by LIBBY KAUFER and MARIA VIDART-DELGADO, Ad Hoc LLC
Ethnographic methods that center systems-thinking, how knowledge is constructed, and how knowledge is shared among communities are the best approach for developing collective digital products like APIs.
Application Programming Interfaces, commonly known as APIs, connect the front-end interfaces we see when we navigate the internet (like websites and apps) to the back-end systems, or databases, that store information. APIs enable people to carry out transactions online, like purchasing goods, booking flights, or applying for government benefits. While they are invisible to end-users, APIs are crucially important to developers and to the way many websites, programs, and applications function.
Like codebases and databases, APIs are objects consumed collectively and collaboratively by teams of developers who work together to integrate front-end to back-end systems, run tests, and monitor and troubleshoot integration issues. In the context of APIs, typical UX research methods...
University of Technology Sydney
University of Technology Sydney
Effective software quality assurance in large-scale, complex software systems is one of the most vexed issues in software engineering, and, it is becoming ever more challenging. Software quality and its assurance is part of software development practice, a messy, complicated and constantly shifting human endeavor.
What emerged from our immersive study in a large Australian software development company is that software quality in practice is inextricably entangled with the phenomena of productivity, time, infrastructure and human practice. This ethnographic insight — made visible to the organization and its developers via the rich picture and the concept of entanglements — built their trust in our work and expertise. This led to us being invited to work with the software development teams on areas for change and improvement and moving to a participatory and leading role in organizational change.
Keywords: ethnography, entanglements,...
“What can those of us who work in, and maybe even love, computing cultures do about computing’s colonial expansions?”
Sareeta Amrute’s keynote address “Tech Colonialism Today” opened EPIC2019 in a provocative, mobilizing spirit that inspired discussions on stage, in breakout sessions, and around breakfast tables. Sareeta journeyed across time and territory to explore what characteristics make something colonial to begin with, such as extractive and hierarchical systems. As you might guess, she argued that yes, the tech industry today has core colonial attributes. But goal wasn’t just critique; Sareeta showcased counterconduct—the agency that people, communities, and companies have to build alternatives.
If colonial legacies and socioeconomic systems seem a bit “out of scope” as context for standard product or user research projects, check out Sareeta’s award-winning book Encoding Race, Encoding Class. You’ll learn about Meena’s daily tea ritual, hear Bipin describe why he sometimes chooses to write bad code,...
This case study examines how one Artificial Intelligence (AI) security software team made the decision to abandon a core feature of the product – an interactive Knowledge Graph visualization deemed by prospective buyers as “cool,” “impressive,” and “complex” – in favor of one that its users – security analysts – found easier to use and interpret. Guided by the results of ethnographic and user research, the QRadar Advisor with Watson team created a new knowledge graph (KG) visualization more aligned with how security analysts actually investigate potential security threats than evocative of AI and “the way that the internet works.” This new feature will be released in Q1 2020 by IBM and has been adopted as a component in IBM’s open-source design system. In addition, it is currently being reviewed by IBM as a patent application submission. The commitment of IBM and the team to replace a foundational AI component with one that better aligns to the mental models and practices of its...
Agile methodologies have taken hold as a model to be followed in software industry. Among them, Scrum is one of the most used frameworks and has a high level of acceptance among a large range of organizations. The underlying premise of Scrum is that by implementing an iterative and incremental process of development, an organization can become more efficient in coping with unpredictability, thus, increasing the chances of delivering business value. In this paper we use the context of SIDIA, an R&D center based in Manaus (Brazil), to look at how Scrum is practiced, by following Post-its notes, which are commonly used in agile landscapes.
Following previous work on the idea of thinking through things (instead of thinking about things) as an analytic method to account for the ethnographic experience (Henare, 2006), the purpose here is to draw out the capacity of these objects to re-conceive the workplace. We argue that somehow the extensive use of post-its in this specific context...
Few professions appear more at odds, at least on the surface, than ethnography and data science. The first deals in qualitative “truths,” gleaned by human researchers, based on careful, deep observation of only a small number of human subjects, typically. The latter deals in quantitative “truths,” mined through computer-executed algorithms, based on vast swaths of anonymous data points. To the ethnographer, “truth” involves an understanding of how and why things are truly the way they are. To the data scientist, “truth” is more about designing algorithms that make guesses that are empirically correct a good portion of the time. Data science driven products, like those that Uptake builds, are most powerful and functional when they leverage the core strengths of both data science and ethnographic insights: what we call Human-Centered Data Science. I will argue that data science, including the collection and manipulation of data, is a practice that is in many ways as human-centered and subjective...
Nissan Research Center – Silicon Valley
Nissan Research Center – Silicon Valley
Case Study—Recognizing that the movement of cars on the road involves inherently social action, Nissan hired a team of social scientists to lead research for the development of autonomous vehicles (AVs) that engage with pedestrians, bicyclists, and other cars in a socially acceptable manner. We are expected to provide results that can be implemented into algorithms, resulting in a challenge to our social science perspective: How do we translate what are observably social practices into implementable algorithms when road use practices are so often contingent on the particulars of a situation, and these situations defy easy categorization and generalization? This case study explores how our cross-disciplinary engagements have proceeded. A particular challenge for our efforts is the limitations of the technology in making observational distinctions that socially acceptable driving necessitates. We also illustrate...