The class ceiling in recruitment
: a study examining the social biases in recruitment processes nowadays and possible solutions based on artificial intelligence

  • Helena Holtappels (Student)

Student thesis: Master's Thesis

Abstract

Recruitment processes today face challenges such as bias, fairness, and the pursuit of a diverse workforce. The war for talent also underscores the importance of examining recruitment processes. This study explores the potential of artificial intelligence (AI) to mitigate biases in hiring while encouraging diversity. This thesis aimed to discover the potential of AI in human resource (HR) management. We interviewed experts in the field and reviewed the existing literature to determine optimal HR use cases of AI. This depended on contextual factors such as industry type and urban versus rural hiring dynamics. While skepticism about AI's effectiveness persists, experts agreed on its utility for initial screening, especially in larger organizations. Skill assessment is emerging as a focal point, with tools like HiPeople gaining traction for predicting hard skills. However, experts agreed soft skills assessment remains an area where human interaction excels. Diverse teams are recognized for their positive impact, in line with academic views. In summary, while AI is useful in areas of recruiting, implementation requires consideration of contextual factors.
Date of Award22 Jan 2024
Original languageEnglish
Awarding Institution
  • Universidade Católica Portuguesa
SupervisorPeter V. Rajsingh (Supervisor)

Keywords

  • Artificial intelligence
  • Machine learning
  • Disruptive innovation
  • Recruiting
  • Talent acquisition
  • Biases
  • Classism
  • Nepotism
  • Similarity bias
  • Resource based view (RBV)

Designation

  • Mestrado em Gestão

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