What key terms should I know within artificial intelligence (AI) discourse?

Artificial Intelligence (AI)

Artificial Intelligence, often referred to as AI, encompasses computational systems created to imitate human behaviors and cognitive processes. In essence, computer scientists strive to design AI that can augment or replicate specific human cognitive functions, such as problem solving, experiential learning, pattern recognition, and decision making.

Generative AI (GenAI)

Generative AI is a branch of artificial intelligence trained on vast datasets (text, images, audio, code, etc.) in order to generate contextually relevant outputs. ChatGPT is a well-known formation of GenAI designed to generate human-like language in response to a prompt; in fact, the “G” in ChatGPT stands for “generative” to reflect this nature. However, GenAI covers a great variety of generators, such as image generators like Midjourney and DALL-E 2, or voice generators like Eleven Labs. Amid these various formations, ChatGPT belongs to a specific subcategory of GenAI called Large Language Models.

Large Language Models (LLMs)

Large Language Models are a specific subset of GenAI designed to process and generate human language. These models, trained on extensive textual data, can understand, generate, and manipulate text in ways that resemble human communication. LLMs include popular chatbots like OpenAI’s ChatGPT, Microsoft’s Bing, Google’s Bard, and more.

What should I know about rhetorical analysis as a skill before I begin this tutorial?

A Brief Overview

Most academic writing demonstrates strong argumentation skills. However, texts can also entertain, instruct, or inform. One thing most texts have in common are attempts to  persuade. Influencing  your audience with a convincing argument is a major part of everyday writing and a key component of academic writing .

Writing a rhetorical analysis can be one of the most challenging assignments required within a composition and rhetoric classroom. A rhetorical analysis evaluates the success of an article’s argument and determines what rhetorical strategies and devices were used to persuade the audience. Composing a rhetorical analysis requires that readers go beyond simply trusting what they read. Readers must critically engage with the expressed truth, value, and appropriateness of a text’s content. In a rhetorical analysis, you are asked to determine what is happening in a text, why specific modes were used, whether the argument is successful, and how the information is focused toward a specific audience.

This tutorial demonstrates how ChatGPT, a Large Language Model (LLM), can help you recognize rhetorical situations and strategies, evaluate a text for effectiveness, and recognize bias and logical fallacies within a text. By harnessing the power of ChatGPT as a generative tool, you can gain insights and support in navigating the sometimes challenging task of recognizing and discussing a text’s structure and effectiveness.

For further information on rhetorical analysis as a general skill and the process of writing one, see table 1.

Table 1

Open-Access Resources Related to Rhetorical Analysis

This lesson mines the following article for examples:

Kellogg, Ronald T. “Professional Writing Expertise.” The Cambridge Handbook of Expertise and Expert Performance, edited by K. Anders Ericsson, Neil Charness, Paul J. Fetovich,

and Robert R. Hoffman, Cambridge University Press, 2006, pp. 389-402.

What are three ways that ChatGPT can help with composing a rhetorical analysis?

Recognize Rhetorical Situations and Strategies

ChatGPT can be a valuable resource for looking at a text rhetorically. With effective prompting, ChatGPT can mine a text to help you identify patterns so you can judge the strength of a text’s arguments. ChatGPT can also help identify classical rhetoric within a text. Leveraging ChatGPT‘s capabilities allows you to refine your ideas about a text and the tools an author uses to persuade the reader.

Strategy in Action #1

View the following example prompt and response with ChatGPT focused on recognizing rhetorical situations and strategies.

If you’d like to interact directly with ChatGPT in the above conversation, access the original chat through this link and click the ‘Continue the conversation’ button in the opened dialogue window.

Check out table 2 for additional tips and suggestions on dividing text into compact portions that can easily be managed within ChatGPT.

Table 2

Tips and Suggestions: Working with Manageable Chunks

Evaluating Information within a Text through Analysis

Sometimes forming an opinion about a text for your rhetorical analysis can be difficult. Utilizing ChatGPT may help you develop a starting point for your research. By engaging in interactive discussions with ChatGPT, you can explore a text using different search terms and criteria. This collaborative exploration with ChatGPT helps you fine-tune your search strategies, broaden your information retrieval abilities, and achieve greater precision in your research outcomes.

Strategy in Action #2

View the following example prompt and response with ChatGPT focused on evaluating information within a text through analysis.

If you’d like to interact directly with ChatGPT in the above conversation, access the original chat through this link and click the ‘Continue the conversation’ button in the opened dialogue window.

Check out table 3 for additional tips and suggestions related to ensuring content validity.

Table 3

Tips and Suggestions: Ensuring Validity

Recognize Bias and Logical Fallacies within a Text

A rhetorical analysis may center around a text’s use of faulty logic or bias. Identifying and arguing against the author’s logic or stance on an issue can be a great focus. ChatGPT can help you identify bias and logical fallacies by defining and demonstrating different fallacies. Finding discrepancies in logic and biased thinking can help you gauge the effectiveness of a text. Identifying and arguing against the author’s logic or stance on an issue can be a powerful part of your analysis. Similarly, conceding that a text is logical and then invalidating the arguments with alternative facts and interpretations can be another way to focus your rhetorical analysis.

Strategy in Action #3

View the following example prompt and response with ChatGPT focused on recognizing bias and logical fallacies within a text.

If you’d like to interact directly with ChatGPT in the above conversation, access the original chat through this link and click the ‘Continue the conversation’ button in the opened dialogue window.

Check out table 4 for additional tips and suggestions related to determining bias and recognizing logical fallacies.

Table 4

Tips and Suggestions: Recognizing Bias and Logical Fallacies

What are some possible pitfalls when collaborating with ChatGPT on a rhetorical analysis?

Produces Inaccuracies and Fabricated Information

ChatGPT and other LLMs may fabricate information to fulfill a prompt. This fabrication is a by-product of the way these tools mine available texts to build responses. These tools are designed to mimic human language in a convincing manner; however, they may not deliver valid or reliable information. While the information may sound credible, it may be easily recognized as false by others. For example, most of the information contained in this ChatGPT response concerning ‘back gaze’ is misleading as ‘back gaze’ is not a consideration of the past in relation to one’s life. Instead, it correctly refers to the male gaze that overtly sexualizes women.

Learning Outcomes for ENGL 1302: How does this tutorial apply to state standards?

This tutorial is designed to support your success in ENGL 1302 (Composition II) by aligning with the student learning outcomes established by the Texas Higher Education Coordinating Board. As highlighted in Table 5 below, this tutorial directly addresses three key standards. By aligning with these specific learning outcomes, this tutorial not only provides you with skills and knowledge that transfer across diverse learning environments but also gives your education value outside your institution.

See table 5 for applicable state learning outcomes.

Table 5

Applicable State Learning Outcomes