[论文解读] Ethical AI in Retail: Consumer Privacy and Fairness

Anthonette Adanyin|arXiv (Cornell University)|Oct 20, 2024

Ethics and Social Impacts of AI被引用 4

一句话总结

本研究探讨了人工智能驱动零售中的伦理挑战，重点关注消费者隐私与公平性。通过对300名电子商务用户的调查发现，消费者对数据收集和算法偏见高度关注，结论认为透明度、定期偏见审计以及强有力的数据保护措施对于在不牺牲竞争力的前提下实现人工智能的伦理部署至关重要。

ABSTRACT

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.

研究动机与目标

• 分析人工智能在零售领域应用带来的伦理挑战，特别是与消费者隐私和公平性相关的问题。
• 识别零售商在保持竞争力的同时实施伦理人工智能的策略。
• 考察消费者对人工智能驱动零售平台数据收集实践和算法偏见的认知。
• 基于实证消费者反馈，提出可操作的伦理人工智能实施建议。

提出的方法

• 采用描述性调查设计，从主要电子商务平台收集300名受访者的数据。
• 使用描述性统计方法（包括百分比和平均分）分析数据，以评估消费者态度和关注点。
• 评估消费者对零售商使用的人工智能系统在数据隐私、透明度和公平性方面的感知。
• 通过调查回复中关于信任与数据管理的题项分析，识别关键的伦理实践。
• 基于关于透明度、偏见审计和消费者反馈整合的综合发现，提出建议。

实验结果

研究问题

• RQ1 消费者如何看待人工智能驱动零售应用对其个人数据的收集与管理？
• RQ2 消费者在多大程度上认为零售领域的人工智能系统对待他们公平？哪些因素导致了感知到的偏见？
• RQ3 零售商可采取哪些伦理人工智能实践，以在确保数据隐私与公平性的同时保持竞争力？
• RQ4 如何将透明度和消费者反馈整合到零售领域的人工智能开发生命周期中？

主要发现

• 大多数消费者对人工智能驱动零售应用收集的个人数据量表示高度担忧。
• 许多消费者对其数据管理方式缺乏信任，表明在感知数据保护方面存在显著差距。
• 相当大比例的受访者认为人工智能系统未能公平对待消费者，凸显了对算法偏见的广泛担忧。
• 尽管存在伦理顾虑，消费者仍认识到，若负责任地实施，人工智能可提升业务效率与竞争力。
• 数据隐私与透明度被确定为亟需改进的关键领域，消费者强烈呼吁实施更严格的数据保护协议。
• 定期审计以检测并纠正偏见，以及提升人工智能流程的透明度，被视为建立消费者信任的关键要素。