Ethical Principles and Legal Responsibility in Artificial Intelligence: Ensuring Fairness and Accountability in AI Governance

Abstract

Artificial intelligence (AI) presents significant ethical and legal challenges, particularly regarding algorithmic bias, opaque decision-making, and the absence of clear liability mechanisms. This study examines how key ethical principles such as transparency, fairness, privacy protection, and accountability can be integrated into a legal responsibility framework to support fair and accountable AI governance. The research uses a normative juridical method with conceptual, statutory, and case approaches to assess the limitations of traditional liability models when applied to autonomous systems. The findings indicate that algorithmic bias can lead to both material and procedural injustice, while gaps in regulation create uncertainty about who should bear responsibility for AI-related harm. This study recommends the application of fairness by design, mandatory model documentation, algorithmic audits, and shared responsibility among developers, operators, and users. These findings highlight the need for adaptive regulation to ensure that the use of AI upholds justice, protects individual rights, and serves the public interest.