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Balancing Safety and Innovation: A Manufacturer’s Perspective on AI-Powered Cars in Embedded Systems

Baskaran, Sowdambika LU and Ahmed, Zara LU (2025) INFM10 20251
Department of Informatics
Abstract
AI-powered vehicle systems, including autonomous driving features and advanced driver assistance systems (ADAS), are becoming increasingly integrated into modern automotive development. While these technologies offer benefits such as improved functionality, innovation acceleration, and competitive advantage, they also introduce new challenges. One of the key challenges is maintaining system safety in highly dynamic, embedded environments where AI-based decisions must remain predictable and certifiable. As the role of AI expands in safety-critical systems, manufacturers face growing tension between innovation and safety assurance. This study explores how automotive manufacturers perceive and manage this balance. A qualitative and... (More)
AI-powered vehicle systems, including autonomous driving features and advanced driver assistance systems (ADAS), are becoming increasingly integrated into modern automotive development. While these technologies offer benefits such as improved functionality, innovation acceleration, and competitive advantage, they also introduce new challenges. One of the key challenges is maintaining system safety in highly dynamic, embedded environments where AI-based decisions must remain predictable and certifiable. As the role of AI expands in safety-critical systems, manufacturers face growing tension between innovation and safety assurance. This study explores how automotive manufacturers perceive and manage this balance. A qualitative and interpretive approach was used, with data collected through semistructured interviews with professionals from the automotive AI domain. The study identifies key themes where AI implementation enhances, complicates, or is constrained by safety requirements. In addition, collaboration across regulatory, technical, and ethical domains emerged as a necessary condition for safe and innovative development. The findings highlight the need for proactive risk governance, cross-functional team coordination, and ethical alignment during AI integration. Based on these insights, the study proposes that responsible AI deployment in embedded vehicle systems depends on both organizational structure and sociotechnical adaptability. (Less)
Popular Abstract
Artificial intelligence (AI) is transforming the way cars operate, making them smarter and more independent. But as cars become more automated, ensuring safety remains a top concern. This study explores how vehicle manufacturers view the balance between creating innovative AI-driven systems and maintaining high safety standards. Through interviews with engineers and decision-makers in the automotive industry, we found that manufacturers face several challenges — from ethical concerns to strict regulations. However, they also see exciting opportunities for AI to improve road safety and user experience. By understanding how companies manage these trade-offs, this research sheds light on how we can build smarter, safer vehicles in the future.
Please use this url to cite or link to this publication:
author
Baskaran, Sowdambika LU and Ahmed, Zara LU
supervisor
organization
alternative title
Balancing Safety and Innovation
course
INFM10 20251
year
type
H1 - Master's Degree (One Year)
subject
keywords
AI-powered cars, safety, embedded systems, ethical decision
language
English
id
9200530
date added to LUP
2025-06-17 13:48:18
date last changed
2025-06-17 13:48:18
@misc{9200530,
  abstract     = {{AI-powered vehicle systems, including autonomous driving features and advanced driver assistance systems (ADAS), are becoming increasingly integrated into modern automotive development. While these technologies offer benefits such as improved functionality, innovation acceleration, and competitive advantage, they also introduce new challenges. One of the key challenges is maintaining system safety in highly dynamic, embedded environments where AI-based decisions must remain predictable and certifiable. As the role of AI expands in safety-critical systems, manufacturers face growing tension between innovation and safety assurance. This study explores how automotive manufacturers perceive and manage this balance. A qualitative and interpretive approach was used, with data collected through semistructured interviews with professionals from the automotive AI domain. The study identifies key themes where AI implementation enhances, complicates, or is constrained by safety requirements. In addition, collaboration across regulatory, technical, and ethical domains emerged as a necessary condition for safe and innovative development. The findings highlight the need for proactive risk governance, cross-functional team coordination, and ethical alignment during AI integration. Based on these insights, the study proposes that responsible AI deployment in embedded vehicle systems depends on both organizational structure and sociotechnical adaptability.}},
  author       = {{Baskaran, Sowdambika and Ahmed, Zara}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Balancing Safety and Innovation: A Manufacturer’s Perspective on AI-Powered Cars in Embedded Systems}},
  year         = {{2025}},
}