Age is a protected class, and it's extremely difficult to sanitise age from a resume.
Let's say the candidate got a BS in EECS in 1987, they've had 6 jobs since graduating, and their first job was cost-optimising floppy disk drives.
Do you feed the ML system this data, which is clearly correlated with age? Do you keep the number of jobs but delete the duration, responding to 6-jobs-in-3-years the same as 6-jobs-in-30-years? How do you sanitise the age-correlated data out of job descriptions naming old tech or defunct employers? Do you delete all but the last 5 years of their employment history, assigning no value to experience beyond that?
Let's say the candidate got a BS in EECS in 1987, they've had 6 jobs since graduating, and their first job was cost-optimising floppy disk drives.
Do you feed the ML system this data, which is clearly correlated with age? Do you keep the number of jobs but delete the duration, responding to 6-jobs-in-3-years the same as 6-jobs-in-30-years? How do you sanitise the age-correlated data out of job descriptions naming old tech or defunct employers? Do you delete all but the last 5 years of their employment history, assigning no value to experience beyond that?