Nov 20, 2024
A Fundamental Rethinking to AI Evaluations: Establishing a Constitution-Based Framework
Arrow Paquera, and Paul Ivan Enclonar
Summary
While artificial intelligence (AI) presents transformative opportunities across various sectors, current safety evaluation approaches remain inadequate in preventing misuse and ensuring ethical alignment. This paper proposes a novel two-layer evaluation framework based on Constitutional AI principles. The first phase involves developing a comprehensive AI constitution through international collaboration, incorporating diverse stakeholder perspectives through an inclusive, collaborative, and interactive process. This constitution serves as the foundation for an LLM-based evaluation system that generates and validates safety assessment questions. The implementation of the 2-layer framework applies advanced mechanistic interpretability techniques specifically to frontier base models. The framework mandates safety evaluations on model platforms and introduces more rigorous testing for major AI companies' base models. Our analysis suggests this approach is technically feasible, cost-effective, and scalable while addressing current limitations in AI safety evaluation. The solution offers a practical path toward ensuring AI development remains aligned with human values while preventing the proliferation of potentially harmful systems.
Cite this work:
@misc {
title={
A Fundamental Rethinking to AI Evaluations: Establishing a Constitution-Based Framework
},
author={
Arrow Paquera, and Paul Ivan Enclonar
},
date={
11/20/24
},
organization={Apart Research},
note={Research submission to the research sprint hosted by Apart.},
howpublished={https://apartresearch.com}
}
