The terms “blue-collar” and “white-collar” carry a lot of weight, and much of it stems from stereotypes and long-standing perceptions of the importance of different workplace roles.
The white-collar worker is held in greater esteem than their blue-collar counterpart. Despite holding a central role to the functioning of our economy, the latter are rarely recognised as such.
Something both types of work have in common, though, is a shortage of workers and a gap in skills. These challenges go hand in hand.
Over half of organisations (56%) in Scotland are struggling with skills gaps. This is to the detriment of Scotland’s productivity, where we remain behind other parts of the UK and our international competitors.
And this is where artificial intelligence (AI) comes in.
White-collar work might soon see skills gaps filled by AI and automation. This, however, does not apply to sectors like construction, agriculture or healthcare, who rely on overseas workers and are struggling with Brexit and a tougher climate on immigration.
Scotland’s fishing industry, for example, has long relied on migrants and is struggling to find enough fishermen because skilled workers’ visas are now required, which are difficult to obtain with a high English language requirement.
For others, poor pay and working conditions prevent people entering, or remaining in, these jobs. The Royal College of Nursing recently pushed the Scottish Government to assist with increasing the retention of nurses in the healthcare sector with 3,961.8 whole time equivalent posts unfilled at the end of last year.
And in a recent Scottish Government survey, the highest rate of businesses struggling with a worker shortage was in the construction sector (38.3%). In July this industry grew at its fastest pace in over two years, but where will the workers needed to properly accommodate rising orders come from?
What AI could prompt is a recalibration of how society understands the value of blue-collar work, which would simultaneously present a solution to the business community’s recruitment problems.
Unlike technological revolutions of the past, roles with physical or caring components will be the hardest to replace. These positions can be unpredictable and require a high level of human cognition, originality, adaptation and emotion. Even with robotics streamlining operations and curtailing errors, as it stands, these jobs require naturally human qualities.
According to the Pearson Skills Outlook survey, up to 46% of hours spent on some white-collar jobs could be automated with generative AI, which falls to less than one per cent for many blue-collar jobs.
So, the necessity of blue-collar employment won’t change.
These human workers are irreplaceable.
Blue-collar salaries would likely grow to reflect this, and their workplace safety and conditions improve.
An evolution would take place. New, skilled opportunities in the likes of AI oversight or management would arise, offering greater scope for career advancement as roles are elevated and higher skill levels are required to operate advanced technology.
These factors considered, previous white-collar workers would be more inclined to switch paths and reskill, and some blue-collar workers to upskill, with reskilling and upskilling made more efficient through programmes developed by AI.
A proportion of those who may have entered professional services after school would instead opt for skilled blue-collar positions. As a result, apprenticeships would stop being treated as an “afterthought” - a key concern of the National Union of Students Scotland and the National Society of Apprenticeships.
But in the meantime, school leavers need to have options in front of them to pursue pathways suitable for the changing nature of work, and not those encouraged by older depictions of what a career should look like.
If there is a technological solution to Scotland’s skills and worker shortages, the market will find it. AI offers a fix by shifting the dial and rebalancing traditional perceptions of work.
by Sophie Taylor, Associate