Towards AI Transparency and Accountability: A Global Framework for Exchanging Information on AI Systems

TL;DR

This paper proposes a global open standard for AI information exchange to enhance transparency and accountability, enabling effective regulation, public comparison, and conformity assessments of AI systems worldwide.

Contribution

It introduces a lightweight, scalable framework for AI transparency using AI cards and automated assessments, fostering international cooperation and compliance.

Findings

Design of AI cards for standardized reporting

Use of automated benchmarks for AI assessment

Framework supports compliance with regulations like the EU AI Act

Abstract

We propose that future AI transparency and accountability regulations are based on an open global standard for exchanging information about AI systems, which allows co-existence of potentially conflicting local regulations. Then, we discuss key components of a lightweight and effective AI transparency and/or accountability regulation. To prevent overregulation, the proposed approach encourages collaboration between regulators and industry to create a scalable and cost-efficient mutually beneficial solution. This includes using automated assessments and benchmarks with results transparently communicated through AI cards in an open AI register to facilitate meaningful public comparisons of competing AI systems. Such AI cards should report standardized measures tailored to the specific high-risk applications of AI systems and could be used for conformity assessments under AI transparency and accountability policies such as the European Union's AI Act.