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Mapping the Future of Occupations: Transformative and Destructive Effects of New Digital Technologies on Jobs

Fossen, Sorgner

2019Foresight and STI Governance100 citations

Exposure / measurementInterdisciplinary

Automation / RobotsAI (General)Augmentation vs. substitutionRoutine task change

DOI: 10.17323/2500-2597.2019.2.10.18

Abstract

We investigate the impact of new digital technologies upon occupations. We argue that these impacts may be both destructive and transformative. The destructive effects of digitalization substitute human labor, while transformative effects of digitalization complement it. We distinguish between four broad groups of occupations that differ with regard to the impact of digitalization upon them. “Rising star” occupations are characterized by the low destructive and high transformative effects of digitalization. In contrast, “collapsing” occupations face a high risk of destructive effects. “Human terrain” occupations have low risks of both destructive and transformative digitalization, whereas “machine terrain” occupations are affected by both types. We analyze the differences between these four occupational groups in terms of the capabilities, which can be considered bottlenecks to computerization. The results help to identify which capabilities will be in demand and to what degree workers with different abilities can expect their occupations to be transformed in the digital era.

Summary

Fossen and Sorgner develop a two-dimensional framework combining existing automation risk measures (Frey & Osborne 2017) and AI progress measures (Felten et al. 2018) to classify 751 US occupations by their exposure to destructive versus transformative digitization effects, analyzing associated skill requirements using O*Net data.

Main Finding

Approximately 75% of US workers are in occupations experiencing either high transformative effects (37% in 'rising stars' with high AI transformation but low automation risk) or high destructive effects (38% in 'declining' occupations with high automation risk but low transformation), while 25% experience both effects or neither

Primary Datasets

O*NET

Other

Felten et al. (2021)

AI-focused

O*Net occupational database; Frey and Osborne (2017) computerization probabilities; Felten et al. (2018) AI progress measure

Secondary Datasets

None

Key Methods: Descriptive analysis combining two existing AI exposure measures (automation risk and AI progress) to create a two-dimensional occupational classification framework; cross-tabulation of occupational skill requirements by exposure quadrant
Sample Period: 2017-2018
Geographic Coverage: United States
Sample Size: 751 occupations covering approximately 121 million US workers
Level of Analysis: Occupation
Occupation Classification: 6-digit SOC (Standard Occupational Classification)
Industry Classification: None

Notes

Foresight and STI Governance, vol. 13, no. 2, pp. 10-18 [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants. [Claude classification]: Published in Russian journal with English abstract. This is a conceptual/measurement paper that applies and combines two existing exposure measures rather than developing entirely new ones. The main contribution is the two-dimensional framework distinguishing transformative vs destructive digitization effects. Uses weighted medians by employment to classify occupations into four quadrants.