Jensen Huang uses radiology as an example: AI automated the *task* of reading scans, but this freed up radiologists to focus on their *purpose*: diagnosing disease. This increased productivity and demand, ultimately leading to more jobs, not fewer.
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AI is unlikely to replace fields like radiology because of Jevons Paradox. By making scans cheaper and faster, AI increases the overall demand for scans, which in turn can increase the total number of jobs for human radiologists to manage the higher volume and complex cases.
Contrary to common fears, AI is projected to be a net job creator. Citing a World Economic Forum study, Naveen Chaddha highlights that while 92 million jobs will be displaced by automation, 170 million new roles will emerge, resulting in a net gain of 78 million jobs by 2030.
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.
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.
Contrary to the dominant job-loss narrative, a Vanguard study reveals that occupations highly exposed to AI are experiencing faster growth in both jobs and wages. This suggests AI is currently acting as a productivity tool that increases the value of labor rather than replacing it.
Contrary to fears of mass unemployment, research from the World Economic Forum suggests a net positive impact on jobs from AI. While automation may influence 15% of existing roles, AI is projected to help create 26% new job opportunities, indicating a workforce transformation and skill shift rather than a workforce reduction.
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 narrative of AI destroying jobs misses a key point: AI allows companies to 'hire software for a dollar' for tasks that were never economical to assign to humans. This will unlock new services and expand the economy, creating demand in areas that previously didn't exist.
The initial impact of AI on jobs isn't total replacement. Instead, it automates the most arduous, "long haul" portions of the work, like long-distance truck driving. This frees human workers from the boring parts of their jobs to focus on higher-value, complex "last mile" tasks.
Dan Siroker predicts AI will handle the tedious 50% of knowledge work, not eliminate jobs entirely. This allows humans to focus on tasks that provide purpose, passion, and energy. The goal is augmentation, freeing people from drudgery to focus on high-impact, meaningful work.
