Instructor: IAN LOWRIE
Approx 1 hr 43 min. This video presents the lecture portion of a half-day tutorial. Case studies and a bibliography are provided for your use.
Instructor Ian Lowrie describes the organizational and technological aspects of modern data pipelines, framing data science ethnographically as a knowledge practice and data scientists as a particular kind of expert. He also explores methodological approaches to studying data work in real-world contexts. Participants learned to:
Think ethnographically about data work as a knowledge practiceDevelop methodological strategies for studying data workChart the organizational and technological components of data infrastructureInterpret the mindset, jargon, and practical orientations of their data scientist and developer colleaguesUnderstand how algorithmic systems and data analytics impact organizational structures, work practices, and business models
In the second half of the tutorial, participants worked collaboratively to develop a pitch for...
Systems Change Consultant
Case Study—In 2016 The Chicago Community Trust (“The Trust”), a local Chicago foundation, partnered with Roller Strategies (“Roller”), an international professional services firm, to deploy an innovative mixed-methods approach to community-driven social change on the South Side of Chicago. This partnership convened a diverse group of stakeholders representing a microcosm of the social system, and launched a project with the aim of developing resilient livelihoods for youth aged 18-26 in three specific South Side neighborhoods. Roller designed and facilitated a process through which the stakeholder group scoped, launched, piloted and prototyped community-driven initiatives. While innovative and successful by some metrics, the project had its challenges. The convening institutions and their staff were often perceived as “outsiders” and “experts” without intimate local knowledge of the social challenges they were attempting to address. This dynamic played out in complex power...
LARRY S. MCGRATH
Design Science Consulting, Inc.
Using eye tracking in ethnographic research poses numerous theoretical and practical challenges. How might devices originally intended to record individuals' vision of two-dimensional planes be useful in interpersonal contexts with dynamic visual interfaces? What would the technology reveal about collegial environments in which different levels of knowledge and expertise come together and inform decision-making processes? Why would pupil movement show us anything that conventional ethnographic methods could not? In this paper, I argue that these challenges are not intractable. When tailored to specific questions about perception, action, and collaboration, eye trackers can reveal behaviors that elude ethnographers' gaze. In so doing, the devices enrich the observational and interview-based methods already employed in ethnographic studies of workplace dynamics.
Hospitals are a fruitful context in which to test the value of eye-tracking evidence. Healthcare professionals look, interpret,...
Founder, CEO, Acesio Inc.
Head of Behavioral and Organizational Research, Acesio Inc.
The focus of this paper is to investigate deep learning algorithm development in an early stage start-up in which edges of knowledge formation and organizational formation were unsettled and contested. We use a debate by anthropologists Clifford Geertz and Claude Levi-Strauss to examine these contested computational forms of knowledge through a contemporary lens. We set out to explore these epistemological edges as they shift over time and as they have real practical implications in how expertise and people are valued as useful or non-useful, integrated or rejected by the practice of deep learning algorithm R&D. We discuss the nuances of epistemic silences and acknowledgments of domain knowledge and universalizing machine learning knowledge in an organization that was rapidly attempting to develop algorithms for diagnostic insights. We conclude with reflections on how an AI-Inflected Ethnography perspective...
Think-Ng and Mayo Clinic Download PDF
PechaKucha—As an author of a book about ice cream around the world, I am often asked this question: What is the best ice cream? I am often stumped. I know that they want something that they don’t know from the “expert”. So when I hesitantly answer, I would give my personal favorite, one that I discovered during my travels—a goat cheese ice cream with roasted cherries from Jeni’s Ice Cream in Columbus, Ohio. Yet I was curious—why do people ask that question if it could be potentially disappointing? Do they really want the #1 based on my personal opinion? Did they want to find something new to try? Were they trying to understand my motivation? Were they curious about a story? I unravel this question through an investigation of the intention of the question. When applied to ethnography, how does that question apply? As ethnographers, do we miss an important insight if we don’t ask about the best?
Jennifer Ng just joined Mayo Clinic as a senior user experience designer....
Stripe Partners TOM HOY
This paper explores two different forms of knowledge. We compare embodied understanding with propositional or abstract knowledge. Ethnographic research, with its commitment to understanding through immersion and engagement in social fields produces dexterous, intuitive and practical cultural knowledge, which is highly suited towards culturally attuned activity. We argue that ethnography can often be reduced to propositional knowledge as a result of the lack of team participation in research and how we communicate insight. Ideas of professional expertise sit behind the division of labour that characterises client-researcher relationships. Accompanying that division of labour is a need for the communication of ethnographic research to bridge the gap between client and external worlds – the world we as researchers explore and that our clients needs to act in. By engaging our clients in shared, immersive experiences we can create the conditions for them to develop ‘know how’ about...