Author: Jeff Rosenthal
Through previous articles in the LEAD feed that engage the larger literature, we’ve read about various measures of polarization of the labor force and the impact of automation on the labor force.
Recently, the Information Technology & Innovation Foundation produced an interesting analysis on the impact of automation on future work in the United States. Their article points out their concerns with some of the most often-cited recent literature on the impact of automation on work. In response, they created a new risk index based on qualitative analysis with 1=high risk of automation to 5=low risk of automation. They found that 8% of workers were employed in ‘high-risk’ occupations with 33% in ‘moderately high-risk’ occupations, 16% in ‘moderate-risk’ occupations, 28% in ‘moderately low-risk’ occupations and 15% in ‘low-risk’ occupations. They also found that employment in ‘high-risk’ occupations will increase 2% from 2014-2024 while employment in ‘low-risk’ occupations will increase 10%.
We decided to apply their ratings of risk to our statewide long-term occupational projections for 2014-2024.
Not too surprisingly, we found similar distributions for North Carolina1:
- 8% of jobs were in ‘high-risk’ occupations
- 35% in ‘moderately high-risk’ occupations
- 15% in ‘moderate-risk’ occupations
- 30% in ‘moderately low-risk’ occupations
- 13% in ‘low-risk’ occupations.
When we look at the projected changes in sizes of occupational groups, we find that the lower-risk occupations grew more than the higher-risk occupations.
- ‘Low-risk’ occupations showed 14% growth
- ‘Moderately low-risk’ occupations showed 16% growth
- ‘Moderate-risk’ occupations showed 12% growth
- ‘Moderately high-risk’ occupations showed 10% growth
- ‘High-risk’ occupations showed 9% growth.
These findings appear to indicate that the elimination of jobs will not be as far reaching as some analysts such as Frey & Osbourne seem to predict.
There are pluses and minuses to the different studies trying to measure the impact of automation on our future and LEAD does not endorse either as being “better” or more accurate than the other. But, rest assured that we will continue to follow the research and literature, and will help people analyze these trends and their implications for North Carolina jobs. At least until the robots take over.
List of High-Risk Occupations per ITIF
- Automotive and watercraft service attendants
- Switchboard operators, including answering service
- Parking enforcement workers
- Meter readers, utilities
- Word processors and typists
- Cooks, fast food
- Farmworkers and laborers, crop, nursery, and greenhouse
- Graders and sorters, agricultural products
- Tellers
- File clerks
- Dishwashers
- Data entry keyers
- Payroll and timekeeping clerks
- Medical transcriptionists
- Reservation and transportation ticket agents and travel clerks
- Coating, painting, and spraying machine setters, operators, and tenders
- Title examiners, abstractors, and searchers
- Conveyor operators and tenders
- Loading machine operators, underground mining
- Meat, poultry, and fish cutters and trimmers
- Weighers, measurers, checkers, and samplers, recordkeeping
- Court reporters
- Cashiers
- Industrial truck and tractor operators
- Information and record clerks, all other
- Parking lot attendants
- Material moving workers, all other
- Court, municipal, and license clerks
- Couriers and messengers
- Ushers, lobby attendants, and ticket takers
- Communications equipment operators, all other
- Credit analysts
- Baggage porters and bellhops
- Brokerage clerks
- Automotive body and related repairers
- Customer service representatives
- Billing and posting clerks
- Taxi drivers and chauffeursMedical records and health information technicians
1 For our analyses, we utilized only occupations that did not have suppressed data for the 2014 projections. This leaves out 58 occupations with suppressed data.