What blacksmithing and the craftsmen of the past can tell us about the future of entry-level jobs and the workplace.
What blacksmithing and the craftsmen of the past can tell us about the future of entry-level jobs and the workplace.
A rtificial intelligence is taking away entry-level jobs — or, at the very least, limiting them substantially. It isn’t the job apocalypse, but it isn’t the halcyon days, either. AI has changed and will continue to change the job market, and we can’t stop it. We can, however, adapt. Lessons from a blacksmith and a shift from management to mentorship in the workplace can give us clues for how.
AI automates entry-level tasks that workers often consider tedious and mundane. These tasks, while painful for the newbie, are a necessary part of learning the vocabulary, structure, expectations, and even culture of a particular workplace or industry. Then, after you have served your time writing memos and inputting data into spreadsheets, you are able to work your way up into more complex tasks and roles because you were prepared to do so by completing the lower-level tasks. AI threatens to limit or eliminate this preparation.
In a study published in February by the Federal Reserve Bank of Dallas, researcher Scott Davis explains that the impact AI will have on the labor market “will depend on whether the technology automates or augments worker tasks.” In other words, the existence of a job will depend on whether AI replaces or supports the tasks performed by any given worker. According to Davis, the difference between automation and augmentation relies on the distinction between codified knowledge — established information learned from textbooks or the internet — and tacit knowledge — information and understanding gained through experience.
“If AI can replicate codified knowledge, but not tacit knowledge,” Davis writes, “AI will automate jobs requiring codifiable (textbook) knowledge but complement jobs demanding experiential tacit knowledge.” In turn, “AI may substitute for entry-level workers but augment the efforts of experienced workers” by complementing worker expertise but substituting codifiable tasks.
This reality ignores a glaring problem that the workforce will need to address: Without entry-level tasks and jobs, there will be fewer entry-level workers learning the trade of their industry, leaving the succession pipeline dry when it comes time to replace highly trained executives. Industry leaders need workers to succeed them, so what happens when AI replaces apprentices? How can workers learn a job well enough to perfect their tacit knowledge and gain expertise if they don’t first learn the codified knowledge gleaned through entry-level tasks?
To try to answer this question, I spoke with Aaron Strout, a marketing expert and the author of Wired for Purpose. Strout has experienced major technological and employment transformations for 30 years, which has given him what he calls “rational optimism” about AI. He is hopeful but has “guardrails on.” “I use AI literally for almost everything I do, and I love it,” he says. “It is a major, major transformer.”
However, with the introduction of AI in the workplace, Strout identifies what he calls “the apprenticeship problem.” He compares it to farming with seed corn, explaining that “you have these seeds that you use for crops, and if you eat your seed corn because it’s cold that winter, that might sustain you right then, but you’re not going to have anything to plant. And so you might short-term help yourself and [in] the long term, you’re gonna . . . dig yourself a pretty deep hole.”
To address the issue, Strout turns to history. Citing technological disruptions like the Industrial Revolution, electricity, and the PC, he notes that “they did disrupt and they did displace work for the short run but then ultimately ended up creating more jobs down the road, and I think the same thing is going to happen.”
“History,” he explains, “is something that, if we study it, can teach us how to look forward.” With that advice in mind, I sought out and spoke with Will Branson, a modern-day blacksmith.
Blacksmithing is a traditional skills-based craft that relies on tacit knowledge passed down from mentor to apprentice. The active repetition of foundational tasks teaches apprentices the necessary skills and builds intuition, providing the cornerstone for future mastery. Because of blacksmithing’s need for human labor and skill, it is one of the few industries that is almost entirely AI-insulated; however, it has had its fair share of technological disruption. The Industrial Revolution and the mass production of standardized steel and goods rendered traditional blacksmiths almost obsolete, but Will Branson is living proof of the practice’s enduring nature. Based in northern Idaho and owner of Athol Ironworks, he specializes in custom pieces and hand-forged goods and is also the head instructor for a blacksmithing school.
“The Industrial Revolution — that’s kind of what caused some of the waning of blacksmithing. . . . Things were cheaper and faster,” Branson says. But “it wasn’t that it replaced it,” he clarifies. “It just kind of evolved with [it].”
The technological disruptions of the Industrial Revolution were not unlike those of the current age of artificial intelligence, affecting routine and clerical jobs, and they were not without consequences. The number of registered blacksmiths in the United States went from 227,076 in 1904 to between 5,000 and 10,000 today, so it is true that many blacksmith jobs have been replaced; however, those who do that work today have evolved into craftsmen and craftswomen who create projects in which human design, creativity, and personal touch are valued. They found a niche in their industry that machines couldn’t touch.
Blacksmiths also use modern technology today to augment and aid their work. For example, they work with “induction forges,” which use induction coils rather than propane or coal to heat steel, making the process safer, cheaper, and cleaner. “We don’t shy away from technology,” Branson explains. “If you were a blacksmith in 1900 and somebody showed you a welder — a MIG welder — and he would say, ‘Heck, yeah, let me use it,’ because it makes his job easier.”
However, the addition of new technology didn’t mean young blacksmiths were left behind. Branson explains that when he teaches, he uses new technology as “the cherry on top.” “We want to get the nuts and bolts taught first, and that will make you a far better, more rounded blacksmith in the long run. . . . We use that [modern technology] to accentuate and help with the traditional techniques.”
New technology historically automates routine production. So it is with the introduction of AI. The value of human labor shifts from repetitive, codifiable knowledge to adaptation and tacit knowledge. Here, mentorship matters still.
“This apprenticeship problem, [with] these entry-level jobs being taken . . . you don’t really have a logical replacement for that skill set,” explains Strout. The question, he says, is what kinds of apprenticeships and internships colleges and employers can promote in this new technological era.
The answer may lie with the blacksmith and the tradition of apprenticeships. AI will inevitably automate routine cognitive tasks, so the future of work will rely less on the “labor and management” dynamic and more on the “master and apprentice” relationship. It’s something the workplace may have to formalize as part of the AI future. “You do need an adult in the room or someone with the experience to say, ‘Go ahead and run these exercises and . . . run a crisis exercise and tell ChatGPT or Claude what you think you should do,’” says Strout. “Do it ten times and then have someone that’s more senior sit down with you, and they can be the ones that . . . say, ‘Well, this is why that didn’t work or why it wouldn’t work.’”
Furthermore, the introduction of AI could be an opportunity for the workplace to become more human, with a focus on apprenticeship for succession rather than on labor for management. According to the Campaign for Historic Trades, “An apprenticeship has always been more than a job or a training program. Traditionally, it was a long-term relationship built on trust, responsibility, and shared purpose.” To ensure that the succession pipeline for industries like finance, computer programming, and customer service continues to flow, internships need to lean into mentorship, teaching critical thinking and industry context, and providing personal oversight and experiential learning opportunities.
With the addition of AI to augment higher-level jobs, workers will have more time to focus on people, processes, and products without sacrificing efficiency, thereby preserving the industry’s future. Optimization means less time spent with tedium and more time available to teach and mentor. The purpose of “entry-level jobs” must be rethought as a relationship rather than simply an exchange of services. This places the codified knowledge of AI in tandem with tacit knowledge learned through on-site experience, allowing the entry-level employee to learn the necessary skills and knowledge without sacrificing the optimization available with AI.
“Regardless of where you are, older, young, experienced or not, . . . you should absolutely run toward generative AI,” says Strout. “And that doesn’t mean you have to replace everything you do, . . . but start to experiment.”
Some industries will disappear; it is inevitable. However, a prudent workplace will recognize that the future of its open doors will depend on the people it trains to keep holding them open. Jobs will not become easier to find, so it is still in entry-level employees’ best interest to acquire the codified knowledge to set themselves apart. But it is up to each industry to forge a path for future generations to both learn and optimize their respective industries — to place irons in the fire so that when the time comes, they can be molded into tools of the future.