McCullough, C. L., & Dalton, M. (2025, March), Generative AI in Engineering: Tool or Trouble?  Paper presented at 2025 ASEE Southeast Conference , Mississippi State University, Mississippi. 10.18260/1-2--54172

\bibitem{asee_peer_54172}
  McCullough, C. L., \& Dalton, M. (2025, March), \emph{Generative AI in Engineering: Tool or Trouble?}
  Paper presented at 2025 ASEE Southeast Conference , Mississippi State University, Mississippi.
  10.18260/1-2--54172

Claire Lynne McCullough PE and Mike Dalton.  "Generative AI in Engineering: Tool or Trouble?".  2025 ASEE Southeast Conference , Mississippi State University, Mississippi, 2025, March.  ASEE Conferences, 2025.  https://peer.asee.org/54172 Internet.  19 May, 2025

\bibitem{asee_peer_54172}
  Claire Lynne McCullough PE and Mike Dalton.
  "Generative AI in Engineering: Tool or Trouble?".
  \emph{2025 ASEE Southeast Conference , Mississippi State University, Mississippi, 2025, March}.
  ASEE Conferences, 2025.
  https://peer.asee.org/54172 Internet.  19 May, 2025

@INPROCEEDINGS{asee_peer_54172
author = "Claire Lynne McCullough PE and Mike Dalton"
title = "Generative AI in Engineering: Tool or Trouble?"
booktitle = "2025 ASEE Southeast Conference "
year = "2025"
month = "March"
address = "Mississippi State University, Mississippi"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/54172}
number = {10.18260/1-2--54172}
}

TY  - CPAPER
AB  - The publicity surrounding generative AI and its possible uses has led to much excitement and speculation about the role that these tools can play in technical education and in the practice of engineering and computer science. Although ChatGPT is, perhaps, the version most in the news, this is only one of many generative AI applications that could potentially be applied to our professions. Other potential tools include other large, proprietary LLMs (Large Language Models) such as Claude and Gemini; research tools such as Quivr, ExplainPaper and Scite; coding tools like GitHub Copilot and Codeium;  and  tools specific to engineering and technical disciplines. Some possible uses that have been hypothesized for professional use are brainstorming, report writing, proposal composition, authoring training materials and creation of PowerPoint presentations, as well as technical aspects such as code creation, fault detection, circuit layout, and large system design. For students, these uses could include creation of study guides, generation of practice problems and solutions, and idea creation. Some professors are even experimenting with using generative AI to grade and provide feedback on student work. While some of these uses can provide potential benefits to students and professionals, ethical issues must also be addressed: AI “hallucinations,” over-reliance on the tools, changing definitions of plagiarism, copyright issues, and environmental impacts of the technology.

This paper will provide an overview of a selection of the existing tools and their potential uses, an examination of the caveats associated with each, and a beginning discussion of the ethical considerations that must be addressed.

AU  - Claire Lynne McCullough PE
AU  - Mike Dalton
CY  - Mississippi State University, Mississippi
DA  - 2025/03/09
PB  - ASEE Conferences
TI  - Generative AI in Engineering: Tool or Trouble?
UR  - https://peer.asee.org/54172
DO  - 10.18260/1-2--54172
ER  -