Das, Subhro, et al. “Learning Occupational Task-Shares Dynamics for the Future of Work”. AIES 2020 - Proceedings of the AAAI ACM Conference on AI, Ethics, and Society, 2020, pp. 36–42, doi:10.1145/3375627.3375826.
Abstract
The recent wave of AI and automation has been argued to differ from previous General Purpose Technologies (GPTs), in that it may lead to rapid change in occupations' underlying task requirements and persistent technological unemployment. In this paper, we apply a novel methodology of dynamic task shares to a large dataset of online job postings to explore how exactly occupational task demands have changed over the past decade of AI innovation, especially across high, mid and low wage occupations.
Year of Publication
2020
Conference Name
AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society
ISBN Number
9781450371100
DOI
10.1145/3375627.3375826