Authors - Atharva Patil, Dibyanshu Singh, Tanish Dadarkar, Suman Madan Abstract - The use of artificial intelligence in the automotive system presents legal, ethical, and societal issues such as accountability, safety, human trust, and data privacy. In the case of system failure, explainable behaviour, necessitating the complexity and opacity of AI-driven decision-making. Bias in the training dataset may cause unequal system performance in different traffic environments and road uses, thus the need for representative data and validation. The vast amount of vehicle and data collected raises privacy issues, thus the need for secure data handling and anonymization. Ethical system design should therefore consider fairness, safety, and accountability as primary engineering constraints for responsible AI-enabled vehicle deployment. They deliver safe, more efficient and sustainable vehicles and services. Not only are the vehicles themselves being modernized through the technology, but manufacturing processes and supply chain management on the backend are also changing.
