From Burnout to Balance: AI-Enhanced Work Models for the Future
Nearly half (47%) of workers using AI say they have no idea how to achieve the productivity gains their employers expect. Over three in four (77%) say AI tools have decreased their productivity and added to their workload in at least one way.
I wonder why Upwork, a company that’s all-in on “AI”, didn’t promote this study on their blog like they do their other studies.
As I’ve repeatedly trying to point out, there is a huge cost to promoting “AI” as a magical solution to office work when it’s basic functionality is flawed – if not entirely broken.
Seventy-one percent are burned out and nearly two-thirds (65%) report struggling with increasing employer demands.
And:
Women (74%) report feeling more burned out than do men (68%). Alarmingly, 1 in 3 employees say they will likely quit their jobs in the next six months because they are burned out or overworked.
What’s interesting about this is that the study isn’t trying to measure productivity but instead feelings of productivity.
In these kinds of studies, if they’re done soon after a new tool gets adopted, you find a noticeable positive sentiment: it feels productive because it’s new and you notice new things more.
Usually, once the tool has been integrated and you repeat the study a couple of years down the line (which would be now-ish), you’d get a reversion to the mean: no improvement.
Both of these results are usually completely orthogonal to the actual effect on productivity. You’re just measuring people’s sentiment towards the tool.
The later study usually reverts to the mean because the employee, when asked, is comparing the tool to a competitor, not the before state. As in, at that point when asked about the productivity benefit of cloud-based Word, they’re comparing it to Google Docs, not to the idea of dropping the cloud-based editor entirely.
It’s quite unusual for a study like this on a new office tool, roughly two years after that tool—ChatGPT—exploded into people’s workplaces, to return such a resoundingly negative sentiment.
But it fits with the studies on the actual functionality of said tool: the incredibly common and hard to fix errors, the biases, the general low quality of the output, and the often stated expectation from management that it’s a magic fix for the organisational catastrophe that is the mass layoff fad.
Marketing-funded research of the kind that Upwork does usually prevents these kind of results by finessing the questions.
They simply do not directly ask questions that might have answers they don’t like. That they didn’t this time means they really, really did believe that “AI” is a magic productivity tool and weren’t prepared for even the possibility that it might be harmful.