Provable AI Ethics and Explainability in Medical and Educational AI Agents: Trustworthy Ethical Firewall

Abstract

Rapid advances in artificial intelligence are transforming high-stakes fields like medicine and education while raising pressing ethical challenges. This paper introduces the Ethical Firewall Architecture—a comprehensive framework that embeds mathematically provable ethical constraints directly into AI decision-making systems. By integrating formal verification techniques, blockchain-inspired cryptographic immutability, and emotion-like escalation protocols that trigger human oversight when needed, the architecture ensures that every decision is rigorously certified to align with core human values before implementation. The framework also addresses emerging issues, such as biased value systems in large language models and the risks associated with accelerated AI learning. In addition, it highlights the potential societal impacts—including workforce displacement—and advocates for new oversight roles like the Ethical AI Officer. The findings suggest that combining rigorous mathematical safeguards with structured human intervention can deliver AI systems that perform efficiently while upholding transparency, accountability, and trust in critical applications.

Ähnliche Arbeiten