Ethical and Legal Perspectives on Voice Biometric Misidentification in Artificial Intelligence-Based Authentication Systems - Aser Heber Ginting; Muhammad Ayyasi Fawaz; Muhammad Joefitra Zaqy; Fachrurrozi Syah Putra Lubis; Joceline Schellenberg W (SEAN Institute, 2026)
Voice biometric authentication has become an increasingly important component of artificial intelligence (AI)-based identity verification systems due to its convenience, scalability, and integration into digital services. However, the growing adoption of voice biometrics has also raised significant ethical and legal concerns, particularly regarding biometric misidentification caused by algorithmic bias, adversarial attacks, environmental noise, and demographic variability. This study examines the ethical and legal implications of voice biometric misidentification in AI-based authentication systems through a systematic literature review combined with comparative legal analysis. The review synthesizes findings from recent studies on AI-driven speaker recognition, biometric fairness, explainable AI, and international data protection regulations, including the General Data Protection Regulation (GDPR), the European Union Artificial Intelligence Act (EU AI Act), and emerging biometric governance frameworks. The analysis identifies four critical challenges: algorithmic discrimination, insufficient transparency in AI decision-making, limitations in accountability for automated authentication errors, and inadequate protection of biometric privacy. Furthermore, the study proposes an integrated governance framework consisting of fairness-aware model development, explainable biometric decision mechanisms, continuous bias auditing, human oversight, and regulatory compliance to reduce the risk of voice biometric misidentification. The findings demonstrate that technological accuracy alone is insufficient to establish trustworthy biometric authentication; ethical principles and legal safeguards must be embedded throughout the AI system lifecycle to ensure fairness, accountability, transparency, and protection of individual rights. This research contributes to the development of responsible AI governance and provides practical recommendations for policymakers, technology developers, and organizations implementing AI-based voice biometric authentication systems.