This report summarizes the successful effort to leverage advances in generative AI, combined with expert human judgment, to populate Work Style ratings for 891 data-level O*NET-SOC occupations. The generative AI methods used occupational information published within the O*NET database as input for generating Work Style ratings for occupations. For each of the 21 Work Styles, an LLM prompt template was developed that allowed for the generation of Work Style ratings that converged well with ratings made by experts in personality and job analysis and ratings made by O*NET occupational analysts.
As the world of work changes, these models can be applied to future versions of the O*NET database to quickly and efficiently generate and maintain high quality Work Style information for the O*NET system.
