3 ways ‘algorithmic management’ makes work more stressful and less satisfying – Pavilion Demonstration WordPress
Posted by	 August 23, 2021 Leave a comment on 3 ways ‘algorithmic management’ makes work more stressful and less satisfying	
But as appealing as that may sound, you’d be wrong. Our review of 45 studies on machines as managers shows we hate being slaves to algorithms (perhaps even more than we hate being slaves to annoying people).
To get a better sense of what this will mean for the quality of people’s work and well-being, we analysed published research studies from across the world that have investigated the impact of algorithmic management on work.
A great example of the way algorithmic management can reduce task variety and skill use is demonstrated by a 2017 study on the use of electronic monitoring to pay British nurses providing home care to elderly and disabled people.
Research suggests increasing use of algorithms to monitor and manage workers will reduce task variety and skill us. Call centres, for example, already use technology to assess a customers’ mood and instruct the call centre worker on exactly how to respond, from what emotions they should deeply to how fast they should speak.
This loss of general autonomy is underlined by a 2019 study that interviewed 30 gig workers using the “piecework” platforms Amazon Mechanical Turk, MobileWorks and CloudFactory. In theory workers could choose how long they worked. In practice they felt they needed to constantly be on call to secure the best paying tasks.
This isn’t just the experience of gig workers. A detailed 2013 study of the US truck driving industry showed the downside of algorithms dictating what routes drivers should take, and when they should stop, based on weather and traffic conditions. As one driver in the study put it: “A computer does not know when we are tired, fatigued, or anything else […] I am also a professional and I do not need a [computer] telling me when to stop driving.”
For example, in a 2020 study of the experience of 25 food couriers in Edinburgh, the riders spoke about feeling anxious and being “on edge” to accept and complete jobs lest their performance statistics be affected. This led them to take risks such as riding through red lights or through busy traffic in heavy rain. They felt pressure to take all assignments and complete them as quickly as possible so as to be assigned more jobs.
Sharon Kaye Parker receives funding from Australian Research Council.
xavier.parent-rocheleau@hec.ca receives funding from Social Sciences and Humanities Research Council of Canada.