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Algorithmic Bias in Automated Decision-Making: Hidden Risks through the Perspective of AI-Driven Tax Compliance. The EU’S Response from GDPR to the AI Act

Author

Listed:
  • Niki Georgiadou

    (University of Patras, Department of Management Science and Technology)

  • Georgios Thanasas

    (University of Patras, Department of Management Science and Technology)

  • Konstantinos Theodoridis

    (University of Patras, Department of Management Science and Technology)

  • Athanasios Mandilas

    (Democritus University of Thrace, Department of Accounting and Finance)

Abstract

This study discusses the common problem of algorithmic bias in artificial intelligence (AI) systems and its implications on tax compliance and enforcement. Although AI-driven decision-making has the potential for greater efficiency and scalability, it also carries the potential for perpetuating social disparities via biased algorithms. It lights the dilemma of balancing innovation and fairness, along with the necessity of responsible artificial intelligence practices for fair and transparent outcomes especially on tax compliance studying the regulatory responses taken by the European Union (EU), namely through the General Data Protection Regulation (GDPR) and the AI Act proposal.

Suggested Citation

  • Niki Georgiadou & Georgios Thanasas & Konstantinos Theodoridis & Athanasios Mandilas, 2026. "Algorithmic Bias in Automated Decision-Making: Hidden Risks through the Perspective of AI-Driven Tax Compliance. The EU’S Response from GDPR to the AI Act," Springer Proceedings in Business and Economics,, Springer.
    • Handle: RePEc:spr:prbchp:978-3-032-19314-8_11
    DOI: 10.1007/978-3-032-19314-8_11
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