From Ethical Principles to Technical Safeguards: A Unified Framework for Safe and Human-Centered Artificial Intelligence

The growing use of artificial intelligence in healthcare, employment, and business has raised significant concerns regarding safety, ethics, and societal impact. While prior work offers ethical guidelines and technical solutions independently, a gap remains between ethical principles and practical system design. This study presents a unified framework that integrates ethical values, technical safeguards, and governance mechanisms to support safe and human-centered artificial intelligence. The framework maps principles such as fairness, accountability, transparency, and non-maleficence to engineering practices including safe reward design, explainable models, robustness testing, and privacy-preserving techniques. Governance and regulatory alignment are incorporated as continuous components of the AI lifecycle. Use-case analyses demonstrate how ethical objectives can be operationalized across real-world domains. The results emphasize that AI safety must be treated as a socio-technical process combining technical alignment with institutional oversight. This work contributes a practical approach for translating ethical commitments into trustworthy and resilient AI systems.