将人工智能伦理纳入计算机视觉技术的设计和使用,以了解消费者行为

IF 4.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
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引用次数: 0

摘要

人工智能(AI)技术正变得越来越复杂,显示出深入理解和预测消费者行为的潜力,从而促进零售业的发展;然而,迄今为止,对其部署所依据的零售业敏感考虑因素的探讨还很少。本文探讨了人工智能技术在零售业的应用,重点关注其通过防止固有的重大道德风险(如偏见传播和系统缺乏可解释性)来增强决策过程的潜力。本研究借鉴近期有关人工智能伦理的文献,提出了在零售业设计和开发可信、无偏见、更可解释的人工智能系统的方法论路径。该框架以欧洲(欧盟)人工智能伦理原则为基础,并针对零售应用的具体细微差别。为此,我们首先研究了 VRAI 框架(一种用于分析购物者互动、人员统计和重新识别的深度学习模型),以强调人工智能操作透明度和公平性的迫切需要。其次,本文提出了将高级伦理准则融入实际环境的可行策略,特别是减少导致人工智能系统出现不公平结果的偏见,并提高其可解释性。通过这样做,本文旨在展示将人工智能伦理要求嵌入人工智能实践和计算机视觉技术的关键附加值,从而在零售领域真正促进技术上和伦理上健全的人工智能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Embedding AI ethics into the design and use of computer vision technology for consumer’s behaviour understanding

Artificial Intelligence (AI) techniques are becoming more and more sophisticated showing the potential to deeply understand and predict consumer behaviour in a way to boost the retail sector; however, retail-sensitive considerations underpinning their deployment have been poorly explored to date. This paper explores the application of AI technologies in the retail sector, focusing on their potential to enhance decision-making processes by preventing major ethical risks inherent to them, such as the propagation of bias and systems’ lack of explainability. Drawing on recent literature on AI ethics, this study proposes a methodological path for the design and the development of trustworthy, unbiased, and more explainable AI systems in the retail sector. Such framework grounds on European (EU) AI ethics principles and addresses the specific nuances of retail applications. To do this, we first examine the VRAI framework, a deep learning model used to analyse shopper interactions, people counting and re-identification, to highlight the critical need for transparency and fairness in AI operations. Second, the paper proposes actionable strategies for integrating high-level ethical guidelines into practical settings, and particularly, to mitigate biases leading to unfair outcomes in AI systems and improve their explainability. By doing so, the paper aims to show the key added value of embedding AI ethics requirements into AI practices and computer vision technology to truly promote technically and ethically robust AI in the retail domain.

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来源期刊
Computer Vision and Image Understanding
Computer Vision and Image Understanding 工程技术-工程:电子与电气
CiteScore
7.80
自引率
4.40%
发文量
112
审稿时长
79 days
期刊介绍: The central focus of this journal is the computer analysis of pictorial information. Computer Vision and Image Understanding publishes papers covering all aspects of image analysis from the low-level, iconic processes of early vision to the high-level, symbolic processes of recognition and interpretation. A wide range of topics in the image understanding area is covered, including papers offering insights that differ from predominant views. Research Areas Include: • Theory • Early vision • Data structures and representations • Shape • Range • Motion • Matching and recognition • Architecture and languages • Vision systems
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