If you don’t use it, you will lose it. Automate what was once a skill-developed process and those skills will decline.
“Cognitive automation powered by advanced intelligent technologies is increasingly enabling organizations to automate more of their knowledge work tasks. Although this often offers higher efficiency and lower costs, cognitive automation exacerbates the erosion of human skill and expertise in automated tasks. Accepting the erosion of obsolete skills is necessary to reap the benefits of technology—however, the erosion of essential human expertise is problematic if workers remain accountable for tasks for which they lack sufficient understanding, rendering them incapable of responding if the automation fails.” —The Vicious Circles of Skill Erosion (2023)
One key factor in understanding how we learn and develop skills is that experience cannot be automated. Increasing automation requires that the Learning and Development (L&D) field must get out of the comfort zone of course development and into the most complex aspects of human learning and performance. To understand learning at work, L&D must understand the work systems. Now they also have to understand skill erosion.
Addressing skill erosion will be a great challenge because the entire capitalist economy seeks continuous automation in order to feed the ‘constant growth’ economic machine. “Thanks to accounting conventions and tax laws dating back centuries, a robot doesn’t need to be better – or more efficient – than a human being at a task to make a business more profitable. It just needs to be 34% as good, or 11% as good, depending on that business’s accounting and amortization policies.” —John Carolus Sharp
As more of our work systems become automated, there is less need for vigilant human oversight. But take the case of commercial aviation. Most aircraft fly most of the time on autopilot. What does this do to pilot concentration and skill erosion? Understanding these complex relations — between skilled humans and very complicated machines & software — requires systems thinking and a better approach to training.
Dave Cormier, author of Learning in a Time of Abundance, warned that learning basic skills will become auto-tuned from the likes of GPT, LLM, etc.
“The real danger is not to people who are experts in their fields. Super experts in every field will continue to do what they have always done. All of us, however, are novices in almost everything we do. Most of us will never be experts in anything. The vast majority of the human experience of learning about something is done at the novice level.
That experience is about to be autotuned.”
—ChatGPT search – Autotune for knowledge
For the past two decades I have promoted manual sensemaking. It is the basis of my personal knowledge mastery (PKM) framework. Sensemaking is a manual skill, which can be assisted with various tools, but the most important tool is our mind, using good practices, and learning with and from others.
Helen Blunden observed several years ago that PKM is a foundation for sensemaking in the modern, connected workplace. “The more I am out there chatting to clients, the more I realise that your PKM approach is the number one critical skill set. Any way I look at it, all roads seem to end there. It is the foundation. That’s why I thought this is where they need to start – and not just the employees – everyone including the managers.”
As the authors of The Vicious Circles of Skill Erosion, observe — burdensome tasks can be aided by automation systems but reliance on these can lead to individual complacency and organizational skill erosion.
“Therefore, a chain of causal links exists where automation reliance increases organizational performance, which in turn gives rise to complacency at the organizational level. The organizational complacency decreases the enforcement of skill maintenance mechanisms, which finally reduces individual workers’ mindful conduction. We refer to this vicious circle as the organizational skill-erosion loop (R2), a reinforcing loop fueled by organizational complacency.” — p. 1393 Journal of the Association for Information Systems, Vol 24 (2023)
Manual skills are human skills.
