Guardrails on AI

Summary:

We would like to know what are the guardrails that are built into the system. and would like to understand that the system would rate candidates on the following parameters:

• Profile

• Education

• Experience

• Skill

It would be helpful if you could provide a detailed overview of the process being followed to mitigate algorithmic bias. Along with the overview, we would also like to get answers to the following questions:

• Does the selection or rejection of candidates have an impact on the ratings of the candidate over time?

• Is the data used for training diverse? As we would not want candidates of only a certain background/ profile to get pushed by the system.