Navigating the sociotechnical labyrinth: Dynamic certification for responsible embodied AI

TL;DR

This paper proposes a novel dynamic certification framework for embodied AI systems, enabling adaptive regulation that keeps pace with their continuous evolution and addresses sociotechnical challenges.

Contribution

It introduces the concept of dynamic certification, a transdisciplinary approach designed to adapt regulatory oversight to evolving AI systems in real-time.

Findings

Framework supports continuous AI system adaptation

Enhances safety and ethical compliance

Bridges gap between technology and regulation

Abstract

Sociotechnical requirements shape the governance of artificially intelligent (AI) systems. In an era where embodied AI technologies are rapidly reshaping various facets of contemporary society, their inherent dynamic adaptability presents a unique blend of opportunities and challenges. Traditional regulatory mechanisms, often designed for static -- or slower-paced -- technologies, find themselves at a crossroads when faced with the fluid and evolving nature of AI systems. Moreover, typical problems in AI, for example, the frequent opacity and unpredictability of the behaviour of the systems, add additional sociotechnical challenges. To address these interconnected issues, we introduce the concept of dynamic certification, an adaptive regulatory framework specifically crafted to keep pace with the continuous evolution of AI systems. The complexity of these challenges requires common progress in multiple domains: technical, socio-governmental, and regulatory. Our proposed transdisciplinary approach is designed to ensure the safe, ethical, and practical deployment of AI systems, aligning them bidirectionally with the real-world contexts in which they operate. By doing so, we aim to bridge the gap between rapid technological advancement and effective regulatory oversight, ensuring that AI systems not only achieve their intended goals but also adhere to ethical standards and societal values.