No abstract

No abstract

Recently Tracy was asked whether a plan to have everyone in the office go about their day with an “impairment” would be a good way to “practice empathy” and learn more about assistive technology usage. Her response was that while wearing prosthetics demonstrates the shock of becoming impaired, it is questionable what it reveals about living a full life with an impairment. “Empathy” is getting around, especially in the worlds of design thinking, start‐ups, and technology. But in these varied contexts, what does empathy really mean? Such questions led us to explore empathy as a method, attribute, and commodity, in turn raising more questions. When we generate and spread “empathy,” are we participating in creating a veneer of care that obscures tensions between consumers and businesses, and ultimately, value extraction? If so, can we improve how we inspire the corporate imagination, and the ends to which that imagination is applied?

EUGENE LIMB IntuitThe analogy between forms of sport and forms of discourse and knowledge should be taken as literally as possible.Peter Sloterdijk, 2013. PLAYING AROUND WITH THE PRACTICE OF THEORYTheories about humans and their relationships with technology are part of a lifeworld shared by many corporate ethnographic practitioners. Practitioners are typically exposed to theory in professional training programs, but may enjoy limited opportunities to deepen engagement with theory once inside corporations. Individual practitioners' approaches to engaging with theory can vary widely due to factors such as discipline, training program, and the workplace norms they have encountered across their careers. Moreover, corporate settings don't always offer teams the time necessary to engage with theory collectively, or at least to do so in what feels like a satisfactory manner. For our team, as for many practitioners in our field, daily work involves researching and contributing to the processes whereby new technologies are designed, developed, and brought to market. Despite the relevance of theories about humans and technologies to this work, opportunities for explicitly engaging with and contributing to theory may not always be recognized by our organizations, or even by ourselves, as integral to daily practice. These challenges help

INTO THE WEEDSAt eleven on a Tuesday night, we found ourselves hunched over computer screens counting boxes. We were back at the hotel after a hectic day on the floor of a huge yearly retail conference. New York was cold, and the walk back from the Javits Center meant navigating walls of commuter buses making their way from the Lincoln Tunnel to the Port Authority.The boxes we were counting were generated by a computer vision system developed by our company. They lay over a panoramic image of retail shelves showcasing an array of toothpaste. Each rectangle indicated an instance of toothpaste having been recognized by the algorithm. Grading the recognitions by hand, checking which recognitions were correct and which weren't, we aimed to understand how well the algorithm was performing and the kinds of problems it was running into. To do this scoring well we had to know the shelf cold, which meant that over time we'd memorized package details, flavors, sizes, and placements. Scoring was grunt work, painstaking and technical, and we were making mistakes, starting over with our chicken scratches more than once.More concerning, scoring was giving us a very warped perspective on the world. We found ourselves getting excited, cheering, when the algorithm recognized a tricky package, and we were obsessing over why certain products were always in the wrong spot on the shelf. Outside of work, products were like minor celebrities for us, providing a little thrill when we spotted them "in the wild."When we were deep in this scoring work, we felt like we were lost in the weeds. We were having a hard time reconciling why we were doing this kind of work, why this work wasn't being handled by people who are more meticulous, more technically minded. In the depths of scoring, particularly on that night in New York, we felt we'd lost our way. Our team didn't believe they needed more research on end users or stakeholders. They needed help on testing algorithms and making pictures of products. This work had to get done, and we were available to do it. So we did.