How AI is used to surveil workers

Rebecca Ackermann's article in MIT Technology Review discusses the increasing use of opaque algorithms in workplaces to monitor and control worker productivity, rather than just enhancing efficiency. These algorithms, often implemented without transparency, are used to track remote workers and dictate the pace of work in industries like gig economy and warehouses, sometimes leading to negative consequences such as increased injuries. Ackermann argues that these tools shift power dynamics, reducing workers' control and understanding of their work environment, and highlights the need for transparency and regulation to protect workers' rights.

The article also touches on broader implications, noting that as efficiency gains political traction in the US, the public sector may adopt similar technologies. Labor groups are advocating for more transparency in algorithmic decision-making to counterbalance the power shift. The piece underscores the limited means workers have to understand and challenge these productivity tools, emphasizing the widespread impact and high stakes involved.

Key takeaways:

Opaque algorithms meant to analyze worker productivity are spreading rapidly in workplaces, focusing more on control than efficiency.
Algorithmic decision-making affects not only remote workers but also gig workers and those in industries where people don't work from home.
There is a lack of transparency in how productivity models are built and how decisions are made, with few laws requiring companies to disclose this information.
Labor groups are pushing for more transparency in management algorithms to counteract the shift in power dynamics between workers and employers.

How AI is used to surveil workers

Key takeaways:

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