Researchers Propose Global Standard for AI Transparency and Accountability

Global: Researchers Propose Global Standard for AI Transparency and Accountability

A coalition of researchers from several institutions has outlined a proposal for a worldwide framework that would standardize the exchange of information about artificial‑intelligence systems. The paper, submitted on 25 July 2023 and revised most recently on 20 January 2026, argues that such a framework could enable diverse local regulations to coexist while providing clear, comparable data to the public.

Motivation and Context

According to the authors, the rapid deployment of high‑risk AI applications has created a patchwork of national rules that can conflict with one another. They contend that a unified, open standard would help mitigate regulatory fragmentation and support policymakers in making informed decisions.

Proposed Framework Elements

The proposal emphasizes a lightweight regulatory approach that leverages automated assessments and benchmarks. Results from these assessments would be communicated through standardized “AI cards” published in an open register, allowing stakeholders to compare systems on common metrics.

AI Cards and Open Register

The authors describe AI cards as concise documents that report standardized measures tailored to the specific high‑risk uses of each system. By making these cards publicly available, the framework aims to facilitate meaningful comparisons and enhance transparency for consumers, regulators, and industry alike.

Regulatory Alignment

The paper notes that AI cards could serve as evidence for conformity assessments under emerging policies such as the European Union’s AI Act, thereby linking the proposed standard to existing legislative efforts.

Collaboration and Implementation

To avoid excessive regulatory burden, the authors recommend close collaboration between regulators and industry. They suggest that shared development of the AI register and automated tools would create a scalable, cost‑efficient solution that benefits all parties.

Publication Timeline

The manuscript was first posted to arXiv on 25 July 2023 (v1), updated on 26 February 2025 (v2), and most recently revised on 20 January 2026 (v3). The authors provide a DOI (10.48550/arXiv.2307.13658) for reference.

This report is based on information from arXiv, licensed under Academic Preprint / Open Access. Based on the abstract of the research paper. Full text available via ArXiv.