Abstract

The integration of Artificial Intelligence (AI) into engineering decision-making has introduced unprecedented opportunities for efficiency, optimization, and innovation. However, it also raises critical ethical challenges concerning accountability, transparency, fairness, and safety. This paper explores the ethical considerations inherent in AI-assisted engineering decisions, emphasizing the responsibilities of engineers, developers, and organizations in deploying AI systems. Key concerns include bias in training data, explainability of algorithmic recommendations, potential safety risks in safety-critical applications, and the societal impacts of automation. The paper proposes a framework for ethical AI deployment in engineering, incorporating principles of transparency, traceability, risk assessment, and stakeholder engagement. Case studies in civil, mechanical, and aerospace engineering highlight practical scenarios where ethical lapses can lead to adverse outcomes, emphasizing the importance of governance structures, validation protocols, and continuous monitoring. By integrating ethical guidelines with technical AI development, organizations can foster trust, ensure regulatory compliance, and enhance decision-making quality. The findings underscore that ethical considerations are not ancillary but central to responsible AI adoption in engineering, promoting sustainable and socially responsible technological advancement.