AHP-TOPSIS视角下电商AIGC合规风险差异化评估

Differentiated Assessment of Compliance Risks in E-Commerce AIGC Applications from the Perspective of AHP-TOPSIS

摘要: AIGC已经渗透到电商行业的各个场景，然而不同类型电商企业的AIGC合规风险差别却很大，目前虽然已有相对完备的治理模式，但难以适应电商的特定场景，致使风险防控缺乏针对性和专业性。因此，我们深入讨论电商行业内AIGC合规风险不均、治理模式单一的问题，建立量化评估方法，发现差异、明确分类排序治理先后级。本研究从数据安全风险、内容与算法风险、知识产权风险、商业与监管风险等方面分析，选取了16个具体指标，应用AHP、TOPSIS法建立一套电商AIGC应用的合规风险差异性量化评估模型。该模型可用于电商不同场景及不同类型企业的AIGC合规风险等级排序，还可与权重分析相关内容，识别产生主要风险因素，能够为电商AIGC实施分类分级治理、监管和企业决策的正确性、精准性提供更好的途径方法建议。

Abstract: AIGC has permeated various scenarios in the e-commerce industry; however, there are significant disparities in AIGC compliance risks among different types of e-commerce enterprises. While relatively comprehensive governance frameworks are currently in place, they fail to adapt to the specific scenarios of e-commerce, resulting in a lack of targeting and professionalism in risk prevention and control. Therefore, this study delves into the issues of the uneven distribution of AIGC compliance risks and a one-size-fits-all governance model within the e-commerce industry, establishes a quantitative evaluation method to identify disparities, and clarifies priorities for classified and hierarchical governance through sorting. From the perspectives of data security risks, content and algorithm risks, intellectual property risks, and commercial and regulatory risks, this research selects 16 specific indicators and employs the AHP and TOPSIS methods to construct a differentiated quantitative evaluation model for compliance risks in e-commerce AIGC applications. This model can not only be used to rank the AIGC compliance risk levels across different e-commerce scenarios and enterprise types but also identify key risk factors through weight analysis, thereby providing more effective methodological support for the implementation of classified and hierarchical governance, supervision, and the scientificity and accuracy of enterprise decision-making regarding e-commerce AIGC.