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This working paper tests whether India's Consumer Protection Act, 2019, can handle harms from defective AI, such as biased outputs, psychological harm, and loss of control. Its central finding is that the Act's technology-neutral definitions may reach AI incidents, but the law assumes discrete manufacturers, sellers, and service providers, and it struggles with causation when AI failures stem from design choices and with liability spread across data providers, model developers, deployers, and users. For AI readers, the practical takeaway is that liability exposure in consumer-facing AI depends on how a product's value chain is structured and documented, not only on the model itself.
Sources coveringarXiv, Fortune, Quantum Frontiers, Interconnects
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

AI and Consumer Rights in India Working Paper

arXiv2 min read

arXiv:2608.12863v2 Announce Type: replace Abstract: 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.

Abstract: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.

Artificial Intelligence (cs.AI)

arXiv:2608.12863 [cs.AI]

(or arXiv:2608.12863v2 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2608.12863 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 263 words

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