AI is increasingly used to filter job applications, potentially overlooking qualified candidates. Automated systems analyse CVs and cover letters, ranking applicants based on keywords and pre-defined criteria. This process can inadvertently screen out individuals who don't perfectly match the algorithm's ideal profile, even if they possess the skills and experience necessary for the role.
The reliance on AI in recruitment raises concerns about bias and lack of human oversight. Algorithms may perpetuate existing inequalities if they are trained on data that reflects historical biases. Candidates from underrepresented groups or those with unconventional career paths may be unfairly disadvantaged. The lack of transparency in AI decision-making makes it difficult to identify and correct these biases.
To mitigate these issues, companies should regularly audit their AI recruitment systems for bias and ensure that human recruiters are involved in the final selection process. Diversifying training data and using AI to augment, rather than replace, human judgment can lead to more equitable and effective hiring outcomes.