文学文享（96）：泛读文献

摘要：Today, the editor will interpret and share "Meta synthesis Study on the Interaction Framework of Factors Influencing Data security

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今天小编为大家带来文献泛读。

欢迎您的访问！

Share interest, spread happiness, increase Knowledge, and leave beautiful.

Dear, this is the LearingYard New Academy!

Today, the editor brings you the literature reading.

Welcome to visit!

1 内容摘要（Content summary）

今天小编将从“思维导图、精读内容、知识补充”三个板块，解读分享文献《生成式人工智能数据安全影响因素互作用框架的元综合研究》。

Today, the editor will interpret and share "Meta synthesis Study on the Interaction Framework of Factors Influencing Data security in Generative Artificial Intelligence" from the three sections of "mind map, intensive reading content, and knowledge supplement".

2 思维导图（Mind mapping）

3 精读内容（Intensive reading content）

本次泛读的文章是刊载于《图书情报工作》上的一篇关于生成式人工智能数据安全的文章，文章使用了基于系统性文献筛选的元综合分析法，将历史文献进行编码和阐释，构建出了影响因素模型，为促进生成式人工智能数据安全相关研究提供了一定的理论参考。

The article extensively read this time is an article about data security in generative artificial intelligence published in "Library and Information Work". The article uses a meta synthesis analysis method based on systematic literature screening to encode and interpret historical literature, and constructs an influencing factor model, providing a theoretical reference for promoting research on data security in generative artificial intelligence.

文章开篇的引言中指出，生成式人工智能作为一种具有良好互动性和高度通用性的技术大模型，现已被应用于很多领域，伴随而来的数据安全问题也成为了相关部门关注的焦点。虽然各国都启动了响应的监管和控制，但是生成式AI发展太快，数据安全问题仍愈演愈烈，故探究数据安全及其互作用关系十分有意义。

The introduction at the beginning of the article points out that generative artificial intelligence, as a technology model with good interactivity and high universality, has been applied in many fields, and the accompanying data security issues have also become a focus of attention for relevant departments. Although various countries have initiated responsive regulation and control, the rapid development of generative AI has led to escalating data security issues. Therefore, exploring data security and its interrelationships is of great significance.

国内外学者对生成式AI数据安全进行了十分丰富的研究，主要分为生成式AI技术本身的数据安全和生成式AI技术应用引发的数据风险两个方面，前者又分为了生成式AI生命周期视角和生成内容视角两个不同的研究视角，而后者又可分为意识形态层面的风险和对现实层面的风险。

Domestic and foreign scholars have conducted extensive research on the data security of generative AI, mainly divided into two aspects: the data security of generative AI technology itself and the data risks caused by the application of generative AI technology. The former is further divided into two different research perspectives: the lifecycle perspective of generative AI and the content perspective of generative AI. The latter can be further divided into ideological risks and risks to the real world.

文章主要使用的方法是元综合法，它是一种对特定目标主体的相关文献进行检索、筛选、提取、解释、融合、重建并详细解释的系统分析方法，该方法在管理学、医学和图情领域均有所应用，它不是对概念的简单汇总，而是对概念进行重新定义及拓展研究。

The main method used in the article is the meta synthesis method, which is a systematic analysis method for searching, screening, extracting, interpreting, fusing, reconstructing, and providing detailed explanations of relevant literature on a specific target subject. This method has been applied in the fields of management, medicine, and graphic engineering. It is not a simple summary of concepts, but rather a redefinition and expansion of concepts.

作者对生成式AI数据安全相关中英文文献进行了全面的检索，检索范围涵盖各大中英文数据库，共检索到文献3100余篇，后通过一定的标准及评估剔除了大量不符合需求的文献，最终有54篇优质文献纳入了作者的研究范围，后作者借鉴前人的编码思路和CIS方法进行了数据提取和信息编码。

The author conducted a comprehensive search of Chinese and English literature related to generative AI data security, covering various large, medium, and English databases. More than 3100 articles were retrieved, and a large number of articles that did not meet the requirements were excluded through certain standards and evaluations. Finally, 54 high-quality articles were included in the author's research scope. The author drew on previous coding ideas and CIS methods for data extraction and information coding.

对于结论的检验，作者使用了三种方式来保证研究结论具备较好的信效度，分别是借鉴前人关于理论饱和度检验标准的研究、EBL文献质量评估和专家评判法，通过综合上述三种检验方式，作者的结论具有良好的信效度。

For the verification of the conclusion, the author used three methods to ensure that the research conclusion has good reliability and validity, namely drawing on previous research on theoretical saturation testing standards, EBL literature quality evaluation, and expert evaluation methods. By integrating the above three testing methods, the author's conclusion has good reliability and validity.

4 知识补充（Knowledge supplement）

什么是信效度？

What is reliability and validity?

信度和效度是优良的测量工具必备的条件，是评估所测量数据的可靠性和有效性的基本尺度。只有保证测量工具的信度和效度，才有可能获得可靠、正确的数据。信度，即可靠性或一致性，指的是测量结果经得起重复检验，即测量工具能否稳定地测量到它想要测量的数据。效度，即切实性，指的是测量工具确实能够测出其所要测量的内容。

Reliability and validity are essential conditions for excellent measurement tools, and are the basic scales for evaluating the reliability and effectiveness of the measured data. Only by ensuring the reliability and validity of measurement tools can reliable and accurate data be obtained. Reliability or consistency refers to the ability of a measurement tool to consistently measure the data it wants to measure, meaning that the measurement results can withstand repeated testing. Validity, also known as practicality, refers to the ability of a measuring tool to accurately measure the content it is intended to measure.

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