AI Policy and Regulatory Text Dataset

**AI Policy and Regulatory Dataset**

**Overview**

Search AI Global provides a curated dataset of text passages extracted from documents within the **AI Policy and Regulatory domain**. The dataset is designed to support research, monitoring, and analysis of how artificial intelligence is governed across jurisdictions, institutions, and policy contexts.

The dataset focuses on high-signal public documents that shape or interpret the regulatory landscape for AI systems. Initial focus is on US sub/national with a view to extend globally.

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**Domain definition**

The AI Policy and Regulatory domain cover's documents related to the **governance, regulation, legal frameworks, standards, and public policy** shaping the development, deployment, and societal impact of AI systems. This definition has been translated into search parameters that are used within the Google search api to identify relevant documents. In the near future we are hoping to combine an LLM and human in the loop validation layer.

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**Data source & processing**

- **Source:** Public web documents identified via curated Google Search API queries.
- **Text extraction:** IBM’s Docling tool.

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**Dataset structure**

- This dataset is at the passage level. Thus, there is one row per passage of text.
- A relatively simple schema has been defined. Should users want more fields like embeddings, coordinates etc. then please get in touch.

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**Use cases**

- Regulatory monitoring and trend analysis.
- Cross-jurisdictional policy comparison.
- LLM training and evaluation on regulatory content.
- Compliance, risk, and governance research.

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**Update frequency**

- Daily updates are in development.
- The current release should be considered static.

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**Feedback**

We welcome feedback to validate user value prior to scaling, including requests for additional coverage or metadata - **[e-mail]**

搜集汇总

背景与挑战

背景概述

该数据集聚焦于人工智能政策与法规领域，收录了从公共网络文档中提取的文本段落，旨在支持对AI治理框架的研究、监测和分析。数据集适用于监管趋势跟踪、跨司法管辖区政策比较以及大语言模型训练等应用场景。