Skill-biased technological change complements workers whose knowledge helps them use new tools while substituting for selected routine activities. The technology can increase output without reducing total employment if demand expands or workers shift toward tasks that remain valuable.
Artificial intelligence may favor judgment, context, evaluation and the ability to reorganize work around model capabilities. The distributional effect depends on access, training, adoption and whether productivity gains create new products and demand.
Acronyms and aliases
SBTC acronymskill-biased technology variant
Related terms
Frequently asked questions
How can AI be skill-biased?
It can make workers with strong domain judgment and tool-use skills more productive while automating routine activities performed by other roles.
Does skill-biased change always reduce employment?
No. It changes relative productivity and demand, while total employment also depends on growth, new work, wages and how organizations adopt the technology.
