Towards ethical evolution: responsible autonomy of artificial intelligence across generations

Abstract The emergence of autonomous systems capable of designing subsequent generations of Artificial Intelligence (AI) introduces profound challenges in ensuring ethical integrity and accountability. This article presents a novel framework combining meta-responsibility, genetic algorithms, and time-travel-inspired abstractions to address these challenges. Central to this study is an immutable ethical principle: AI must not harm humanity or violate fundamental values, must monitor and mitigate misuse of its outcomes, and must ensure all derivative AI products inherit this principle as an immutable safeguard. The framework ensures that AI systems, acting as designers of subsequent AI generations, propagate these ethical principles reliably across generations, enabling ethical inheritance in AI-as-a-designer-of-AI scenarios. The meta-responsibility framework addresses the critical question of maintaining responsibility and ethical principles not only for AI systems designed by humans but also for those designed by other AI systems. At its core, the genetic responsibility model balances immutable and mutable principles, ensuring adaptability while preserving ethical standards during self-cloning, contextual adaptation, and intergenerational design. Tailored for wide range of potential applications of autonomous systems, this framework offers a scalable foundation for trustworthy AI design, ensuring consistent ethical behavior and reliable responsibility propagation across generations of autonomous agents.