Candidate Shortlisting
Using AI to rank or filter job applicants so that a person can decide who goes forward. The site places it at the Recommend rung of the delegation ladder, with a person accountable for the final call.
What it means in practice
The task and decision article compares a password reset with a candidate shortlist. The reset is reversible in seconds and runs on a clear rule. A shortlist is much harder to undo once a candidate has been told no, so it stops at Recommend on the delegation ladder. The EU AI Act and GDPR review adds that using an AI tool to rank applicants puts a business in the high-risk group whichever product it uses.
How we use it
The task and decision article says an audit should scope shortlisting-type steps as Recommend from day one, with a named reviewer built into the process. How we audit is where that sorting happens, and the AI bias page covers why a screening step needs a published criterion for every exclusion.
FAQ
Questions about Candidate Shortlisting
Can AI shortlist job candidates on its own?
The task and decision article says no. It reports AI accuracy of about 75 to 80% on candidate shortlisting against 85 to 90% for experienced humans, useful as a ranking for a person to look at first but not enough to hand the call over. Shortlisting stops at Recommend on the ladder, with a person accountable.
Is filtering CVs against criteria the same as ranking candidates?
No. The HR training article says filtering candidates against published criteria is an arguable use of AI, while ranking them by an opaque score is not. It recommends naming a published criterion for every exclusion, anonymising the data and keeping the final call with a person, not the model.
What it means for a Business
The site's task and decision article reports AI accuracy on shortlisting at about 75 to 80% against 85 to 90% for experienced humans, close enough to support the call but not to replace it. The EU AI Act treats CV filtering and candidate scoring as high-risk, so the site's review advises taking advice before using AI to rank applicants.
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