  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. Notably, big data and AI
have risen significantly among high wage occupations since 2012 and 2016,
respectively. We built an ARIMA model to predict future occupational task
demands and showcase several relevant examples in Healthcare, Administration,
and IT. Such task demands predictions across occupations will play a pivotal
role in retraining the workforce of the future.
