Explore a Stanford HAI seminar where postdoctoral fellow Sarah Bana presents her research on using natural language processing to predict salaries from job posting text. Delve into the methodology of creating a model that accurately estimates wage premia for various job characteristics. Learn about the application of NLP techniques to turn job postings into context-dependent vectors, facilitating a modern approach to hedonic regression. Discover insights on the relationship between job posting text and salary predictions, including the significance of specific certifications and skills. Gain understanding of the model's performance, structure, and the implications of text injection experiments. Compare the findings with data from the Current Population Survey and examine the broader implications for understanding labor market dynamics through computational methods.