From Human Negligence to Machine Logic: Rethinking Causation and Liability in AVs under Indian Law

The shift to human driverless decision-making with autonomous vehicles (AVs) is posing difficulties to traditional law in India concerning liability. Traditional negligence relies on human fault and a clear nexus between cause and effect. With the use of complex systems involving software, data, and machine learning, the cause of the harm will not solely be human intervention, but rather the effect of a multiplicity of variables working together. This paper's central assertion is that the cause issue in AV cases is less about problems in the available evidence and more about the inappropriateness of the concept itself within the legal framework. Existing rules in this regard do not prove sufficient as they tend to imply clearly demarcated causes, a phenomenon that is rare in an autonomous system. This issue is exacerbated by laws like the Motor Vehicles Act, 1988, the Consumer Protection Act, 2019, and the Bharatiya Sakshya Adhiniyam, 2023, that emphasize fault based liability and are structured around placing the burden of proof on the victim. The paper also has a comparative analysis of various approaches followed by nations such as the United Kingdom, the United States of America, and Germany, which have been shifting the burden from the driver to the manufacturer and the system. Therefore, based on these comparisons, the paper concludes that India must move toward new methods such as enterprise liability, compensation based on insurance, and presumptive liability. The paper concludes that as human intervention takes a step back and is replaced by technology, the law of liability also has to reformulate itself toward a system based framework.