Automated employment decision tool
Also called AEDT
A computational process that substantially assists or replaces discretionary decision-making in hiring or promotion, typically by scoring, ranking or filtering candidates.
Last reviewed
In practice
The term comes from New York City’s Local Law 144, which requires employers using such a tool for candidates in the city to have it independently bias-audited within the preceding year, publish a summary of the results, and notify candidates that it is in use.
The boundary is genuinely contested. A tool that produces a score a human then acts on may or may not be "substantially assisting" depending on how much the score drives the outcome. Employers who spend their energy arguing the boundary tend to end up on the wrong side of it.
The practical response is to build for the requirement rather than litigate the definition: tell candidates, keep a human making the decision, commission the independent audit, and publish it.
Related
Bias audit
An assessment of whether a hiring tool produces different selection rates across protected groups, performed by a party independent of the tool’s vendor.
Human in the loop
A requirement that a person makes or can meaningfully change an automated decision, rather than reviewing it after the fact or approving it as a formality.
Adverse impact
A substantially different rate of selection for a protected group that results from a neutral-seeming employment practice, regardless of whether anyone intended it.
How CalHire handles this: AI governance, bias auditing and the audit trail