Responsible Artificial Intelligence Management in Mechatronic Systems for the Automotive Industry: Ethics, Transparency, and Governance

Țîţu Aurel Mihail (), Bâlc Emanuel () and Bâlc Daniel ()
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Țîţu Aurel Mihail: Lucian Blaga University of Sibiu, Sibiu, Romania
Bâlc Emanuel: Lucian Blaga University of Sibiu, Sibiu, Romania
Bâlc Daniel: National University of Science and Technology POLITEHNICA Bucharest, Bucharest, Romania

Proceedings of the International Conference on Business Excellence, 2025, vol. 19, issue 1, 2213-2223

Abstract: The swift growth of artificial intelligence (AI) in the automotive sector has majorly impacted the evolution of mechatronic systems in which vehicles upgrade performance, safety, and automation. This research explores the influence of responsible АI management on the effectiveness and dependability of mechatronic systems by reviewing transparency, ethics governance, and regulatory obedience. This study will look further into the improvements made in modern vehicles with AI technologies, which include by-wire systems, AI-based driver monitoring, and autonomous navigation technologies, and indicate the challenges these face during the large-scale implementation process. Previous academic literature has carefully reviewed the enormous advantages of AI for automotive mechаtronics while it has also brought up a few outstanding concerns such as opaque algorithms, lack of standardized governance frameworks, and the necessity of explainability. The study is based on a mixed-method approach comprising case study analysis, regulatory document review, and performance data comparison to evaluate the impacts of AI integration on vehicle efficiency and accident prevention. Results indicate that AI-aided mechаtronic systems lead to a 6-8% cut in fuel consumption, vehicle weight decreases by 22%, and an overall driver fatigue-induced accident rate down by 17%. To add, this research reiterates the point that user trust is massively enhanced by the existence of Explainable AI models which have an acceptance rating at 91% versus 43% for Black-Box models. Thus, the paper lays down a suggestion for standardizing AI audit frameworks and calls for the implementation of mandatory AI certification and transparency protocols that would be of interest to stakeholders and implementers in the automotive industry, the public sphere, and the research community who can use the results to ensure the ethical deployment of AI-driven technologies for safe and efficient mobility solutions.

Keywords: artificial intelligence; mechatronic systems; automotive industry; responsible AI management; ethical governance; transparency; regulatory compliance (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:19:y:2025:i:1:p:2213-2223:n:1026

DOI: 10.2478/picbe-2025-0171

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