An important rule for business and life is that everything that glistens is not necessarily gold.
This aphorism, believed to have been first quoted by Aesop but made famous in The Merchant of Venice by William Shakespeare, is an important call to look beyond the beauty of a surface to ensure that the substance beneath is as valuable.
This is particularly important when it comes to productivity tools and technologies; countless pieces of office software have been made over the years, but not everything that promises huge increases in productivity has the substance to deliver.
It can take specialists in IT service delivery to ensure you get the right hardware and software for your needs, and a good example of the problems that can lie behind the surface is with the recent issue of “workslop”.
To understand what it is and why 95 per cent of businesses that have adapted artificial intelligence tools into their business workflow are seeing no return, it is important to define the problem and explore potential solutions.
What Is Workslop?
There have been a few terms used to define the same issue, but one of the most recent of these, as described in an article by Harvard Business Review, is “workslop”.
Workslop is a variation on “AI slop”, the epithet used to describe the low-quality results of artificial intelligence tools, large language models and image diffusion models. They tend to be poor quality, uncanny and often filled with basic errors and falsehoods.
However, whilst a lot of AI slop is harmful in relatively abstract ways by spreading and proliferating misinformation at an overwhelming volume to dominate search results and social media feeds, workslop is specifically the use of AI tools to create documents and complete tasks in ways that ostensibly appear correct but have substantial foundational issues.
The key to workslop is that it is the use of an allegedly time-saving tool that costs more time and money as other people have to clarify, clean up and provide the actual substance behind the masquerade.
According to a study led by HBR, every instance of workslop takes two hours on average to fix and can cost a company millions per year in lost productivity.
The reason for this is also the appeal for AI more broadly; to people who cannot tell the difference, the reports look professional and well-worded, whilst the PowerPoint presentations have slick transitions and graphical flourishes, and the code generated looks plausible.
However, to people who understand the field in question, it can take time to reveal that it is utter nonsense, by which point it has already caused damage.
A Bad Tool Or A Tool Used Badly?
All of this has ignited a debate that has existed for as long as the first AI evangelists were claiming that the future of the world will rely on what they describe as “generative AI”.
Microsoft, the makers of Windows, have described a vision of a future version of the operating system and its Office suite (now confusingly called CoPilot) that relies on giving commands to AI agents the same way one would ask an employee, proclaiming the end of the keyboard and mouse.
Given the issues with workslop, a debate has emerged somewhat about whether it is an example of a revolutionary tool being used inappropriately, or a false dawn that, much like the output it generates, appears impressive but lacks substance.
Advocates for the former will note that it took a long time for computers and the internet to be properly implemented into workflows, that the learning curve meant that people would take longer with a new system to complete a task than they would have done, and that the productivity benefits could sometimes be offset by busywork.
On the other hand, the constant mistakes and issues caused by AI tools would typically be considered unacceptable for a human employee, and there appears to be a ceiling for the capabilities of many AI tools with regards to generating written text, images, code or video.
How Can You Ensure Productivity Tools Improve Productivity?
The key to boosting productivity is to accept that there is not going to be a one-size-fits-all solution, and that any IT systems you use will need to appropriately fit not only with other technology but also with employees.
It also means being as critical and astute in your judgement of tools as you are of the people who use them. If a tool keeps causing problems, frequently breaks or seems to be a timesink for productivity, it is important to talk to any technology partners or cease its usage.
As well as this, have a discussion with your teams or a consultation period with larger organisations before implementing a solution that does not work for you.