Towards the Terminator Economy: Assessing Job Exposure to AI through LLMs

• URL: http://arxiv.org/abs/2407.19204v1
• Date: Sat, 27 Jul 2024 08:14:18 GMT
• Title: Towards the Terminator Economy: Assessing Job Exposure to AI through LLMs
• Authors: Emilio Colombo, Fabio Mercorio, Mario Mezzanzanica, Antonio Serino,
• Abstract summary: One-third of U.S. employment is highly exposed to AI, primarily in high-skill jobs. This exposure correlates positively with employment and wage growth from 2019 to 2023.
• Score: 10.844598404826355
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The spread and rapid development of AI-related technologies are influencing many aspects of our daily lives, from social to educational, including the labour market. Many researchers have been highlighting the key role AI and technologies play in reshaping jobs and their related tasks, either by automating or enhancing human capabilities in the workplace. Can we estimate if, and to what extent, jobs and related tasks are exposed to the risk of being automatized by state-of-the-art AI-related technologies? Our work tackles this question through a data-driven approach: (i) developing a reproducible framework that exploits a battery of open-source Large Language Models to assess current AI and robotics' capabilities in performing job-related tasks; (ii) formalising and computing an AI exposure measure by occupation, namely the teai (Task Exposure to AI) index. Our results show that about one-third of U.S. employment is highly exposed to AI, primarily in high-skill jobs (aka, white collars). This exposure correlates positively with employment and wage growth from 2019 to 2023, indicating a beneficial impact of AI on productivity. The source codes and results are publicly available, enabling the whole community to benchmark and track AI and technology capabilities over time.

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