Governing AI Outcomes in Civil and Construction Engineering Education: Toward Trustworthy and Ethical Implementation

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

Artificial intelligence (AI) is transforming civil and construction engineering (CCE) education. CCE students must develop both AI technical proficiency and ethical awareness, ensuring that AI tools reflect the varied experiences of project clients. Integrating ethical AI instruction supports the formation of students’ professional identity by encouraging them to internalize values of responsibility, integrity, and equity in future practice. Adopting a narrative literature review, this paper examines the ethical concerns surrounding AI in CCE education, implications of existing regulations, and the need for institution-specific risk mitigation policies. The synthesis of the literature indicates that while integrating AI into CCE education may enhance learning experiences and personalized instruction, it also raises key ethical risks, such as algorithmic bias, privacy concerns, lack of transparency, threats to academic integrity, and digital inequity. As such, we also offer guidelines for responsible AI use in educational settings and propose an output governance framework and practical recommendations for educators and institutions, including performing regular ethical and algorithmic audits of AI tools, involving students in technology deployment decisions, and providing faculty development on digital ethics. By detailing actionable strategies, formalizing human-in-the-loop validation workflows, and preserving chains of provenance for educational metrics, these recommendations aim to align AI innovation with the core values of engineering education, i.e., integrity, equity, and public welfare.