decision making

Automation Otherwise: A Review of “Automating Inequality”

by DANYA GLABAU, Implosion Labs What if we thought differently about how to integrate human and machine agencies?  Automating Inequality: How High-Tech Tools Profile, Police, and Punish the PoorVirginia Eubanks2018, 272 pp, St. Martin's Press As I sat down in to write this review of Virginia Eubanks’ latest book, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor, I couldn’t help but consider it in light of the growing restiveness among tech workers in response to their companies’ perceived ethical lapses. Rank and file employees have begun to speak out against the use of big data-driven software systems and infrastructure for ethically questionable ends like warfare, policing, and family separation at the United States-Mexico border. To date, these protests have mired several public-private contracts between government agencies and some of the world’s biggest tech companies in controversy, including Google’s Project Maven, a collaboration with...

Designing for Interactions with Automated Vehicles: Ethnography at the Boundary of Quantitative-Data-Driven Disciplines

MARKUS ROTHMÜLLER School of Architecture, Design and Planning, Aalborg University Copenhagen, Denmark and Shift Insights & Innovation Consulting PERNILLE HOLM RASMUSSEN School of Architecture, Design and Planning, Aalborg University Copenhagen, Denmark SIGNE ALEXANDRA VENDELBO-LARSEN School of Architecture, Design and Planning, Aalborg University Copenhagen, Denmark Case Study—This case study presents ethnographic work in the midst of two fields of technological innovation: automated vehicles (AV) and virtual reality (VR). It showcases the work of three MSc. Techno-Anthropology students and their collaboration with the EU H2020 project ‘interACT’, sharing the goal to develop external human-machine interfaces (e-HMI) for AVs to cooperate with human road users in urban traffic in the future. The authors reflect on their collaboration with human factor researchers, data scientists, engineers, experimental researchers, VR-developers and HMI-designers, and on experienced challenges between the paradigms of qualitative and quantitative...

The Transformative Power of Singular Stories: Making the Case for Qualitative Evidence in Healthcare Contexts in Colombia

JULIANA CARDONA A Piece of Pie JULIANA SALDARRIAGA A Piece of Pie MARIA FERNANDA ESTUPIÑAN A Piece of Pie PAULA GAMBOA A Piece of Pie Case Study—In this case study we describe how we collaborated with a Colombian healthcare provider company and enabled its decision makers to understand the power of stories and other types of qualitative evidence in healthcare contexts. The stories became a tool for recognizing singularities in a complex, massive system, where individuals were constantly reduced to social security numbers. We describe the qualitative methods implemented, such as in-depth interviews, projective techniques, shadowings and observations, explain the difficulty in explaining the value of our qualitative evidence and mention some of the lessons learned throughout the project. We also discuss the project’s outcomes, such as understanding the difference between user perception and user experience, the impotance of healthcare providers to go beyond healthcare and using stories as input for measuring quality of the service....

Empathy Is not Evidence: Four Traps of Commodified Empathy

RACHEL ROBERTSON Shopify PENNY ALLEN Shopify Product teams, including our own, often interpret empathy as evidence. However, in practice, empathy is actually something that drives us to seek evidence. By observing and evaluating various examples within Shopify, we have identified 4 traps that are common in the way empathy is manifested. We modelled the relationship between empathy, problems, evidence, and decisions to provide strategies for how to use empathy effectively while being sympathetic to its limitations. Since empathy drives us to seek evidence, and thus cannot be considered evidence itself, empathy must be used at an appropriate level of abstraction throughout the product decision-making process in order to influence good decisions....

Reading the Tea Leaves: Ethnographic Prediction as Evidence

CLAIRE MAIERS WillowTree, Inc. 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 that are strongly associated with objectivity and untainted by human bias and shortcomings. Recently, data science, big data, algorithms, and machine learning have fueled a new wave of the quantification bias. One of the central fascinations of this wave has been the promise that humans now have the power of prediction at their fingertips. In this paper, I reflect on what it means to make predictions and explore the differences in how predictions are accomplished via quantitative modeling and ethnographic observation. While this is not the first time that ethnographic work has been put in conversation and in contrast with quantified practices, most theorists have framed the role of ethnography as providing context...

Going with the Gut: The Case for Combining Instinct and Data

by SIMON ROBERTS, Stripe Partners "The lesson I took away from that was, while we like to speak with data around here, so many times in my career I've ended up making decisions with my gut, and I should have followed my gut," Otellini said. "My gut told me to say yes." So said the ex-CEO of Intel, ruing his decision to pass on the opportunity to put Intel processors in the first iPhone. It was a decision that would cost Intel the opportunity to power the wildly successful iOS range. His gut, it turns out, was right—but the data didn’t support his instinct. The story most businesses tell to themselves is that they make decisions based on the best available information. It isn’t an exaggeration to suggest that the entire infrastructure of business strategy is configured around the idea, and needs, of the “rational decision maker.” In the technocratic world the quantitative emphasis on what can be counted (empirical data) obscures what does not count (and cannot be counted), namely subjective emotions, intuition and experience. The...