Artificial intelligence in the hiring process: uses and consequences

• Ano de defesa: 2025
• Autor(a) principal: Silva, Humberta Karinne da Conceição Santos
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Consequences of AI usage; Consequências do uso da IA; Gestão de pessoas; Hiring; Human resource management; Personnel selection; Seleção de pessoas; Usage of artificial intelligence; Uso de inteligência artificial
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/12/12139/tde-03102025-113052/

In the neoliberal context, Artificial Intelligence (AI) is employed across all spheres of human activity, from the most prosaic tasks to the most complex. In both the global and Brazilian contexts, organizations have increasingly adopted 4.0 technologies as part of broader automation strategies, integrating them into various practices, including hiring, in Human Resource Management (HRM). The aim has been to make these processes more agile, objective, and efficient. However, algorithms are developed and used by people, and as such, they inherently carry conscious and/or unconscious biases embedded in their training data, design, and user outputs; therefore, these systems are not neutral. These biases manifest through the choice of input parameters, thresholds, and constraints, which consequently influence how algorithms operate and the decisions they generate. When applying technology to rank candidates, Talent Acquisition (TA) professionals are subject to hidden criteria that may be discretionary and, depending on the social and organizational context, even discriminatory. Moreover, this impact becomes especially significant when users cannot explain the system\'s outputs. Therefore, this research aims to address the following question: To what extent does the continuous use of artificial intelligence in the hiring process lead to undesirable consequences and changes for stakeholders? To address this question, the dissertation was divided into three articles, each aimed at exploring the phenomenon from complementary angles: (1) A systematic literature review on the consequences of AI use in hiring; (2) A qualitative study analyzing how AI is transforming the hiring processes of German headquarters and their Brazilian subsidiaries; (3) A qualitative investigation of stakeholder experiences within the hiring process, focusing on identify the consequences of AI adoption. The three publications reveal that the consequences of using AI in hiring encompass a complex interplay of benefits and drawbacks that significantly affect users, candidate experiences, the talent acquisition profession, organizations, and society. The findings reveal a hiring process that is fragmented, with different kinds of systems processing large amounts of applicant data to provide unique results, which the TA professional must oversee and monitor to create shortlists of the most \"suitable\" individuals. By customizing recommendations based on past decision- making patterns, these systems appear efficient while influencing organizational structure and behavior. Although these technologies deliver the expected results, such as reduced hiring time, they are not without controversy, and the undesirable consequences outweigh the desirable ones.