Project Overview
In response to the rising concerns surrounding the impact of Large Language Models (LLMs) and artificial intelligence on employment, this capstone project, titled "Assessing Job Vulnerability and Employment Growth in the Era of Large Language Models," aims to conduct a comprehensive analysis, particularly focusing on white-collar occupations. The rapid evolution of technology, coupled with the potential for automation, necessitates an in-depth exploration of job vulnerability to empower affected workers and inform key stakeholders.
The scope of the project is focused specifically on white-collar jobs and their susceptibility to automation. White-collar jobs typically involve professional, managerial, administrative, or clerical tasks, often requiring higher levels of education, cognitive skills, and specialized knowledge. Examples of white-collar occupations include accountants, lawyers, software developers, managers, and administrative assistants.
While acknowledging that automation also impacts blue-collar jobs (typically involving manual labor and skilled trades), the project's primary focus remains on white-collar occupations. However, users will have the opportunity to explore blue-collar jobs that are also susceptible to automation. This option allows users to gain insights into both white-collar and blue-collar job automation risks, while keeping the core analysis and findings centered on white-collar occupations.
What White-collar jobs are more likely to be replaced by LLMs?
| Occupation | Probability | Risk of Automation |
|---|