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Automation doesn't always eliminate jobs. As with bank tellers after ATMs arrived, AI will handle redundant tasks, freeing humans for higher-value work like relationship building. This leads to job transformation and growth, not just obsolescence, for roles with potential for value-add.
Fears that AI will eliminate entry-level jobs are unfounded due to Jevon's paradox. Just as Excel didn't kill accounting jobs but instead enabled more complex financial analysis, AI will augment the work of junior employees, increasing the sophistication and volume of their output rather than replacing them.
The common fear of AI eliminating jobs is misguided. In practice, AI automates specific, often administrative, tasks within a role. This allows human workers to offload minutiae and focus on uniquely human skills like relationship building and strategic thinking, ultimately increasing their leverage and value.
Counterintuitively, making a task cheaper and easier with AI doesn't just eliminate jobs; it drastically increases the overall demand for that task. Just as Excel created more accountants, AI's efficiencies will lead to an explosion in the volume of work, creating new roles and opportunities.
As technology made marketing tasks more efficient (e.g., Google Ads), it democratized access, causing a 5x increase in marketing jobs since the 1970s. Box's CEO argues AI will have a similar effect on all knowledge work by lowering costs, which will dramatically increase overall demand for that work.
AI makes tasks cheaper and faster. This increased efficiency doesn't reduce the need for workers; instead, it increases the demand for their work, as companies can now afford to do more of it. This creates a positive feedback loop that may lead to more hiring, not less.
The introduction of ATMs unexpectedly doubled the number of bank tellers by enabling banks to open more branches. This historical precedent suggests AI will transform roles in unforeseen ways, shifting tasks from basic functions to relationship-oriented work rather than simply eliminating jobs.
Economists see no AI job loss in data because, like cheaper coal in the 1860s, cheaper intelligence via AI doesn't shrink demand. Instead, it explodes it, creating new roles and applications that offset initial displacement.
Contrary to fears of mass job replacement, technology like ATMs historically automated specific tasks (e.g., cash dispensing), freeing workers (bank tellers) to focus on higher-value activities like sales and customer relationships. This often changes jobs rather than destroying them.
Historical data from the computer revolution shows that technology rarely replaces entire professional jobs. Instead, it automates routine tasks within a role, freeing up humans to focus on higher-value activities like analysis, judgment, and coordination, thereby upgrading the job itself.
The Jevons Paradox observes that technologies increasing efficiency often boost consumption rather than reduce it. Applied to AI, this means while some jobs will be automated, the increased productivity will likely expand the scope and volume of work, creating new roles, much like typewriters ultimately increased secretarial work.