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Embracing artificial intelligence in the labour market: the case of statistics

Interdisciplinary Studies

Embracing artificial intelligence in the labour market: the case of statistics

J. Liu, K. Chen, et al.

This groundbreaking study by Jin Liu, Kaizhe Chen, and Wenjing Lyu explores the booming integration of statistics and AI in the US labor market between 2010 and 2022, revealing a staggering 31-fold increase in demand for AI-specialized statistical talent across 932 unique roles. The findings highlight significant interdisciplinary trends and provide valuable recommendations for future skill development.

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~3 min • Beginner • English
Abstract
In an era marked by rapid advancements in artificial intelligence (AI), the dynamics of the labour market are undergoing significant transformation. A common concern amidst these changes is the potential obsolescence of traditional disciplines due to AI-driven productivity enhancements. This study delves into the evolving role and resilience of these disciplines within the AI-influenced labour market. Focusing on statistics as a representative field, we investigate its integration with AI and its interplay with other disciplines. Analyzing 279.87 million online job postings in the United States from 2010 to 2022, we observed a remarkable 31-fold increase in the demand for AI-specialized statistical talent, diversifying into 932 distinct AI-related job roles. Additionally, our research identified four major interdisciplinary clusters, encompassing 190 disciplines with a statistical focus. The findings also highlight a growing emphasis on specific hard skills within these AI roles and the differences in demand for AI talent in statistics across economic sectors and regions. Contrary to the pessimistic view of traditional disciplines’ survival in the AI age, our study suggests a more optimistic outlook. We recommend that professionals and organizations proactively adapt to AI advancements. Governments and academic institutions should collaborate to foster interdisciplinary skill development and evaluation for AI talents, thereby enhancing the employability of individuals from traditional disciplines and contributing to broader economic growth.
Publisher
HUMANITIES AND SOCIAL SCIENCES COMMUNICATIONS
Published On
Aug 30, 2024
Authors
Jin Liu, Kaizhe Chen, Wenjing Lyu
Tags
AI specialization
statistics
US labor market
job demand
interdisciplinary skills
online job postings
skill development
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