But as appealing as that may sound, youd be wrong.
Amazon has been another enthusiastic adopter, using software and surveillance to direct human workers in its massive warehouses.
It’s free, every week, in your inbox.
Just four of the 45 studies showed mixed effects on work (some positive and some negative).
The rest highlighted consistently negative effects on workers.
In this article were going to look at three main impacts:
1.
The system under which the nurses worked was meant to improve their efficiency.
They had to use an app to tag their care activities.
They were paid only for the tasks that could be tagged.
Nothing else was recognized.
This reduced both the quality of care as well as the nurses sense of doing significant and worthwhile work.
Researchsuggestsincreasing use of algorithms to monitor and manage workers will reduce task variety and skill.
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 isnt just the experience of gig workers.
Increased intensity and insecurity
Algorithmic management can heighten work intensity in a number of ways.
It can dictate the pace directly, as with Amazons use of timers for pickers in its fulfillment centers.
But perhaps more pernicious is its ability to ramp up the work pressure indirectly.
Workers who dont really understand how an algorithm makes its decisions feel more uncertain and insecure about their performance.
They worry about every aspect of affecting how the machine rates and ranks them.
This led them to take risks such as riding through red lights or through busy traffic in heavy rain.
Currently, the design and use of algorithmic management systems are driven by efficiency for the employer.
A more considered approach is needed to ensure these systems can coexist with dignified, meaningful work.
