As algorithms play an increasingly important role in the lives of people and corporations, finding more effective, ethical, and empathetic ways of developing them has become an industry imperative. Ethnography, and the contextual understanding derived from it, has the potential to fundamentally...
Tag: data science
Who and What Drives Algorithm Development: Ethnographic Study of AI Start-up Organizational Formation
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...
ReHumanizing Hospital Satisfaction Data: Text Analysis, the Lifeworld, and Contesting Stakeholders’ Beliefs in Evidence
Case Study—Declining clinician engagement, increasing rates of burnout, and stagnant patient and family experience scores have led hospital leadership at Seattle Children's Hospital to submit requests to a data scientist and an anthropologist to identify key themes of survey comments and provide...
Acting on Analytics: Accuracy, Precision, Interpretation, and Performativity
Case Study—We report on a two-year project focused on the design and development of data analytics to support the cloud services division of a global IT company. While the business press proclaims the potential for enterprise analytics to transform organizations and make them ‘smarter’ and more...
How Modes of Myth-Making Affect the Particulars of DS/ML Adoption in Industry
The successes of technology companies that rely on data to drive their business hints at the potential of data science and machine learning (DS/ML) to reshape the corporate world. However, despite the headway made by a few notable titans (e.g., Google, Amazon, Apple) and upstarts, the advances...
The Stakes of Uncertainty: Developing and Integrating Machine Learning in Clinical Care
The wide-spread deployment of machine learning tools within healthcare is on the horizon. However, the hype around “AI” tends to divert attention toward the spectacular, and away from the more mundane and ground-level aspects of new technologies that shape technological adoption and integration....
Humans Can Be Cranky and Data Is Naive: Using Subjective Evidence to Drive Automated Decisions at Airbnb
Case Study—How can we build fairness into automated systems, and what evidence is needed to do so? Recently, Airbnb grappled with this question to brainstorm ways to re-envision the way hosts review guests who stay with them. Reviews are key to how Airbnb builds trust between strangers. In 2018 we...
Below the Surface of the Data Lake: An Ethnographic Case Study on the Detrimental Effect of Big Data Path Dependency at a Theme Park
Case Study—This case-study details how a team of anthropologists and a team of data scientists sought to help a Middle Eastern theme park make use of their big data platform to measure ‘the good customer experience’. Ethnographic research within the theme park revealed that visitors yearned to...
Revitalising Openness at Mozilla: A Mixed Method Research Approach
Case Study—This is a case about how Mozilla, the open source browser company, set out to reconnect with ‘collaborating in the open’ to regain its competitive advantage. This case describes how a multi-disciplinary research team used ethnographic, market, and data analysis to articulate and clarify...
Reading the Tea Leaves: Ethnographic Prediction as Evidence
Those who work in research know that we live in a world that is strongly influenced by what Tricia Wang has called the quantification bias. More so than other forms of information, numbers have incredible formative power. In our culture, numbers are seen as trustworthy representations of reality...