印度的人工智能与消费者权利工作文件
AI and Consumer Rights in India Working Paper
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中文总结 AI 辅助
本工作文件研究印度2019年《消费者保护法》应对AI产品服务损害及责任分配的情况，指出其存在因果证明难、责任类别不匹配等缺口，需明确领域重叠以完善AI责任执行。
中文摘要 AI 辅助
随着人工智能（AI）系统在面向消费者的应用中不断普及，与AI相关的损害责任问题仍未得到解决。本工作文件探讨印度2019年《消费者保护法》是否充分应对了有缺陷的AI产品和服务造成的损害，以及是否在AI价值链中按比例分配了责任。该法案对产品责任、损害和缺陷的宽泛定义似乎与技术无关，可能适用于AI相关事件，包括人身伤害、心理损害、有偏差的输出以及控制权丧失。然而，仍存在重大缺口：证明AI缺陷与消费者损害之间的因果关系是一项技术挑战，因为AI故障通常源于设计选择而非离散缺陷；此外，该法案的框架假设制造商、销售商和服务提供商的角色明确，而AI价值链涉及数据提供者、模型开发者、部署者和使用者之间重叠的责任，无法整齐地映射到这些类别，当前的责任框架缺乏按比例分配的机制来有效应对复杂的多利益相关方AI损害，尽管该法案可能涵盖AI实体，但执行需要明确特定领域的重叠问题。
英文摘要
As AI systems proliferate in consumer facing applications, questions about liability for AI related harms remain unresolved. This working paper examines whether India's Consumer Protection Act, 2019, adequately addresses harm caused by defective AI products and services, and whether it proportionately allocates liability across the AI value chain. The Act's broad definitions of product liability, harm, and deficiency appear technology agnostic and potentially applicable to AI related incidents including personal injury, psychological harm, biased outputs, and loss of control. However, significant gaps remain. Proving causation between AI defects and consumer harm presents a technical challenge, as AI failures often stem from design choices rather than discrete defects. Additionally, the Act's framework assumes distinct roles for manufacturers, sellers, and service providers, yet the AI value chain involves overlapping responsibilities among data providers, model developers, deployers, and users that do not neatly map to these categories. Current liability frameworks lack proportionate mechanisms to effectively address complex, multistakeholder AI harms. While the Act may cover AI entities, enforcement requires clarification on sector specific overlaps.
