ETD

• Artificial Intelligence
• Economic Ethics
• Economics
• EU AI Act
• Job Recruitment
• Labour Market

Artificial intelligence is now integrated into every step of the hiring process, from drafting job ads to screening CVs, video interviewing, and matching profiles on sites like LinkedIn. This thesis investigates the ethical consequences of these technological advancements, with special focus on the problems of distributive justice.
The argument rests on five interrelated ethical pillars: fairness, transparency, accountability, privacy and autonomy; and reveals that existing AI recruiting technologies systematically negatively impact those already most disadvantaged in the labour market. This result is due to bias in training data, lack of transparency in decision-making, and dispersed accountability systems. The thesis uses John Rawls’s theory of justice as its evaluative framework, and argues that the prevalent tools violate the difference principle by providing efficiency gains for employers while concentrating the costs on marginalised candidates.
A review of the regulatory framework (including the EU AI Act, GDPR, NYC Local Law 144, and the Illinois AI Video Interview Act) shows a significant difference between governance fundamentals and enforcement realities. The thesis presents an ordered framework of technical, organisational and regulatory safeguards and draws recommendations for employers, AI providers, regulators and candidates. The conclusion is that AI is not by design unjust in hiring, but its current deployment fails to meet the minimum standards of a fair system.