arXiv:2410.15369cs.CYcs.AI2024-10被引 43

零售业AI应用需平衡隐私与公平,提升透明度与可信度。

Ethical AI in Retail: Consumer Privacy and Fairness

  • 通过300份问卷调研消费者对AI数据收集的担忧
  • 超半数消费者认为AI系统存在偏见,不公平现象普遍
  • 建议加强透明度、定期审计与用户反馈机制

人工智能在零售业的广泛应用推动了个性化服务与运营效率提升,但也引发消费者隐私保护与算法公平性的伦理争议。本研究采用描述性调查设计,从主要电商平台收集300名受访者数据,通过描述性统计分析发现:多数消费者对AI应用收集个人数据的规模表示高度担忧,且普遍缺乏对数据管理的信任;同时,大多数受访者认为现有AI系统未能公平对待所有消费者,算法偏见问题突出。研究还表明,在不牺牲隐私与公平的前提下,企业仍可通过合规方式实现竞争力提升。研究强调,数据隐私与透明度是关键改进领域,亟需建立更严格的数据保护机制并持续监督AI系统运行。结论指出,零售商应优先保障透明性、公平性与数据安全,具体建议包括增强流程透明、定期开展偏差审计、融入消费者反馈,并强化数据隐私保护。

原文摘要 · Abstract (English)

The adoption of artificial intelligence (AI) in retail has significantly transformed the industry, enabling more personalized services and efficient operations. However, the rapid implementation of AI technologies raises ethical concerns, particularly regarding consumer privacy and fairness. This study aims to analyze the ethical challenges of AI applications in retail, explore ways retailers can implement AI technologies ethically while remaining competitive, and provide recommendations on ethical AI practices. A descriptive survey design was used to collect data from 300 respondents across major e-commerce platforms. Data were analyzed using descriptive statistics, including percentages and mean scores. Findings shows a high level of concerns among consumers regarding the amount of personal data collected by AI-driven retail applications, with many expressing a lack of trust in how their data is managed. Also, fairness is another major issue, as a majority believe AI systems do not treat consumers equally, raising concerns about algorithmic bias. It was also found that AI can enhance business competitiveness and efficiency without compromising ethical principles, such as data privacy and fairness. Data privacy and transparency were highlighted as critical areas where retailers need to focus their efforts, indicating a strong demand for stricter data protection protocols and ongoing scrutiny of AI systems. The study concludes that retailers must prioritize transparency, fairness, and data protection when deploying AI systems. The study recommends ensuring transparency in AI processes, conducting regular audits to address biases, incorporating consumer feedback in AI development, and emphasizing consumer data privacy.

AI伦理消费者隐私算法公平零售科技

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