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Surveillance Tech At Work On The Rise

A new report ‘Data and Algorithms At Work’ from the US shows what is in store, when it comes to workers’ surveillance. Examples are hiring software that generates scores of job applicants based on their tone of voice and word choices, algorithms used to predict whether workers will quit or become pregnant or try to organize a union, and software monitoring workers and calculating metrics on their speed.

The goal of the report is to give policymakers and other stakeholders an understanding of trends in the data-driven workplace and a framework of the technology rights that workers need and deserve. The US is usually ahead of Europe, when it comes to deploying new tech, and despite the fact that Europe is generally more unionized, a lot of this is also going on in Europe and unions and policymakers should discuss the red lines here.

Dehumanisation and automation are not the only path. With strong worker protections in place, new technology can be put in the service of creating a vibrant and productive economy built on living wage jobs, safe workplaces, and race and gender equity, says the report who focuses on the negative impact of use of data and surveillance:

Worker Data Dollection
“Employers can collect an extensive array of data about workers. Some of it is gathered in the workplace, such as computer activity, location in the building, customer ratings, bathroom use, coworker interactions, and smartphone app interactions. Other data is bought from third parties, like social media activity, credit reports, driving history, and consumer activity. Some of this data, such as criminal background checks, has been collected by employers for decades. More recently, as new wearable sensors have become available, employers have partnered with technology vendors and wellness programs to collect more personal biometric and health and wellness data. Methods of data collection range from directly soliciting data from workers (and customers) through surveys or data mining the internet, to microphones embedded in worker badges. Employers may collect worker data themselves, but they may also contract with third-party firms to do so; an entire ecosystem is emerging of businesses engaged in collecting, processing, and selling worker data,” according to the report.

Electronic Monitoring
“Here we see passive data collection technologies such as sensors embedded in workplace equipment, devices, and wearables that can capture a wide range of data on worker location, activities, and interactions with coworkers. Likewise, systems that log keystrokes and capture screenshots enable employers to monitor computer and internet activity. Employers also use GPS technologies embedded in vehicles or in workers’ personal smartphones to monitor their presence on job sites and track their locations while out in the field.”

According to the report, algorithms transform input data into technological outputs, which can take the form of everything from promotion recommendations and instructions for delivery drivers, to chatbots and semi-autonomous service robots that complete job tasks.

With clients can view worker profiles to find and select service providers. Worker profiles display performance metrics based on data compiled by the platform, such as customer request response times and customer ratings (which have the potential to perpetuate discrimination against people of color and immigrants in hiring and wage offers).These ratings have a significant impact on which workers will be featured in customers’ searches, and therefore on their likelihood of finding work. From the report.

How to Use the Data
• Human resource analytics, such as hiring, performance evaluation, and on-the-job training.
• Algorithmic management, such as workforce scheduling, coordination, and direction of worker activities.
• Task automation, where some or even all tasks making up a job are automated using data-driven technologies.

The company Presto has developed a computer vision system that analyzes video data streams to automatically classify objects and human activities (and therefore flag, for example, long wait times for food or untidy waiting areas). The system uses this analysis to generate scores of likely customer experience. Based on these scores, the system can send real-time notifications to staff so that they can address issues immediately, as well as individual performance reports to managers. From the report.

How It Can Harm Workers
Harms can take the form of work intensification and speed-up; deskilling and automation; hazardous working conditions; growth in contingent work; loss of autonomy and privacy; discrimination; and suppression of the right to organize. Of particular concern is that workers of color, women, and immigrants can face direct discrimination via systemic biases embedded in these technologies, and are also most likely to work in occupations at the
front lines of experimentation with artificial intelligence.

Get the report here