2026 ASEE Annual Conference & Exposition

Artificial intelligence (AI) is a rapidly evolving technology seeing widespread use across education and engineering practice. For example, students are using AI to assist with learning, professors are using it to help develop learning activities, and structural engineers are using it to create conceptual designs for building projects. There are, however, concerns that come with the implementation of AI, such as the bias it can perpetuate through its training data or the ethics of using AI to supplement one’s own writing and creation processes. As the ubiquity of AI has increased, professors are talking about it more in their courses, with new courses being developed to teach engineering students how to create and use AI models to solve technical problems. Professors must now provide students with documentation clearly outlining the acceptable use of generative AI tools in their courses. It is imperative that students be equipped to judge for themselves what is an appropriate use of AI as they go into engineering practice. This paper will provide an overview of how AI is being used in structural engineering practice and the concerns that students and engineers should be aware of when using AI in practice. The paper will describe a learning activity employed in an introductory structural engineering course to support students’ development of ethical judgement around the use of AI in structural engineering practice. Finally, a qualitative analysis of student artifacts and feedback will be done to identify themes in students’ perceptions around the ethical use of AI in structural engineering practice and to assess how the learning activities contributed to these perceptions. Overall, students found the activity to be valuable, noting that it improved their awareness of AI applications and potential issues. The results highlighted the importance of educators emphasizing that students must change their mindset and interactions with AI throughout their higher education and engineering apprenticeships, transitioning from AI being the “expert” that can assist them in their learning, to them being the expert that can check the technical accuracy of AI output.