For Work / Against Work
Debates on the centrality of work

"Automation, algorithms, and beyond: Why work design matters more than ever in a digital world"

by Parker, Sharon K; Grote, Gudela (2020)


We propose a central role for work design in understanding the effects of digital technologies. We give examples of how new technologies can?depending on various factors?positively and negatively affect job resources (autonomy/control, skill use, job feedback, relational aspects) and job demands (e.g., performance monitoring), with consequences for employee well-being, safety, and performance. We identify four intervention strategies. First, work design choices need to be proactively considered during technology implementation, consistent with the sociotechnical systems principle of joint optimization. Second, human-centred design principles should be explicitly considered in the design and procurement of new technologies. Third, organizationally oriented intervention strategies need to be supported by macro-level policies. Fourth, there is a need to go beyond a focus on upskilling employees to help them adapt to technology change, to also focus on training employees, as well as other stakeholders, in work design and related topics. Finally, we identify directions for moving the field forward, including new research questions (e.g., job autonomy in the context of machine learning; understanding designers? work design mindsets; investigating how job crafting applies to technology); a reorientation of methods (e.g., interdisciplinary, intervention studies); and steps for achieving practical impact.

Key Passage

On the other hand, new technologies and their associated work practices can undermine or interfere with human autonomy. We consider this issue in relation to automation, where most research has been done. The early focus of technology designers and implementers was to automate as much as possible, giving humans only the “left over” monitoring tasks that could not be performed by the technology. However, as Bainbridge (1983) noted in an article on the “ironies of automation”, this assumes that designers get everything correct (they don’t) and also that, by automating the complex tasks, only the “simple” ones are left. But in fact, “by taking away the easy parts of his task, automation can make the difficult parts of the human operator’s task more difficult”. In essence, humans are turned into supervisory controllers” (Sheridan, 1987) of systems they are no longer able to fully understand, impeding adequate intervention when these systems fail. In what has been referred to as the “out of the loop” performance problem Billings, 1991), operators of automated machines, compared to manual operators, become increasingly unable to detect system errors and perform manual tasks in the face of automation failures due to the loss of manual skills and loss of situational awareness of the system. (p.10)


Automation, Algoriths, Work Design, Digitial, Artificial Intelligencce, Technology, Autonomy



Links to Reference



How to contribute.