AI for recruiting is the application of artificial intelligence (such as machine learning, natural language processing, and sentiment analysis) to the recruitment function.
On the one hand AI screening can mitigate some intrinsic human racial bias in decision making, by removing the unconscious bias humans bring to evaluating candidates and CVs. AI models can be tasked with ensuring that job application outcomes are fairer and not based on data correlated with protected demographic variables such as race and gender. The idea is that computers can assess data points objectively – free from the assumptions, biases, and mental fatigue to which humans are susceptible.
In reality, because historical recruitment data is often used to train the machine learning algorithm, it can still cause and even amplify past bias. This could result in locking ethnic minorities out of employment or, at least, heavily hinder their possibilities to be considered for jobs that they are qualified for.
Resume screening is the first hurdle applicants typically face when they apply for a job. Despite the many empirical studies showing bias at the resume‐screening stage, fairness at this funnelling st… CVs are worldwide one of the most frequently used screening tools. CV screening is also the first hurdle applicants typically face when they apply […]
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