Using Artificial Intelligence to Assist
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The introduction of ChatGPT 3.5 in November 2022 has led to a rethinking of the process used by engineers and scientists to produce technical documents [1]. Since that release, much debate has arisen on whether, when, and how much engineers and scientists should use artificial intelligence (AI) to assist in their writing. This website presents multiple perspectives on these questions.
Case for AI-Assisted Writing. Many respected engineers and scientists have begun experimenting with artificial intelligence both to improve specific aspects of their writing and to streamline the writing process [2]. While few professionals are arguing for using AI to write all documents or even to use AI to perform all major steps of the technical writing process (shown in Figure 1), many are finding success in having AI assist on portions of the process. For instance, many engineers and scientists who are not writing in their native language find AI extremely helpful in revising documents to connect ideas and to adhere to the many rules of grammar, punctuation, and usage. 
Figure 1. Three important stages of the writing process: researching, drafting, and revising.
As depicted in the analogy of Figure 2, AI is not only helping engineers and scientists write a significant slice of current documents but also helping write other documents that would have been too large or difficult to take on with a traditional approach.
Figure 2. Analogy that AI is assisting not only on a large slice of documents but also helping write new types of documents that would otherwise be too time-consuming to attempt.
Case Against AI-Assisted Writing. Writing done with artificial intelligence has distinct weaknesses. As indicated on the page of telltale signs of AI writing, the biggest weakness for engineers and scientists is a lack of technical precision. Writing generated by AI can be "erroneous, misleading, or entirely irrelevant" [3]. In general, the more technical precision that is needed in a document, the less effective that AI is at drafting the document. The imprecision of AI writing stands as a counterargument for using it to write about technical content.
Another counterargument about AI-assisted writing concerns AI not properly crediting sources. Not crediting a source can damage one's reputation in the professional community. Still another counterargument concerns engineering and science students. This argument is that students should not use AI for technical writing assignments because doing so allows students to bypass the learning of the process for writing technical documents--a process that many of those students do not yet understand [2]. |
 Figure 2. Order of adopters for an innovation [5] such as using AI to assist in writing. When faced with whether to adopt an innovation, people will take different stances.
The Diffusion of AI-Assisted Writing. Since November 2022, AI-assisted writing has begun diffusing into engineering and scientific documents. The theory for the diffusion of innovation helps explain the adoption of and resistance to this new idea [4]. As depicted in Figure 2, when an innovation becomes available, a group called "early adopters" experiments with the innovation and, if they find enough value, they will adopt it. Already, many engineers and scientists have adopted AI to assist in researching, drafting, or revising some of their documents.
On the other end of the curve, because writing with AI threatens deeply established practices, this innovation has encountered significant resistance [5]. Many not only have publicly decried the innovation but are blocking its use in their institutions, departments, or courses. While some engineers, scientists, and instructors of technical writing have become outspoken adopters or resistors of AI for writing technical documents, most are remaining quiet. Many are watching for what early adopters will do (early majority), while others are waiting to follow what most people do (late majority).
For this middle group, an important question is deciding when using AI to help write documents is appropriate. This answer is not simple. Much depends on the content, audience, purpose, and occasion of the document. For instance, in many cases, using AI as an assistant is fine for specific stages of the writing process, but not for others. For instance, some argue that AI is not appropriate for drafting new content when you are still learning about the content. In such a case, using AI to draft deprives authors of the insights that naturally arise during the drafting stage when authors convert their thoughts into words on paper. Purpose of This Website. The purpose of this website is to provide insights about using AI to assist in technical writing. One goal is to help engineers and scientists (and teachers of technical writing) decide when or even whether to adopt (or teach) this innovation.
At the site, one webpage highlights examples of AI-assisted writing by professional engineers and scientists. Another webpage discusses stylistic and grammatical signs for when a document is written with AI. Knowing the style of AI writing is valuable for multiple reasons, one being to craft AI prompts that mitigate its weaknesses. One forthcoming page presents results from surveys of students and faculty on their perspectives about using AI to assist in technical writing. Still another forthcoming page is an experiment to determine how much time using AI would actually save students performing a common writing assignment in a technical writing course. An assumption of this experiment is that the student seeks to create an excellent assignment. 
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Photo by pxibay.com (CC0 1.0)
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Photo by PickPic
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Faculty Quotations about Students Using AI
for Technical Writing Assignments 
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Calculation of Time Saved with Using AI for a Common
Assignment in Technical Writing (Forthcoming) 
Isabelle Grosjean ZA, CC BY-SA 3.0
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References
- Berber Jin and Belle Lin, “OpenAI Unveils GPT-5, Its Latest and Most Powerful Model, After Two-Year Wait,” Wall Street Journal (7 August 2025), p. A-1.
- Catherine Berdanier and Michael Alley, "We still need to teach engineers to write in the era of ChatGPT," Journal of Engineering Education, vol 112, issue 3 (July 2023), pp. 583-586.
- Qinjin Jia, Jialin Cui, Haoze Du, Parvez Rashid, Ruijie Xi, Ruochi Li, Edward Gehringer, “LLM-generated Feedback in Real Classes and Beyond: Perspectives from Students and Instructors,” Proceedings of the 17th International Conference on Educational Data Mining, (Atlanta, Georgia: International Educational Data Mining Society, July 2024), pages 862–867.
- Everett M. Rogers, The Diffusion of Innovation, 5th edition (Free Presee, 16 August 2003).
- Jessica Grose, "These College Professors Will Not Bow Down to AI," opinion, The New York Times (6 August 2025).
*AI was not used to research, draft, or revise this webpage.