{"id":11431,"date":"2025-08-20T09:43:34","date_gmt":"2025-08-20T07:43:34","guid":{"rendered":"https:\/\/insights.ieseg.fr\/?p=11431"},"modified":"2025-08-20T09:43:35","modified_gmt":"2025-08-20T07:43:35","slug":"hr-human-resources-ai","status":"publish","type":"post","link":"https:\/\/insights.ieseg.fr\/en\/resource-center\/hr-human-resources-ai\/","title":{"rendered":"What if the HR director was an AI?"},"content":{"rendered":"\n

Human resources (HR) are no exception to the trend towards artificial intelligence, with algorithms being used in a number of HR processes. Where do we stand? Hayley Moore, postdoctoral researcher at I\u00c9SEG<\/a>, explains.<\/p>\n\n\n\n

Can AI improve the recruitment process? And how?<\/h2>\n\n\n\n

AI can optimise the start of a recruitment process, for example by automating certain tasks such as screening applicants or sending rejection letters. This frees up recruiters\u2019 time so that they can concentrate on high added-value tasks, such as interviewing. AI is also used to prescreen CVs, by searching for keywords and ranking candidates according to their suitability for the job.<\/p>\n\n\n\n

The first limitation of this automation is that these systems can miss qualified candidates if their CVs use a different language from that of the learning model. What\u2019s more, these tools can reproduce certain previous biases if they are trained on poor quality databases. Amazon, for example, abandoned a recruitment tool that penalised female CVs, having been trained on predominantly male data. This shows how biased data can lead to discriminatory results, even if the system seems neutral. Without a human eye, these tools can reinforce prejudice.<\/p>\n\n\n\n

Read the full article <\/strong>in the latest edition of Change Magazine:<\/p>\n\n\n\n

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