2026 ASEE Annual Conference & Exposition

Exploring How AI Engineers Perceive and Develop Translational Ethical Competency: RFE-Funded Project Updates

Presented at NSF Grantees Poster Session II

As AI technologies become increasingly embedded in educational and professional contexts, there is an urgent need to prepare engineering students and practitioners to engage critically with the ethical dimensions of their work. The project responds to this need by examining how ethical principles and reasoning about these principles can be systematically integrated into the daily routines of AI system design, moving beyond the philosophical studies of ethics towards practice-oriented understanding. For this purpose, this project investigates how to define and cultivate translational ethical competency (TEC) among practical AI engineers.

It builds upon a series of publications that together develop the conceptual foundation of TEC. Initially, we published a conceptual article, which argued for integrating policy perspective into the ethical governance of AI, positioning policy as a bridge that connects the abstract ethical principles to institutional and technical implementation of AI ethics. Later on, we demonstrated that ethics education remains peripheral in the computing curriculum worldwide, with only one-third of the programs requiring ethics courses. Such a gap in the computing curriculum hinders students’ ability to develop practical ethical competencies such as TEC that enable them to work competently and responsibly in professional settings. They also underscore the importance of studying TEC among practicing AI engineers and integrating those insights into computing education. Finally, our most recent work established the conceptual model of TEC by emphasizing the ”principle-to-practice” gap in AI Ethics, and introduced elicitation interview as method to explore how engineers navigate the ethical challenges in design. This research also introduced the results of pilot study that was conducted to validate the research instruments for eliciting the processes in which practicing AI engineers translate ethics principles into concrete AI systems designs. Collectively, these publications were used to situate TEC as a vital link between ethics, policy and engineering practice.

Overall, this project aims to address three objectives (our present work is addressing the first objective): 1) to understand the processes AI engineers follow when translating ethical principles into technical design decisions, 2) to identify the competencies that are essential for effective translation of ethical principles into responsible engineering practice and 3) to explore the critical moments and learning pathways through which AI engineers develop and refine these translational competencies in real-world contexts.

By articulating and empirically exploring the notion of TEC, this project contributes to the emerging discourse on responsible AI engineering. The findings are expected to inform the design of educational models and training programs that embed ethics as an integral, actionable component of engineering practice, thus preparing future engineers to translate abstract ethical values into tangible, responsible design decisions.

Authors

Emad Ali Virginia Polytechnic Institute and State University [biography]

Emad Ali is currently pursuing a PhD in Engineering Education at Virginia Tech. His research focuses on the integration of artificial intelligence in engineering education, with a particular emphasis on its ethical implications. He holds a Master's degree in Electrical Engineering, specializing in Embedded Systems, from the Information Technology University of the Punjab (ITU Lahore), as well as a Bachelor's degree in Avionics Engineering from the National University of Sciences and Technology (NUST) in Islamabad, Pakistan. Through his work, he aims to contribute to the advancement of educational practices in engineering by addressing both the opportunities and challenges presented by emerging technologies.
Dr. Qin Zhu http://orcid.org/0000-0002-6673-1901 Virginia Polytechnic Institute and State University [biography]

Dr. Zhu is an Associate Professor in the Department of Engineering Education at Virginia Tech, with additional affiliations in the Department of Science, Technology & Society, the Department of Philosophy, the Center for Human-Computer Interaction, and the Center for Future Workplaces and Practices. He serves as Associate Editor for Science and Engineering Ethics, Studies in Engineering Education, and Editor for International Perspectives at the Online Ethics Center for Engineering and Science. Additionally, Dr. Zhu is a member of the Board of Directors for the Association for Practical and Professional Ethics (APPE). His research investigates how culture both shapes and is shaped by the formation of socially responsible engineers; the ethical design and deployment of emerging technologies such as AI, robotics, and quantum computing; and innovative approaches to teaching responsible AI and robot literacy in K–12 education. He directs the LANCSET (Laboratory for the Advancement of Normative, Cultural, and Societal Engagement with Emerging Technologies) Research Lab, where further information about his projects and publications is available.
Dr. Dayoung Kim Virginia Polytechnic Institute and State University [biography]

Dr. Dayoung Kim is an Assistant Professor in the Department of Engineering Education (College of Engineering) at Virginia Tech and a Director of the LABoratory for Innovative and REsponsible ENgineering workforce (LAB-IREEN). She also serves as an Executive Committee Member and Affiliate Faculty of the Center for Future Work Places and Practices (CFWPP). Her Engineering Practice research examines the practice of engineers across a range of employment settings, including business organizations – from startups to large, established firms – and government agencies. Building on insights from this work, her Engineering Workforce Development research focuses on developing the future engineering workforce capable of contributing innovatively and responsibly within their own contexts. Across her research, teaching, and service, she aims to bridge academia, industry, and government by translating insights from engineering practice into scalable systems for education, workforce development, and science and technology policy. She received her Ph.D. in Engineering Education from Purdue University and her B.S. and M.S. in Chemical Engineering from Yonsei University and Purdue University, respectively. She was the 2022 Christine Mirzayan Science & Technology Policy Graduate Fellow at the National Academies of Sciences, Engineering, and Medicine (NASEM).
Hoda Eldardiry http://orcid.org/0000-0002-9712-6667 Virginia Polytechnic Institute and State University [biography]

Eldardiry is an Associate Professor of Computer Science and director of the Machine Learning Laboratory at Virginia Tech. Her research centers around machine learning and AI ethics and education.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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