GB/T 46801-2025Artificial intelligence social experiments - Design guidelines (English PDF)

Foreword

This document complies with the provisions of GB/T 1.1-2020 "Standardization Work Guidelines Part

1.Structure and Drafting Rules of Standardization Documents". Drafting. GB/T 46801 "Guidelines for the Design of Social Experiments in Artificial Intelligence" and GB/T 46802 "Guidelines for the Implementation of Social Experiments in Artificial Intelligence" and GB/T 46799, "Evaluation Guidelines for Social Experiments in Artificial Intelligence," together constitute the national standard system supporting the conduct of social experiments in artificial intelligence. Please note that some content in this document may involve patents. The issuing organization of this document assumes no responsibility for identifying patents. This document was proposed and is under the jurisdiction of the National Working Group on Basic Standardization of Social Application and Evaluation of Intelligent Technologies (SAC/SWG35). This document was drafted by: Zhejiang University, Hefei Qinghe Intelligent Technology Co., Ltd., Tsinghua University, and the CPC Ordos Municipal Committee Network Security Department. National Information Technology Commission Office, China National Institute of Standardization, Runze Intelligent Computing Technology Group Co., Ltd., Zhejiang Provincial People's Hospital, Shanghai Computer Software Technology Development Center, Shenzhen Pingshan District Government Service and Data Management Bureau, Zhixing Think Tank (Hangzhou) Co., Ltd., Lingxin Qiaoshou (Beijing) Technology Co., Ltd., Guizhou University, Zaozhuang City Cybersecurity Protection Center, Harbin Institute of Technology (Shenzhen), Qingdao Tongchan Intelligent Technology Co., Ltd. Joint-stock limited company. The main drafters of this document are. Huang Cui, Su Jun, Zhou Chaonan, Zhong Jun, Wei Yuming, Shang Erping, Wang Yongjie, Zhang Fang, Ru Peng, Chen Junhua, and Liu Yang. Jin Dong, Li Li, Zhang Xian, Zhu Jing, Shen Cheng, Cao Gang, Chi Hao, Wang Yu, Li Hanlin, Lü Liyuan, Cen Xiaoteng, Yang Qingfeng, Chen Mingang, Wang Xu, Guo Teng, He Daojing and Guo Xiaoxuan.

Human society is moving towards an intelligent society supported by artificial intelligence as a key technology. This requires summarizing and forming experiences and guidelines for the development and governance of an intelligent society. Laws and theories, proactively exploring standards and norms for the development and governance of an intelligent society, and improving the systems and mechanisms adapted to the development and governance of an intelligent society will have It effectively supports the modernization of the national governance system and governance capabilities. Artificial intelligence social experiments are a key method for exploring the development and governance paths of intelligent societies, and also a standardization approach for the development and governance of intelligent societies. One of the fundamental methods. Through conducting long-term, wide-area, multidisciplinary artificial intelligence social experiments, it systematically identifies, defines, observes, and evaluates... This paper analyzes the impact of specific intelligent technologies on social application scenarios, examines potential governance challenges, summarizes countermeasures, and formulates solutions and norms. It is of great significance to reasonably regulate the social risks of technology application and promote the healthy development of technology. my country has established a national standards system to support social experiments in artificial intelligence. Within this system, GB/T 46801 "Artificial Intelligence..." is a standard that... The purpose of "Guidelines for Designing Social Experiments in Artificial Intelligence" is to provide basic methodological guidelines for designing social experiments in artificial intelligence, and to offer suggestions for the design of social experiments in artificial intelligence. The experimental methodology, design principles, applicable scenarios, and operational suggestions provide guidance for relevant technical and application stakeholders engaged in social experiments related to artificial intelligence. This provides a reference for the research subjects and guides the development of social experiments related to artificial intelligence, thereby improving the scientific rigor and standardization of experimental design. Guidelines for Designing Social Experiments in Artificial Intelligence

1 Scope

GB/T 46801-2025 is the Chinese national standard covering designing the experiment - the question, the population and the control, the duration, the consent and the ethics review, and the arrangements for stopping if harm appears. First edition, the first of the three parts of this unusual family. It was issued on 2 December 2025 and has been in force since 2 December 2025, as a first edition. The document is under the responsibility of the Standardization Administration of China. This page is published from the official record of the 2025 edition; the clause text of a standard this recent is not yet in circulation, and the figures, limits and tables it contains are those of the document itself, delivered in full with the English translation.

This document establishes the general principles and phased procedures for designing social experiments in artificial intelligence, and provides a methodological framework for such experiments. The document provides guidance and suggestions on design principles, applicable scenarios, and operational procedures, and includes examples. This document is intended to guide relevant parties, including entities involved in the application, research, and technology of artificial intelligence social experiments, in conducting artificial intelligence social experiments. The design of the experiment.

2 Normative references

This document has no normative references.

3 Terms and Definitions

The following terms and definitions apply to this document.

3.1 Introducing specific artificial intelligence technologies into social activities creates AI application scenarios. Through experimental design, the general meanings within these scenarios are explored. Sexual influence is transformed into a measurable variable with clear connotations and precise concepts, and scientific methods are used to track and analyze it at the micro-individual and meso-group levels. This study examines the development and changes in the social system, including its structure and macro-level mechanisms, to comprehensively assess the actual impact and potential risks of artificial intelligence applications, and then proposes countermeasures and recommendations. process. Note

1.Artificial intelligence social experiments mainly employ four types of methods. natural experiments, field experiments, survey experiments, and computational experiments. Note

2.Social experiments with artificial intelligence typically include three experimental phases. organizational application, scientific measurement, and comprehensive feedback.

3.2 natural experiment By leveraging exogenous factors such as natural events, major policies, and chance occurrences, we can explore the application scenarios of artificial intelligence for social groups. To approximate the effect of randomized intervention, the sample was divided into experimental and control groups, and characterization data of subjects in different groups were observed and collected. A social experimental method that compares and analyzes the differences between the experimental group and the control group to determine the extent to which artificial intelligence applications have an impact on the subjects.

3.3 field experiment The experimenters independently constructed artificial intelligence application scenarios and randomly assigned them to subjects, determining the experimental and control groups, and collecting and... The study observed the representational data of subjects in different groups, compared and analyzed the differences between the experimental and control groups, and evaluated the effects of artificial intelligence applications on the subjects. Social experimental methods for impact effects.

3.4 Survey experiment Researchers embedded self-constructed descriptions of artificial intelligence application scenarios into questionnaires and randomly assigned them to participants. The experiment identified experimental and control groups, observed and collected data on the differences in responses to questionnaires from subjects in different groups, and assessed the simulation based on descriptive information.