Associate Professor, Strategy
Marshall School of Business
University of Southern California
My main areas of interest are the economics of innovation and science, creativity and the impact of technology on society. I investigate factors that influence the rate and direction of technological advancements, such as research tools, collaborations and breadth and depth of expertise, and the impact of technological advancements, such as artificial intelligence and quantum computers, on business strategy and productivity.
Could machine learning be a general purpose technology?
A comparison of emerging technologies using data from online job postings
General purpose technologies (GPTs) push out the production possibility frontier and are of strategic importance to managers and policymakers. While theoretical models that explain the characteristics, benefits, and approaches to create and capture value from GPTs have advanced significantly, empirical methods to identify GPTs are lagging. The handful of available attempts are typically context specific and rely on hindsight. For managers deciding on technology strategy, it means that the classification, when available, comes too late. We propose a more universal approach of assessing the GPT likelihood of emerging technologies using data from online job postings. We benchmark our approach against prevailing empirical GPT methods that exploit patent data and provide an application on a set of emerging technologies. Our application exercise suggests that a cluster of technologies comprised of machine learning and related data science technologies is relatively likely to be GPT.