There’s a common belief that AI will free workers from monotonous or low-level tasks, freeing up time for more creative or stimulating work. But it might not be so simple.
Milena Nikolova, a professor in the economics of well-being at the University of Groningen, has looked at data on thousands of workers across 20 European countries over two decades. Surprisingly, she found that automation in industrial workplaces actually increased repetitive and monotonous tasks for humans. Human work became more routine, not less.
Nikolova’s research found that robotisation made work more intense, focusing on a dwindling set of tasks that machines could not easily accomplish. These tasks were also less interesting, with fewer opportunities for cognitively challenging work and human contact.
Workers also became more reliant on a machine’s pace of work and had a more limited understanding of the full production process. The overall result was a decline in meaningful work and autonomy.
I am worried about the content and quality of the jobs that are created with new technologies and the tasks left over for humans
Think of a warehouse operator in a semi-automated depot: the worker still needs to be present while the robot functions. The employee depends on the machine’s output and activities, while the human work is more routine-intensive, less challenging and less interactive. There’s no time for better work.
This research focused on low-skilled work: we know now that AI is taking over more cognitively challenging and creative tasks that only humans could previously perform, whether it be customer service or content creation.
“‘I’m not worried that people won’t have stuff to do. What I am worried about is the actual content and quality of the jobs that are created with new technologies and the tasks left over for humans,” explains Nikolova.
“Will, say, automation and AI create so-called “bullshit” or meaningless jobs? This new wave of automation, including AI, is very different. It has the potential to affect highly skilled, highly educated and highly paid knowledge workers. This is something we’ve not seen before,” she explains.
The challenge to meaningful work
Don’t expect entire occupations to be automated with new AI-powered solutions. Instead, more structured tasks will be taken on by machines or jobs will be restructured so they can accommodate AI.
How AI is adopted in the workplace therefore matters. We need to consider the types of tasks it takes over, whether it is human-centric in design and whether it promotes meaningful work.
According to the International Monetary Fund, AI will affect 60% of jobs in advanced economies and half of these exposed jobs could be negatively impacted. The stakes are high: the market for AI is set to reach $184bn in 2024. Expect more firms to leverage AI in workplaces across the globe.
“Certainly AI poses a range of challenges to meaningful work,” says Katie Bailey, professor of work and employment at King’s College London. “There is the risk that jobs become broken up and disjointed due to AI, or that humans simply end up ‘tending the machine’.”
It’s not all negative, of course; AI has incredible potential. But understanding the technology’s mission creep on the tasks and workplace values that humans hold dear is essential. For instance, AI can increase the intensity of work and put pressure on “humans in the loop” as they try to keep pace with algorithms.
There are other workplace risks. AI-powered digital systems can impinge on worker autonomy, embed employee surveillance, erode employee competencies without adequate retraining and degrade employee socialisation and human interactions.
Public and private organisations need an open and honest dialogue on how new tech tools impact employment and whether it promotes or hinders meaningful work. The adoption of AI-powered work platforms is rarely voted on by employees. At the same time, very few businesses have a framework for what dignity at work looks like with respect to AI or capture objective data on these topics.
Time for experimentation
Carl Benedikt Frey is associate professor of AI and work at the University of Oxford. He says there are lessons to be learnt from past industrial revolutions on how this new digital evolution, driven by AI, will affect meaningful work today.
Initially, in the early 1800s, the automation of human tasks in factory settings such as mills and foundries didn’t lead to huge strides in productivity growth, which only came later, after a period known as “Engels’ Pause”. Instead, it led to human replacement, unrest and a hollowing out of the labour market. It was only when old industries were reconfigured and new ones were born that meaningful work fully evolved – such as the creation of the automobile or aviation sectors.
Just like in past revolutions, it takes years to get beyond plain automation. A recalibration of industry requires human experimentation and ingenuity, which demands time and space. “Right now we’re very much in the automation stage of AI,” says Frey. “It’s about increasing efficiency with respect to the tasks we’re already doing in the workplace. What we should be asking ourselves is ‘what is it that we can now do with this technology that we previously couldn’t do?’”
When it comes to meaningful work and AI we need to move from a system focused on production, measuring how long it takes a worker to complete a task or how many clicks generates a particular output. Instead, “we need to take a more holistic approach and allow people to experiment,” Frey says.
This is the opportunity: if human workers are given more autonomy and more thinking time with this new tech they could shift the dial on all sorts of industrial, economic, social and environmental issues, driving new waves of creativity and workplace happiness. If AI is used primarily to replace tasks, boost efficiencies and generally feed the machine, we are unlikely to see either huge leaps in productivity or more meaningful work.
