodologies, deliverables, and ways of collaborating for impact in this space. This paper outlines a few of the data collection and analysis approaches emerging from hybrid methodology, and learnings about impact and team collaboration, that could be useful for applied ethnographers working on interdisciplinary projects and/or involved in the development of ubiquitous assistive technologies.