A troubling new phenomenon known as “workslop” is taking the place of collaborative efforts in work environments, and hurting creativity and productivity in the process. Researchers—including Jeff Hancock, the founding director of the Stanford Social Media Lab—have seen a dramatic rise in low-quality, AI-generated content. This trend has exploded with the release of OpenAI’s ChatGPT in late 2022. This trend has impacted countless organizations and environments, forcing many to reevaluate the role of AI in advanced professional settings.
The genesis for this change for Hancock was through an experience of grading research assignment in 2022. He called the submissions “pretty good, but not hitting the mark.” After a closer inspection, he discovered that 10 of the 100 assignments were disturbingly alike. Along with this alarming trend came a major lack of originality. Such patterns have together inspired a damning diagnosis of the cumulative quality of work produced across both private and public sectors.
It was a challenge that Kate Niederhoffer, vice president of BetterUp’s research labs, encountered when first discussing her research. She was surprised that the first half of a summary of her work showed how the person summarizing didn’t understand her findings. This state of affairs raised some eyebrows when it came to their level of knowledge and engagement with their peers.
In a very recent survey from Hancock and Niederhoffer, 40% of respondents said they had gotten “workslop” in the last month. These results demonstrate that, overall, 15% of content served to workplaces is low-effort. Most of it is just AI-generated junk. The prevalence of this work raises concerns about how it affects perceptions of colleagues and overall team dynamics.
Accepting things as poor or borderline work makes it hard not to start second-guessing what your colleagues are capable of. Recent research shows an alarming pattern. About 50 percent of employees begin viewing their coworkers as less imaginative, competent and trustworthy once they’ve suffered through “workslop. This change in perspective is incredibly powerful, with outsized impacts on how participants work together and relate to one another.
The consequences extend beyond mere perception. Employees facing “workslop” waste nearly two hours per employee every day fixing the mess it creates. Together, that brings the total cost to an average of $186 every month for each impacted worker. For organizations the size of many state DOTs (about 10,000 employees), this has resulted in an annual productivity cost of at least $9 million.
Hancock reminds us that keeping teams to very high standards is the way to reduce “workslop” from becoming the norm. He’s adamant that a team’s dedication to the quality of work is key. It’s made a big dent in the sheer volume of bad practice churned out. He says that without the effort element, it’s just way too easy to churn out a bunch of junk or non impactful content. This change renders content creation less weighty—more filler.
The share of workers using AI on the job has more than tripled since early 2023. Further, Gallup noted that it had made a drastic leap from 21% to 40%. We see the rapid adoption of AI technologies all around us. The reality is that an overwhelming 95% of organizations are unable to identify a measurable ROI. These figures highlight the necessity for responsible adoption of AI technologies into occupational spaces.
As enticing as this all sounds, Niederhoffer cautions that the adoption of AI needs to be handled very carefully. She states that “people forget that because we’re thinking of [AI] as a tool with which we alone work, but it’s actually mediating human-to-human work.” This observation highlights the importance of using AI to augment human competencies rather than allowing it to replace critical thinking and creativity.
Niederhoffer warns that too much and unjudicious use of AI will leave users stuck in a “copy-and-paste mode.” Either way, this attitude breeds an arrogance that causes them to undervalue the power of hard work. If utilized properly, she’s convinced that AI can be an astonishingly helpful resource. She cautions that when used incorrectly, it can destroy cooperation and reduce productivity.
The lack of clarity around AI-generated work has led people to ask if AI created something more often than not. One finance worker noted the dilemma they faced: “It created a situation where I had to decide whether I would rewrite it myself, make him rewrite it, or just call it good enough.” That’s a sign of a growing skepticism about who is creating information and how trustworthy that information is in our own workplaces.
Furthermore, nearly a third of workers say they’ve alerted their colleagues or bosses when they’ve received AI-generated material that doesn’t make sense. The positive side of this trend is that there’s a greater awareness and discomfort with the type and quality of work being passed around to one’s peers. An equal share says they would be less willing to work with colleagues who submit subpar work going forward.
As organizations continue to navigate the evolving landscape of AI integration, the call for accountability and commitment to quality becomes increasingly vital. The reality of “workslop” teaches us the risks of relying too heavily on technology. We need to keep the human expert in the loop at all times to prevent going down these dark paths.