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Dissecting jobs via automation: Where do we go from here? With Collin Hawkes

Digital AssessmentCandidate Experience
calendarMay 23, 2023

My guest for this episode is Collin Hawkes, Senior Lead I/O Psychologist at Lumen Technologies, an internet services company whose mission is to connect people with technology. Join us today for an interesting conversation that focuses on the use of AI and machine learning to break jobs into a variety of elements, a process also known as “Job Analysis”. We share our experiences in this nascent, but important area and use them as a bridge to other topics that relate to the use of AI in IO psychology.

 

Our discussion begins with the sharing of our mutual admiration for job analysis as both an art and a science. We have both spent countless hours laboring over the tedious aspects of this essential tool of the trade.

 

This crucible has led us both independently to the idea that there must be a better way to tackle the critical but painful minutia while still staying true to the art of the whole thing.

 

Collin notes:

I'd literally go line by line and these tasks and say, okay, what task, this task statement, this specific one task statement, what does this line up to in terms of a competency? And so, I have this Excel sheet with all these tasks in one hearing, and I would go down and I was like, what am I doing this for? Why am I doing this every single time? And so, it sort of created a thought in my mind, well dang, I could train an AI to do the same thing that I'm doing all time and it would probably be better than me at doing it.

 

We then discussed Collin’s pet project, the T stat, which is an automated tool that automatically categorizes task statements which are essentially the “atoms” of a job because they identify each and every task that is required to perform a job. These tasks are then aggregated into higher level factors such as competencies. I then shared my own experience in building an AI based tool that can take transcripts of job analysis interviews that when aggregated can identify the competencies and traits that are most important for a job.

 

Through our discussion of these projects, we find common ground in the use of AI in other areas of our trade, including assessments, video interviews, and job matching tools.

 

The discussion is definitely worth a listen!

 

For anyone interested in learning more about Collin’s app- check out t-stat.com