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Journal of Social Computing 2022, 3(3): 191-205 https://doi.org/10.23919/JSC.2022.0013
Open Access | Issue | Published: 30 September 2022

Misalignment Between Skills Discovered, Disseminated, and Deployed in the Knowledge Economy

Show Author's Information Bhargav Srinivasa Desikan1( ),  James Evans2( )
Department of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
Knowledge Lab, the Department of Sociology, University of Chicago, Chicago, IL 60615, USA, and also with the Santa Fe Institute, Santa Fe, NM 87501, USA
Keywords:
natural language processing, computational content analysis, knowledge economy, sociology of knowledge, data science and society
Cite this article:
Desikan BS, Evans J. Misalignment Between Skills Discovered, Disseminated, and Deployed in the Knowledge Economy. Journal of Social Computing, 2022, 3(3): 191-205. https://doi.org/10.23919/JSC.2022.0013
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Abstract Full text About this article

The knowledge economy is a complex and dynamical system, where knowledge and skills are discovered through research, diffused via education, and deployed by industry. Dynamically aligning the supply of new knowledge with the demand for practical skills through education is critical for developing national innovation systems that maximize human flourishing. In this paper, we evaluate the complex alignment of skills across the knowledge economy by creating an integrated semantic model that neurally encodes invented, instructed, and instituted skills across three major datasets: research abstracts from the Web of Science, teaching syllabi from the Open Syllabus Project, and job advertisements from Burning Glass. Analyzing the high dimensional knowledge and skills space inscribed by these data, we draw critical insight about systemic misalignment between the diversity of skills supplied and demanded in the knowledge economy. Consistent with insights from economic geography, demand for skills from industry exhibits high entropy (diversity) at local, regional, and national levels, demonstrating dense complementarities between them at all levels of the economy. Consistent with the economics and sociology of innovation, we find low entropy in the invention of new knowledge and skills through research, as specialist researchers cluster within universities. We provide new evidence, however, for the low entropy of skills taught at local, regional, and national levels, illustrating a massive mismatch between diversity in skills supplied versus demanded. This misalignment is sustained by the spatial and institutional mismatch in the organization of education by researchers at the site of skill invention over use. Our findings suggestively trace the societal costs of tethering education to researchers with narrow knowledge rather than students with broad skill needs.


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About this article

Misalignment Between Skills Discovered, Disseminated, and Deployed in the Knowledge Economy

Show Author's information Bhargav Srinivasa Desikan1( ), James Evans2( )
Department of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
Knowledge Lab, the Department of Sociology, University of Chicago, Chicago, IL 60615, USA, and also with the Santa Fe Institute, Santa Fe, NM 87501, USA

Abstract

The knowledge economy is a complex and dynamical system, where knowledge and skills are discovered through research, diffused via education, and deployed by industry. Dynamically aligning the supply of new knowledge with the demand for practical skills through education is critical for developing national innovation systems that maximize human flourishing. In this paper, we evaluate the complex alignment of skills across the knowledge economy by creating an integrated semantic model that neurally encodes invented, instructed, and instituted skills across three major datasets: research abstracts from the Web of Science, teaching syllabi from the Open Syllabus Project, and job advertisements from Burning Glass. Analyzing the high dimensional knowledge and skills space inscribed by these data, we draw critical insight about systemic misalignment between the diversity of skills supplied and demanded in the knowledge economy. Consistent with insights from economic geography, demand for skills from industry exhibits high entropy (diversity) at local, regional, and national levels, demonstrating dense complementarities between them at all levels of the economy. Consistent with the economics and sociology of innovation, we find low entropy in the invention of new knowledge and skills through research, as specialist researchers cluster within universities. We provide new evidence, however, for the low entropy of skills taught at local, regional, and national levels, illustrating a massive mismatch between diversity in skills supplied versus demanded. This misalignment is sustained by the spatial and institutional mismatch in the organization of education by researchers at the site of skill invention over use. Our findings suggestively trace the societal costs of tethering education to researchers with narrow knowledge rather than students with broad skill needs.

Keywords: natural language processing, computational content analysis, knowledge economy, sociology of knowledge, data science and society

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Received: 19 August 2022
Revised: 19 October 2022
Accepted: 20 October 2022
Published: 30 September 2022
Issue date: September 2022

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