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.

翻译：人工智能相关技术的普及与快速发展正影响着我们日常生活的诸多方面，从社会到教育，乃至劳动力市场。许多研究者已强调人工智能及相关技术在重塑职业及其相关任务中的关键作用——无论是通过自动化还是增强工作场所中的人类能力。我们能否评估职业及相关任务是否（以及在多大程度上）面临被前沿人工智能技术自动化的风险？本研究通过数据驱动的方法探讨该问题：（i）开发一个可复现的框架，利用一系列开源大语言模型评估当前人工智能与机器人在执行职业相关任务方面的能力；（ii）形式化并计算按职业划分的人工智能暴露度量指标，即teai（任务对人工智能暴露）指数。研究结果表明，约三分之一的美国就业岗位高度暴露于人工智能影响之下，主要集中在高技能职业（即白领阶层）。这种暴露与2019年至2023年间的就业及工资增长呈正相关，表明人工智能对生产力产生了积极影响。相关源代码与结果已公开，可供学术界持续对标追踪人工智能与技术能力的发展演进。