When an employee logs on to Microsoft Office 365 for a workday, data collection begins. Every email she sends on Outlook or call she joins on Teams is a piece of data that can be used to track her productivity for the day. This begs the question; who owns the data? Is it Microsoft who is providing the software? Is it her employer whose network she is under? Or, is it the employee herself who is generating the data as she works?
These are the types of questions that will become increasingly relevant as the world adjusts to working remotely. It is much easier to track an employee’s productivity when the data is being generated automatically through digital platforms. Now that both employers and companies have ownership of this type of data, many ethical issues arise.
“When it comes to data, there are certain things that we don’t want to share with others which is why it’s important to focus on who owns that data,” says Professor Carsten Østerlund. “In the past, data was free to everyone, but now companies have found a way to put a value on it.”
Østerlund identifies this phenomenon as surveillance capitalism, in which private experiences are monetized.. This means that companies turn data collected on individuals into systems that can be sold for profit.
One way that some companies have found a way to put a value on data, according to Østerlund, is by creating dashboards where managers can monitor their employees’ productivity. He recently learned of an example of a dashboard that displayed an employee’s digital productivity by coding their work as “green” for productive or “red” for unproductive.
According to Professor Kevin Crowston, this issue affects blue-collar workers as well. Companies like Amazon use data to track the productivity of their employees in warehouses, and Uber tracks every move of its drivers through the app. These mass amounts of data can be used to improve the quality of work processes for Amazon and Uber, but it also means that the companies own a lot of information about their employees, and have to use it responsibly, which can create problems.
“This practice is very intrusive about how the work is done and ends up creating bad jobs,” said Crowston. For example, Crowston notes that Uber can track when a driver is speeding or going off the route, which they can be punished for or questioned about. This means that the company is using data to micromanage its drivers, often without knowing the reason behind the driver’s actions.
Østerlund adds that these systems may not always represent accurate data when employees learn how to game the system. He cited a recent study from his iSchool colleagues at a nursing home that sought to track how much time employees spent with elderly patrons. Both parties were required to wear tracking devices that monitored how long the two individuals were in close proximity to each other. The researchers found, however, that employees would often leave the tracker on the bed next to the patient and go out for a smoke break, therefore tricking the system into thinking they were spending adequate time together.
The impact of data on the future of work, however, isn’t all bad. Both Østerlund and Crowston cited multiple examples of how data can be used to improve jobs and companies in the future. For example, data monitoring can be used to track processes and adjust in real-time. If crewmembers on a ship can track how much energy they are consuming and how much it costs, they can adjust their usage in real-time to save energy and money.
“At the iSchool, we train people in data science and how they will deal with how data is generated. A lot of this data tracking is going to shape how we do things and organize our work differently,” said Østerlund.
Crowston also added that it’s important to understand that while we cannot just take the data away, we can use it to improve working conditions.
“We shouldn’t focus so much on data privacy itself as we should focus more on how it affects job quality,” he said. “We can use data-driven decision-making around work conditions. Let’s not take the data away, but use it to build a system where different stakeholders have a voice.”