JOHN SHERRY

Contributed Articles

Scale and the Gaze of a Machine

RICHARD BECKWITH Intel Labs JOHN W. SHERRY Intel Labs Scale suffuses the work we do and, recently, has us considering an aspect of scale best suited to those with ethnographic training. We've been asked to help with scaling up one of the latest blockbusters in high tech – deep learning. Advances in deep learning have enabled technology to be programmed to not only see who we are by using facial ID systems and hear what we say by using natural language systems; machines are now even programmed to recognize what we do with vision-based activity recognition. However, machines often define the objects of their gaze at the wrong scale. Rather than “look for” people or objects, with deep learning, machines typically look for patterns at the smallest scale possible. In multiple projects, we've found that insights from anthropology are needed to inform both the scale and uses of these systems. Keywords Deep Learning, Human Scale, Ethnographic Insights Article citation: 2020 EPIC Proceedings...

Pathmaking, A Dialogue: Keynote Address

JOHN F. SHERRY, JR. Herrick Professor of Marketing, Mendoza College of Business, and Professor of Anthropology, University of Notre Dame JOHN W. SHERRY Director, User Experience Innovation Lab, Intel Corporation KEYNOTE ADDRESS John F. Sherry, Jr. is Herrick Professor of Marketing at the University of Notre Dame. He has researched, lectured, and consulted around the globe on issues of brand strategy, experiential consumption, and retail atmospherics. He is widely published and a Fellow of the American Anthropological Association and the Society for Applied Anthropology. He is a past President of both the Association for Consumer Research and the Consumer Culture Theory Consortium, and a former Associate Editor of the Journal of Consumer Research. His most recent book is Resurgence: The Four Stages of Market-Focused Reinvention (with Gregory S. Carpenter & Gary F. Gebhardt). Read more about John, his take on the future of ethnography in business, and why he thinks pathmaking is more like bushwhacking for academics and...

ICT4D => ICT4X: Mitigating the Impact of Cognitive Heuristics and Biases in Ethnographic Business Practice

TONY SALVADOR, JOHN W. SHERRY, L. WILTON AGATSTEIN and HSAIN ILAHIANE With more than five billion people, large corporations have expressed non-trivial interest in “emerging markets” as potential future sources of revenue. We in this community of ethnographic praxis, are privileged to move with some ease between corporate board rooms and people’s living rooms around the world. Yet, our messages and meanings that might lead to positive action are hampered by both our own language – that of development – and the ways in which people hear our language through specific cognitive heuristics and biases. In this paper, we specifically unpack the prevalent business interest concerning the “digital divide”. We discuss how that particular framing, i.e., digital, divide, essentializes upwards of 85-90% of the global population as simply poor and living in developing countries limiting business engagement. We argue that these predilections are further magnified by specific cognitive heuristics and biases we all posses but which are...

The Cackle of Communities and the Managed Muteness of Market

JOHN W. SHERRY Researchers at EPIC face something of a trap. Situated in an ethos of twenty first century consumer capitalism, our professional duties overemphasize individual consumers, and the products of our research always diverge towards our respective corporations’ interests. As a result we have little basis for collective enterprise as a discipline. However, if we remember that human beings are always part of naturally occurring social systems (communities, work organizations, etc.) we might find we have more to say, both to our corporations and among ourselves. When we shift our perspective this way we find our work is as much about catalyzing human social systems as it is about understanding “the consumer.” This paper uses three examples from my own experience at Intel to explain, and highlights some implications of this shift: we must adopt multiple levels of analysis, attend to the fact that structures emerge from human interaction, and account for divergent interests, needs and abilities as these networks form....