Dr. Laura Gonzales teaches technical communication at the University of Florida.

In academia, many of the conversations about generative AI focus on surveillance and cheating. If students can have AI generate content for them, how can teachers assess students’ work? In the introductory technical communication course, many traditional assignments focus on teaching students to generate content—the technical documentation assignment, the tutorial, the memo, and the research report (to name a few examples). Instructors teaching the introductory course—or any course where students write technical documents—spend time teaching students the rhetorical moves embedded in these genres, highlighting the value of audience awareness, accessibility, localization, and more. These skills help students write clearly and effectively across a wide range of contexts, whether they choose to go into a technical communication profession or not.  

However, when generative AI comes into the picture, and students can generate instructions, memos, resumes, and more with a few simple prompts, what should technical communication instructors—or any instructor assigning writing—do? For me, the answer is to focus on helping students craft their voice, even in seemingly straightforward technical genres. In this post, I’ll share three strategies for helping students understand that they have a voice in technical writing and learn how to leverage that voice to create engaging and audience-specific content.  

A Shifting Information Landscape 

As generative AI transforms the way technical content is generated, large companies like Google are also transforming how they present information. For example, Google’s search results are moving from traditional links to a three-tiered results structure. When users search for something on Google, they are now increasingly encountering AI-generated content that answers their search query. For example, if you search “technical communication genres” on Google, at the time of this writing you see an AI-generated description of these genres, followed by the typical links to related articles (ranked by Google’s sponsored-ad algorithm).   

Google search results for “technical communication genres” 

The third set of results, however, will soon be an “Experience and Perspective Filter,” which showcases user-generated content about the topic. With this filter, Google search users will see top-rated (or top-sponsored) user-generated content (e.g., Instagram Reels, TikTok videos) alongside traditional search results. Why? Because companies like Google are recognizing that as generative AI provides content, humans still provide ideas—and both things are valuable (and lucrative).  

After introducing students to this shifting information landscape in my introductory technical communication course, I’ve found it helpful to then help them recognize, craft, and leverage their voice across all our course assignments. I do this by helping students understand the difference between information and perspective; centralize inclusion; and learn to write for, not just with, AI.  

1. Distinguishing Information from Perspective 
When I introduce the technical documentation assignment, I ask students to use generative AI tools, like ChatGPT, to generate instructions or documentation about their topic. I tell students they have to choose to write technical documentation about something they already know a lot about. As students generate content through ChatGPT, I ask them to identify the steps in the process that they are documenting, noting information that is correct (or incorrect). I then ask students to find a YouTube video, community group, or business that also provides information on their topic. For example, in class, I ask students to prompt ChatGPT to provide instructions on changing a car battery, and I then show them an example of a YouTube video that I used to help me change my own car battery. We discuss why that YouTube video is helpful to me, given my own audience expectations and limited experience with cars. What is the difference between the instructions generated by ChatGPT and the instructions I found on YouTube? Perspective. The YouTube video showcases personality, uses a calming voice to help novice viewers, and provides instructions that are more accessible. Through this activity, I then push students to think about how they will use their technical documentation assignment not just to show information, but to showcase their perspective. Perspective, I tell students, is what employers are looking for in their companies, and what encourages users to engage with information. Information alone has become cheap and easy, but perspective is only gaining value.  

2. Centralizing Inclusion
“When general information can be accessed anywhere, you can add a unique perspective that thinks about users who have been excluded. How can you use your skills not just to provide information, but to make information more accessible to others?” I share these statements with my students as a theme for our course, providing examples from community organizations whose mission is to transform information for their specific audiences. For example, I contrast technical documents shared by the US government during the COVID-19 pandemic with examples from local organizations that translated and localized COVID-19 prevention and treatment instructions for Indigenous language speakers. I ask students to annotate community examples to note how these organizations transform technical documentation to increase accessibility and inclusion. Through this activity, students note that general instructions, like “practice social distancing,” can be made more accessible for people who live in multiple-family homes. Instructions like “wash your hands repeatedly” also need to be transformed for communities who do not have regular access to water. Through these adaptations, technical information can become not only accurate, but also actionable, for all.  

3. Teach Students to Write For AI 
While many instructors spend time teaching students about the affordances and potential dangers of writing with AI, I also find it helpful to let students know that they will now also need to know how to write for AI. In our resume and CV unit, we spend time discussing Applicant Tracking Systems (ATS), which are machine learning tools increasingly used by employers to scan resumes and CVs for relevant keywords. Often unknowingly, applicants are writing for AI algorithms that can dictate their future. In this lesson, I ask students to use a text analyzer tool to identify key words in job ads that they find interesting. I then encourage students to tailor their resumes to specific job ads by including these key words on their resumes. Within this same lesson, I let students know that while AI systems like ATS do in fact have biases when reading resumes, human readers also impose their own biases in assessing job candidates. For example, I introduce students to studies demonstrating how African American names have been found to be disproportionally rejected by human resume readers in comparison to applicants perceived to have white names. This data also shows that women tend to make their names smaller on resumes and undersell their qualifications and experiences when compared to male applicants. Thus, as with any technical communication genre, bias cannot be avoided, but it should be considered and addressed directly—whether writing for humans or AI or both!

Writing pedagogies have a long tradition of adapting to fast-changing technological innovations. With the increased presence and influence of AI, instructors have an opportunity to emphasize what we have always known across disciplines—that students’ individual talents, voices, and perspectives are what make communication accessible, effective, and ethical.