By: Dr. Josh Duplantis
Dean of Workforce Development
Coastal Alabama Community College
It was about 10 years ago, and I was asked by a group to do a keynote presentation on disruptive innovation at the College of Osteopathic Medicine in Dothan. Yes, I know, I work for the government and government and disruptive innovation don’t usually go in the same sentence.
I remember coming to a close and asking an audience of about 150 people if they had any questions. After answering a few about data, one gentleman who worked in agriculture seemed pretty frustrated when he asked if he was to just sit back while the robots come to take all of our jobs. Honestly, I forgot my response at the time. It was clear that he wasn’t a fan of what I’m sure he considered a young PhD whippersnapper.
Fast forward 10 years and you see a completely different labor market. Completely different. We are now asking how we can get more robots to fill jobs that people just aren’t there for or not willing to do.
Enter the Automation Index. Automation index captures an occupation’s risk of being affected by automation. I use Lightcast US Automation Index which analyzed the potential automation risk of occupations based on job task content – derived straight from ONET work activities. Their formula combines that data with the Frey and Osborne findings at the occupation level and identifies which job task are “at risk” and which are resilient. The metric uses four measures:
% of time spent on high-risk work
% of time spent on low-risk work
Number of high-risk jobs in compatible occupations
Overall industry automation risk
The output of this formula is presented as a scale with a base of 100. An automation index greater than 100 indicates a higher-than-average risk of automation; an automation index less than 100 indicates a lower-than-average risk of automation.
The fascinating change that I’ve seen is a shift from production occupations pre-pandemic to now construction helper and food and beverage workers leading the way on Alabama Region 07’s automation index.
Below are the top 10 (3-digit) occupations with the highest automation index scores in Southwest Alabama.
Occupational AutomationSOCDescription2022 Turnover Rate Automation Index
47-3000 Helpers, Construction Trades 126% 134.5
35-3000 Food and Beverage Serving Workers 188% 129.0
37-3000 Grounds Maintenance Workers 70% 128.6
35-9000 Other Food Prep and Service-Related Workers 183% 128.1
35-2000 Cooks and Food Prep Worker 141% 126.0
(Lightcast Q32023 Data Set)
I think about that old farmer getting pretty upset with me 10 years ago. I wonder if his opinion has changed.