# A Comprehensive Review and Systematic Analysis of Artificial Intelligence Regulation Policies

arXiv: https://arxiv.org/abs/2307.12218 · HTML: https://mlsanity.com/paper/2307.12218/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 35 references that are in the map.
- First posted on arXiv 23 Jul 2023.

## Builds on (most cited first, 1 of 1)

- [Dilemma of the Artificial Intelligence Regulatory Landscape](https://mlsanity.com/paper/2112.09325/) (2021)

## Built on by (most cited first, 4 of 4)

- [Large Language Model Safety: A Holistic Survey](https://mlsanity.com/paper/2412.17686/) (2024)
- [T2IW: Joint Text to Image & Watermark Generation](https://mlsanity.com/paper/2309.03815/) (2023)
- [Between Innovation and Oversight: A Cross-Regional Study of AI Risk Management Frameworks in the EU, U.S., UK, and China](https://mlsanity.com/paper/2503.05773/) (2025)
- [An Evaluation Framework for National AI Regulation](https://mlsanity.com/paper/2608.15417/) (2026)

## Abstract (arXiv)

Due to the cultural and governance differences of countries around the world, there currently exists a wide spectrum of AI regulation policy proposals that have created a chaos in the global AI regulatory space. Properly regulating AI technologies is extremely challenging, as it requires a delicate balance between legal restrictions and technological developments. In this article, we first present a comprehensive review of AI regulation proposals from different geographical locations and cultural backgrounds. Then, drawing from historical lessons, we develop a framework to facilitate a thorough analysis of AI regulation proposals. Finally, we perform a systematic analysis of these AI regulation proposals to understand how each proposal may fail. This study, containing historical lessons and analysis methods, aims to help governing bodies untangling the AI regulatory chaos through a divide-and-conquer manner.