GWU Economist, Tara Sinclair, led the publication of a report recently that showed that in the 12 major economies of the world that constitute the overwhelming bulk of global GDP – including the US, Russia, China, India and Germany – the average measure of unfilled jobs as a percentage of total job openings is about 12.2%.
This is considerably more significant than total unemployment in many of the world’s leading economies.
Of the unfilled jobs, five sectors alone constitute nearly 92% of total absolute openings.
The percentage measure of unfilled jobs in each of these five sectors is indicated below:
1 Computer and Mathematical 83.8%
2 Architecture and Engineering 81.5%
3 Management 76.0%
4 Healthcare Practitioners and Technical 76.0%
5 Business and Financial Operations 59.0%
A careful look at the sectors indicate a strong compatibility with Artificial Intelligence-assisted skills enhancement. That is to say that the melding of new AI-mediated virtual reality capabilities and AI-enabled expert systems shall generate ‘cognitive exoskeletons’ or ‘second brains’ for many workers who would ordinarily not be able to perform to an adequate level on these jobs.
Furthermore, business model pivoting and innovation remains constrained due to the poor compatibility of skills available in the marketplace with the opportunities promised by such structural innovations.
In a world where average skill potential and mid-level employee capabilities can be considerably enhanced by artificial intelligence, businesses shall have a much improved prospect of hiring sound labour at reasonable cost for long-stalled or sub-optimally executed new operations.
For instance, health technicians and nurses equipped with new imaging and diagnostic tools and easy access to smart case analysis shall begin to perform at levels approaching specialist ability. As also shall paralegals and mechanics in engineering domains. Cheap laboratory tests and examinations and legal consultations could become the norm heightening demand for these services and therefore opening new markets with positive labour hiring implications.
The coupling of mid-level AI systems with mid-level human-cognitive capabilities is the much ignored revolution at the cusp of ‘medium-term change horizons’.
Average workers boosted by average AI offer a more fascinating glimpse into the near and mid future than terminator-level or Jarvis-scale machines making all the key mid-level decisions in technical and managerial domains.
Properly so-evaluated, it becomes obvious that some of the policy recommendations premised on the inevitability of a large-scale loss of mid-level jobs due to an exaggerated near-horizon automation risk can be tempered with a more pragmatic vision of the jobs landscape in the next couple of decades.