Let's have a chat with the EU AI Act
This addresses the problem of navigating complex AI regulations for AI developers, but it is incremental as it applies existing RAG methods to a new domain.
The paper tackles the challenge of ensuring compliance with the EU AI Act and related standards by introducing an AI-driven self-assessment chatbot that uses a Retrieval-Augmented Generation (RAG) framework to provide real-time, context-aware guidance, streamlining regulatory adherence and reducing complexity.
As artificial intelligence (AI) regulations evolve and the regulatory landscape develops and becomes more complex, ensuring compliance with ethical guidelines and legal frameworks remains a challenge for AI developers. This paper introduces an AI-driven self-assessment chatbot designed to assist users in navigating the European Union AI Act and related standards. Leveraging a Retrieval-Augmented Generation (RAG) framework, the chatbot enables real-time, context-aware compliance verification by retrieving relevant regulatory texts and providing tailored guidance. By integrating both public and proprietary standards, it streamlines regulatory adherence, reduces complexity, and fosters responsible AI development. The paper explores the chatbot's architecture, comparing naive and graph-based RAG models, and discusses its potential impact on AI governance.