Week 7: Analyzing AI Exposure by Occupation and Industry
Welcome back to Week 7 of my senior project! This week, I’ve been analyzing the relationship between occupation type (white/blue collar) and industry using linear regression.
Regression Results
You can find the full regression results here.
AI Exposure and Occupation Type
For this analysis, the “whiteCollar” variable is defined as:
- 1 for white-collar workers
- 0 for blue-collar workers
Key takeaways:
- The positive coefficient for white-collar suggests that they are more exposed to AI than blue-collar workers
- This finding aligns with previous studies on AI’s impact across different job types
AI Exposure and Industry
The below list of industries ranks industries by their exposure to AI, from most to least exposed.
- Professional Services & Administrative Support (e.g., Marketing, Accounting, Bookkeeping, Clerical, Consulting, Administrative Support)
- Media and Communications
- Finance, Management, & Real Estate
- Education & Public Services
- Healthcare & Life Sciences
- Information Technology
- Arts, Entertainment & Hospitality
- Science, Engineering, & Technical Services
- Construction and Repair
- Transportation & Logistics
- Agriculture, Natural Resources & Mining
- Wholesale, Retail, and Manufacturing
What’s Next?
Next week, I’ll explore the interaction between race and occupation type while also beginning my study of multicollinearity. I’ll conduct a Variance Inflation Factor (VIF) analysis to refine my regression models.
Thanks for following along, and feel free to share any questions or thoughts in the comments below!
Comments:
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