Knowledge workers have a new overlord: artificial intelligence (AI). Until recently white-collar employees have been evaluated by the quality of their ideas rather than the quantity produced. But now AI programs claim to keep tabs on how they do their jobs and when they are wasting time.
Most employees assume that their employer is probably checking which websites they visit and retaining email logs (as possible evidence in any future disciplinary action or client dispute). Calls are also widely ‘recorded or monitored for quality assurance purposes'. However, new software packages can now:
- Take photos every three to 10 minutes via the desktop’s webcam
- Take screenshots of workstations
- Track app use
- Log or count keystrokes
- Detect keywords such as ‘football’, ‘shopping’ or ‘CV’
- Judge whether email content is gossip- or work-related
- Use calendar apps to track billable hours
- Generate productivity, focus or intensity scores for employees
- Provide a dashboard to compare employee productivity scores and assess engagement levels.
Moreover, these programs can be hidden in running processes. With the EU’s General Data Protection Regulation (GDPR) employees and consumers are supposed to have access to data about them. Staff may opt out, though doing so isn’t always easy in an unequal employer-employee relationship.
A pilot programme in the Netherlands using personal fitness trackers and calendar monitoring initially received wide buy-in from employees. The idea was to correlate time spent with new clients, their profitability, and signs of stress. But people became increasingly aware of privacy issues and started to leave the project.
Similarly, employees who are expected to work late or on weekends at home have not taken to the idea of being tracked around the clock by their company smartphone. There is a productivity bargain to be struck. "Employees are now expecting to be able to gain some time back in return for the time they spend working at home," says Paul Thompson, professor of employment studies at the University of Stirling.
But productivity is a thorny issue. "In electronic monitoring what is monitored is typically behaviours that are easily monitored, not necessarily what should be monitored. They often give supervisors answers to the 'what' question – what is the employee doing – while ignoring the 'why' and 'how' questions," says Bradley Alge, associate professor of management at Purdue University Indiana.
For example, customer service agents tend to be monitored and graded on efficiency not effectiveness. "Taken to the extreme, customer service agents might be rewarded based on production quantity (how many calls were taken in an hour) versus production quality (what was the quality of the call, was the customer satisfied)," Alge says. "Customer service could actually go down because of monitoring and incentivising the wrong things."
As Phoebe Moore, author of The Quantified Self in Precarity: Work, Technology and What Counts, notes: "a lot of the preparatory labour that contributes to productivity is intentionally overlooked". This, she says, might be addressed "if you are allowed to tailor your own subjective productivity; to how much time I spend away from the monitor. It raises major questions about what productivity and performance really is".
The idea that such questions can be turned over to impartial AI algorithms is false. "Bias comes in because of the data you decide to collect," Moore says, and the fact that staff may not be able to understand how it works. "It is a brave new world of the employment relationship."
So how should companies and staff ensure best practice? Acas recommends the following:
Write it down. Create written policies and procedures about workplace monitoring.
Don’t go overboard. Be able to justify the monitoring.
Communicate. Tell employees what information will be gathered and how long it will be kept.
Understand the law. In particular stay on the right side of the Data Protection Act.
Security. Keep the collected data secure.
Catherine Mazy is a freelance business writer for Financial Times | IE Business School Corporate Learning Alliance and former editor at The Wall Street Journal
