In our track, we aim to connect scholars working on ethnographic studies of organizing in the age of datafication. Submit your abstract before December 21, 2018.
Developments in digital data technologies such as analytics, machine learning and artificial intelligence have allowed for high impact changes in social and organizational life, and work in particular. Digital data technologies are widely taken up by organizations to improve decision-making, efficiency and performance.
However, the use of these technologies is also associated with unforeseen and profound shifts in work practices that go beyond mere performance improvements. For example, over-reliance on the algorithms may eventually lead to losing crucial tacit knowledge necessary for professional decision-making (Pachidi et al. 2016), trigger status struggles between professional groups (Anthony 2018) or occasion power tensions in institutional fields, such as travel industry (Orlikowski and Scott 2013). Even though an emerging stream starts speculating on such controversial consequences of datification (e.g. Faraj et al. 2018; Elish and boyd 2018), there is still a need for in-depth studies that unpack what the use of algorithms and data-driven work constitutes in practice.
This track aims to bring together field studies of situated use of data and AI and its consequences for work. We specifically invite scholars conducting ethnographic research on organizing with algorithms and interested in theorizing unintended and unforeseen consequences of datification for people in the workplace.