Recruiting algorithms are machine learning models that are used by companies to automate and streamline the hiring process. These algorithms analyze applicant data and make predictions about their suitability for a job.
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Machine learning models are computer programs that can learn from data and make predictions or decisions without being explicitly programmed. They use statistical techniques to identify patterns in data and generalize from them.
Fairness metrics are measures used to evaluate how fair or unbiased a machine learning model is in its decision-making process. They assess whether the model treats different groups of individuals equally and without discrimination.
Applicant tracking system (ATS): This is software used by companies to manage their recruitment process. It helps track applicants, store resumes, schedule interviews, and often integrates with recruiting algorithms to automate parts of the hiring process.