Studying and Theorizing Knowledge Work in the Age of Intelligent Machines

Organizing knowledge work and workers has been a long-standing theme in information systems research (Bailey et al. 2010; Brown and Duguid 2000; Dougherty and Dunne 2012; Newell et al. 2009; Orlikowski 2002; Schultze 2000). Maintaining a focus on knowledge work is critical insofar as so-called “intelligent” machines, such as deep learning algorithms, are changing the ways knowledge is created and shared in organizations and epistemic communities more generally (e.g., professions/ occupations) (Faraj et al. 2018). Understanding the consequences of emerging knowledge worker-intelligent machine (KWIM) reconfigurations is of huge practical and theoretical significance (Rai et al. 2019). In this PDW, we are interested in exploring the potential opportunities and challenges for studying and theorizing knowledge work in the age of intelligent machines. We will jointly map the current terrain of knowledge work research; discuss what KWIM reconfigurations IS researchers may need to attend to; explore what alternative theoretical lenses might be useful; and reflect on how to tackle potential methodological challenges in studying KWIM reconfigurations.