Browsing by Author "Prill-Gonzalez, Johanna Marie"
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- The ethical risks of overlooking human potential in AI recruitment : current unethical outcomes and future mitigation strategiesPublication . Prill-Gonzalez, Johanna Marie; Fioravante, RosaThe rapid integration of Artificial Intelligence (AI) into recruitment processes has revolutionized hiring practices, offering significant opportunities while introducing profound ethical risks. This thesis aims to provide an overview of current debates on the ethical risks and opportunities posed by AI recruitment and their mitigation strategies, with a particular focus on the underexplored risk of AI-Defined Candidate Evaluation Filters Overlooking Human Potential. The central research question is: How can organizations deploy AI recruitment systems without risking overlooking human potential, especially among candidates with more individualistic or non-conforming backgrounds? Utilizing a qualitative systematic literature review, the study synthesizes peer-reviewed articles as well as established books in the field to assess AI's ethical challenges and identify gaps in the literature. Findings reveal that AI-defined evaluation filters can exclude capable candidates from diverse backgrounds, amplify biases, undermine inclusivity, and devalue human judgment. These various outcomes result in workforce homogeneity, stifling innovation and adaptability. To better understand the interconnected risks, the framework categorizes these into three dimensions: Inclusivity & Accessibility, Depth & Accuracy of Candidate Evaluation, and Organizational Adaptability & Long-Term Impact. Finally, the thesis addresses these challenges by proposing a mitigation framework based on two dimensions: resource intensity and implementation horizon. Strategies include expanding outreach channels, conducting algorithmic bias audits, refining data practices to exclude sensitive attributes, and fostering human-AI collaborative evaluation processes.