AI购物代理中的人机协同决策对消费者的影响研究

A Study on the Impact of Human-Machine Collaborative Decision-Making in AI Shopping Agents on Consumers

摘要: 随着生成式人工智能技术的快速发展，AI购物代理正从被动工具演变为具备自主决策能力的协同伙伴，推动消费决策模式从“人找货”向“货找人”转变。本文聚焦于AI购物代理中的人机协同决策机制及其对消费者的双重影响。研究首先界定了AI购物代理与人机协同决策的核心概念，进而构建了由意图层、协商层与执行层构成的三阶段运作模型，系统阐释了AI购物代理中人机协同决策的动态过程。其次，本文指出AI购物代理对消费者具有显著积极影响与潜在风险。在此基础上，本文从强化用户主体性、推进算法革新与完善制度保障三个维度，提出优化人机协同决策体验的路径，旨在为构建负责任、可持续的AI购物代理生态系统提供理论参考与实践启示。

Abstract: With the rapid advancement of generative AI technology, AI shopping agents are evolving from passive tools into collaborative partners with autonomous decision-making capabilities, driving a shift in consumer decision-making from “people finding products” to “products finding people”. This paper focuses on the human-machine collaborative decision-making mechanism within AI shopping agents and its dual impact on consumers. The study first defines the core concepts of AI shopping agents and human-machine collaborative decision-making, then constructs a three-stage operational model comprising the intention layer, negotiation layer, and execution layer to systematically elucidate the dynamic process of human-machine collaborative decision-making in AI shopping agents. Second, the paper identifies both significant positive impacts and potential risks of AI shopping agents for consumers. Building on this, it proposes pathways to optimize the human-machine collaborative decision-making experience across three dimensions: strengthening user agency, advancing algorithmic innovation, and improving institutional safeguards. This aims to provide theoretical references and practical insights for constructing a responsible and sustainable AI shopping agent ecosystem.