Fired by a robot!
Amazon has been in the news recently for its practice of tracking warehouse workers’ box packing speed and firing them if they do not “make rate.” According to internal Amazon documents, related to a termination at a Baltimore Maryland warehouse location, Amazon’s automated tracking system automatically generates a series of warnings. After 6 warnings in 12 months, a termination is automatically generated if workers fail to meet “efficiency” standards. These termination decisions are made automatically by the system and without input from a real person, though Amazon says that supervisors are able to override the automatically generated terminations.
We have truly reached an age where people and robots are working together and where robots are effectively performing an HR function. HR, unlike a self-checkout or an assembly line robot, is something we normally think of as a soft, people only skill! Robots are branching out! However you may feel about machines in the workforce, we think it’s pretty cool that robots are expanding their skill set. While there are certainly risks to be navigated and considered, there are also undoubtedly gains to be had in terms of efficiency and elimination of bias. Robots do not have teacher’s pets! But should robots be making human resources decisions?
When Your Boss is a Robot
So, effectively, Amazon workers are, to an extent, monitored and managed by these rate tracking robots. The robot supervisors also track the time an employee is “off task” – reportedly causing some employees to skip bathroom breaks. Decisions about productivity rates are made by (human) managers outside of the facility and changed only if more than 75% of the workforce fails to meet the targets. Targets are reviewed quarterly.
Amazon says that a worker can apply to have their termination reviewed by the general manager of their facility or to an appeals panel of their peers. In the Baltimore documents noted above, the terminated worker on one occasion gave the excuse that his “rate” was low because he was ill. He was told by the peer review panel that he should not have come in if his illness was going to slow him down and impact his rate.