論文アブストラクト： We are in a transitional economic period emphasizing automation of physical jobs and the shift towards intellectual labor. How can we measure and understand human behaviors of job search, and how communities are adapting to these changes? We use internet search data to estimate employment demand in the United States. Starting with 225 million raw job search queries in 2015 and 2016 from a popular search engine, we classify queries into one of 15 fields of employment with accuracy and F-1 of 97%, and use the resulting query volumes to estimate per-sector employment demand in U.S. counties. We validate against Bureau of Labor Statistics measures, and then demonstrate benefits for communities, showing significant differences in the types of jobs searched for across socio-economic dimensions like poverty and education level. We discuss implications for macroeconomic measurement, as well as how community leaders, policy makers, and the field of HCI can benefit.
論文アブストラクト： Effective communication of activities and progress in the workplace is crucial for the success of many modern organizations. In this paper, we extend current research on workplace communication and uncover opportunities for technology to support effective work activity reporting. We report on three studies: With a survey of 68 knowledge workers followed by 14 in-depth interviews, we investigated the perceived benefits of different types of progress reports and an array of challenges at three stages: Collection, Composition, and Delivery. We show an important interplay between written and face-to-face reporting, and highlight the importance of tailoring a report to its audience. We then present results from an analysis of 722 reports composed by 361 U.S.-based knowledge workers, looking at the influence of the audience on a report's language. We conclude by discussing opportunities for future technologies to assist both employees and managers in collecting, interpreting, and reporting progress in the workplace.
論文アブストラクト： This paper examines how mobile technology impacts employee accountability in the blue-collar data-driven workplace. We conducted an observation-based qualitative study of how electricians in an electrical company interact with data related to their work accountability, which comprises the information employees feel is reasonable to share and document about their work. The electricians we studied capture data both manually, recording the hours spent on a particular task, and automatically, as their mobile devices regularly track data such as location. First, our results demonstrate how work accountability manifests for employees' manual labor work that has become data-driven. We show how employees work through moments of transparency, privacy, and accountability using data focused on location, identification and time. Second, we demonstrate how this data production is interdependent with employees' beliefs about what is a reasonable level of detail and transparency to provide about their work. Lastly, we articulate specific design implications related to work accountability.
論文アブストラクト： Application-centric computing dominates human-computer interactions, yet the concept of an application is ambiguous and the impact of its ubiquity underexplored. We unpack "the application" through the lens of non-standard knowledge work: freelance, self-employed, and fixed-term contract workers who create knowledge in collaboration with a wide variety of stakeholders on a per-project basis. Based on interviews with fourteen participants we describe how: i) their economic value is intertwined with data and skills related to specific applications; ii) their access to this value is systematically jeopardised in collaboration due to the different application practices, preferences, and proficiencies of other stakeholders; and iii) they mitigate the costs of this compromise through cross-application collaboration strategies. We trace these experiences to common characteristics of applications, such as update processes, interface symmetries, application-document relationships, and operating system and hardware dependencies. By empirically and analytically focusing on "the application", we reveal the implications of the current application-centric computing paradigm and discuss how variations within this model create qualitatively different human-computer interactions.