How to Cite Generative AI in Your Writing

The APA and MLA guidelines for citing AI-generated texts call for writers to cite every phrase that was generated by an AI tool. This expectation fails to account for how writers are using GAI (generative artificial intelligence) recursively and with multiple tools throughout the writing process. A single phrase -- perhaps the gist that becomes the thesis -- may be informed by a writer's searching with Elicit, Consensus, and Perplexity. They may then upload papers they found during strategic searching to tools such ChatGPT or Perplexity and ask for summaries. They may then use LitMaps, Inciteful, and ResearchMaps to better understand canonical texts and gaps in the research. Next they may begin drafting on a blank page in gdocs, or, perhaps they will copy/paste the results of their strategic searching into an AI tool and ask it to write the first draft. Perhaps once they write a draft they will then run it by multiple AI tools to check for audience awareness, diction, voice, tone, and persona. Even more importantly, the APA and MLA citation guidelines fail to account for the extent of human labor or the percentage of AI involvement. Additionally, in the references, the MLA guidelines call for writers to list their prompts. The prompts a writer uses to generate a phrase may be pages long. When done conscientiously, a single phrase could have ten pages of prompts and citations in the references, noting the prompts they used over days or even weeks. This failure on the part of APA and MLA to account for how writers are composing with AI tools matters because it puts the careers of students and professionals at risk. To protect their reputations, authors need a viable way to clarify for their readers how they avoided plagiarism and academic dishonesty when using AI to compose texts. Based on scholarship and research in writing studies, this article presents four distinct citation frameworks: one broad model applicable across all disciplines and professions, and three more detailed models specifically tailored for educational settings, where instructors aim to assess students' labor, creative processes, and use of AI tools throughout the writing process.

a human and a robot sit together. Both the human and robot are staring at the computer screen, collaborating.

Summary

This article addresses the question, “Can I Use Generative AI in Ways That Avoid Academic Dishonesty & Plagiarism?”

The emergence of GAI (Generative Artificial Intelligence) tools has blurred the lines between academic integrity and plagiarism. These tools not only assist in traditional stages of writing—such as prewriting, drafting, editing, and proofreading—but also enhance the creative process itself, serving as a Thought Partner for developing and critiquing ideas, a Research Assistant for gathering and synthesizing sources, a Composition Assistant for refining ideas and structure, a Designer for creating visual elements, an Editor for polishing the prose, a Citation Assistant for managing references, and a Publishing Assistant for finalizing and distributing work across platforms. As AI continues to shape how we create, the boundaries between human authorship and AI-assisted collaboration grow increasingly complex, raising important questions about authorship, academic integrity, plagiarism, and copyright.

Traditionally, academic dishonesty encompasses actions like submitting someone else’s work as one’s own, copying without proper attribution, and receiving unacknowledged assistance. But with AI, things are not so clear-cut. If a writer prompts an AI to generate text and presents it as their own work without acknowledging the AI’s contribution, it may not be traditional plagiarism—after all, AI doesn’t “own” the text. However, it could still be viewed as academically dishonest if the writer doesn’t disclose the use of AI. Especially in school settings where teachers engage students in writing to learn deeply about a subject, a student’s superficial use of AI that is unacknowledged misrepresents the process and level of effort involved in creating the work.

According to U.S. copyright law, writers do not own AI-generated text, as it lacks the human authorship necessary for copyright protection (Federal Register, 2023). Only the original human contributions—such as creative decisions made during the writing process—are eligible for copyright. This legal reality complicates questions of ownership and academic honesty, leaving students and professionals vulnerable to allegations of plagiarism if they fail to clearly distinguish their own contributions from AI-generated content.

Most educators would likely consider it academically dishonest if students superficially engage with AI tools and present AI-generated text as their own. However, if a writer actively engages with AI-generated text—cutting words, adding others, revising, and refining the content to better meet their rhetorical goals—is this dishonest? Does the author own the copyright of substantively revised works?

The concepts of authorship, plagiarism, and copyright need to evolve to account for how writers are using AI to compose. In the future, AI may be perceived as just another tool a writer uses to express themselves, much like a word processor, grammar checker, or visualization tool. Authorship may be considered legitimate if writers remain in charge of their creative processes, interrogating every word and ensuring their inner speech and perception of the rhetorical situation drive the narrative. In this model, AI becomes a collaborative partner rather than a substitute for original thought and composition. The integrity of the work depends on the writer’s active role in crafting and controlling the content.

Presently, some educators view any AI-generated work as academically dishonest — and students certainly need to practice audience awareness and follow their teacher’s and institution’s plagiarism and academic integrity policies. Rightfully so, educators worry use of AI will diminish human agency, students’ cognitive development, and student learning.

Others, however, argue that AI is yet another technology in an ongoing evolution of communication technologies. They point to past disruptive technologies—such as the pen, the word processor, or the printing press. They note these tools have revolutionized how we communicate–that changes in technology do more than facilitate communication: they transform human agency and redefine what it means to be human. They argue the affordances and constraints of today’s hardware (e.g., Blackwell GPU) and software (e.g., Chato1-preview) remediate how we research, solve problems, interpret information, and think, compose, and create (Rainie and Aderson, 2023)

For example, the printing press not only democratized knowledge but also disrupted existing power structures by spreading ideas, empirical research methods, and textual criticism, thus contributing to the broader “conversation of humankind” (Bolter, 2001). As technorhetoricians like Dobrin (2002) argue, writing is always evolving, constantly shaped by new technologies. From this perspective, adopting AI tools is simply the next step in our quest to express ourselves and accomplish our goals more efficiently. Ultimately, as Lessig argues in Free Culture (2024), if a tool makes a process a human wants to do easier, it will be widely adopted.

The article below analyzes these questions by reviewing the APA and MLA conventions for citing AI-generated texts. It critiques these guidelines for being inconsistent and impractical in seven key areas: (1) they fail to account for how AI is integrated into all stages of writing, from prewriting to publishing; (2) they risk overwhelming texts with excessive citations, disrupting readability and making them difficult to follow; (3) they do not distinguish between minor AI assistance (e.g., grammar checks) and significant content generation; (4) they fail to acknowledge the iterative nature of AI use, where students engage with AI throughout the writing process; (5) they provide no guidance on how to specify the percentage of AI involvement in a text; (6) they lead to cluttered reference lists with multiple entries for the same tool used at different stages; and (7) they do not account for the labor involved in revising AI-generated content, thus failing to adequately reflect human contribution. This lack of clarity leaves students and professionals vulnerable to accusations of dishonesty—even if they believe they are following the rules.

Based on scholarship and research in writing studies, this article recommends that authors include a “metaprocess footnote” that explains how they used AI—whether as a (1) Thought Partner, (2) Research Assistant, (3) Composition Assistant, (4) Designer, (5) Editor, (6) Citation Assistant, or (7) Publishing Assistant. This initial model is broad, making it applicable across academic and professional fields, providing a flexible framework for documenting AI involvement in writing processes.

Additionally, the article presents three more detailed models specifically designed for educational settings, where teachers can use them as accountability measures and evaluation criteria:

  1. Rhetorical Processes: This model focuses on how AI tools are integrated into rhetorical reasoning and analysis, helping writers develop an appropriate rhetorical stance based on audience, context, and purpose.
  2. Composing Processes: This model maps AI usage across all stages of the writing process, including prewriting, inventing, drafting, collaborating, researching, planning, organizing, designing, rereading, revising, editing, proofreading, sharing or publishing. This framework is particularly useful in writing classrooms, where educators can assess how students use AI tools throughout the entire composing process, ensuring students remain engaged and responsible for their creative decisions.
  3. Style: This model addresses how AI tools contribute to the refinement of style—including elements such as clarity, brevity, coherence, flow, inclusivity, simplicity, and unity. Instructors can use this model to evaluate whether students effectively used AI tools like Grammarly or ChatGPT to improve stylistic features of their writing while maintaining their voice and control over the content.

These four models provide a comprehensive approach, allowing writers and educators to integrate AI in ways that are transparent, accountable, and ethically sound, while ensuring that human agency remains central to the writing process.

AI Citation Guidelines: APA and MLA

Presently, style guidelines promulgated by the APA and MLA advise writers to cite content generated by or significantly influenced by AI.

APA 7th Edition (2023 update)

Format:

  • Cite AI tools as software, not as authors
  • Include: name of AI tool, version, organization, year, URL (if available)

Example:

In-text citations: (ChatGPT, 2023; Claude, 2024; Perplexity AI, 2024)

Sentence: Estimates of nuclear warhead counts for the top five nuclear powers vary between AI tools: Russia (5977-6257), United States (5550), China (350-410), France (290), and the United Kingdom (225-260) (ChatGPT, 2023; Claude, 2024; Perplexity AI, 2024).

Reference list entries:

  • OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com
  • Anthropic. (2024). Claude (3.5 Sonnet version) [Large language model]. https://www.anthropic.com
  • Perplexity AI. (2024). Perplexity [Large language model]. https://www.perplexity.ai

MLA 9th Edition (2024 update)

Format:

  • Cite AI-generated content as a source, not an author
  • Include: name of AI tool, version, creator, access date, prompt information

Example:

In-text citations: (OpenAI, “Nuclear arsenals”; Anthropic, “Nuclear weapons count”; Perplexity AI, “Top 5 nuclear powers”)

Sentence: Estimates of nuclear warhead counts for the top five nuclear powers vary between AI tools: Russia (5977-6257), United States (5550), China (350-410), France (290), and the United Kingdom (225-260) (OpenAI, “Nuclear arsenals”; Anthropic, “Nuclear weapons count”; Perplexity AI, “Top 5 nuclear powers”).

Works Cited Entries:

  • OpenAI. “Nuclear arsenals of top 5 countries.” ChatGPT, 2 Oct. 2024, chat.openai.com/chat. Accessed 2 Oct. 2024.
  • Anthropic. “Nuclear weapons count for major powers.” Claude, 2 Oct. 2024, www.anthropic.com. Accessed 2 Oct. 2024.
  • Perplexity AI. “Top 5 nuclear powers and their arsenals.” Perplexity, 2 Oct. 2024, www.perplexity.ai. Accessed 2 Oct. 2024.

Problems with Current APA and MLA AI Citation Guidelines

Misalignment with Real-World AI Usage

Current guidelines assume that AI contributions are discrete and easily identifiable. In reality, writers may use multiple AI tools throughout the writing process. Authors may engage with a dozen tools just to refine a single phrase, making it difficult to track individual AI inputs.

Impracticality for Extensive AI Use

Citation rules become impractical when writers frequently use AI. Using multiple AI tools within a single sentence or paragraph (e.g., for research, summarization, or phrasing) can lead to excessive in-text citations, overwhelming readability and disrupting the natural flow of the text.2. Impracticality for Extensive AI Use

Disruption of Text Flow

Frequent in-text citations for every AI tool used can disrupt readability. MLA’s guidelines, for example, could result in a paragraph filled with citations from different AI tools used across various stages (prewriting, drafting, revising), potentially requiring pages of cited sources for a single paragraph.

Cluttered Reference Lists

The heavy reliance on AI tools can clutter reference lists, leading to lengthy works cited sections that include multiple entries for the same tool used across different points in the writing process. This adds unnecessary complexity to bibliographies.

Lack of Nuance in Contribution

Current guidelines don’t distinguish between minor AI assistance (e.g., grammar checking) and significant content generation. Theses guidelines not acknowledge that writers use AI for various stages, including prewritinginventingdraftingcollaboratingresearchingplanningorganizingdesigningrereadingrevisingeditingproofreadingsharing or publishing

Difficulty in Tracking Iterative AI Use

Writers engage in iterative dialogues with AI tools over extended periods, refining content and revisiting ideas. Current guidelines fail to account for this ongoing interaction, treating AI as a static source instead of a collaborative process that shapes the entire writing journey.

No Mechanism to Specify AI Involvement

The guidelines lack clarity on how much AI involvement requires citation. For example, does an AI suggestion of a few sentences require the same level of citation as a full paragraph generated by AI? This absence of guidance leaves ambiguity around the percentage of AI contributions.

How Should Universities and Publishers Ask Authors to Cite Use of AI?

Below are three frameworks that writers could follow to report their use of AI throughout the composing process. These three models provide transparency about how writers used AI — whether superficially or substantively, and thereby clarify whether they hold copyright per U.S. copyright law. The first model is abbreviated and may work across the disciplines and professions. The second two models are a bit more nuanced and would work well in writing courses where the goal is to introduce students to a broad suite of composing strategies.

Sample MetaProcess Footnotes for Academic and Professional Disciplines

To protect their works from allegations of plagiarism and academic dishonesty, writers should write a “metaprocess footnote” that explicitly states whether they used GAI tools as a (1) Thought Partner; (2) Research Assistant; (3) Composing Assistant; (4) Designer; (5) Editor; (6) Citation Assistant; or (7) Publishing Assistant.

  • Thought Partner: AI acts as a reflective partner during the prewriting and brainstorming stages, helping writers think critically about their ideas and the direction they want to take.
  • Research Assistant: AI tools help writers identify key research, synthesize multiple sources, and explore new methods to enrich their writing.
  • Composing Assistant: AI supports the drafting process by offering alternative approaches, helping writers structure their arguments, and assisting with rhetorical reasoning.
  • Designer: AI enhances the visual appeal of documents, helping writers create scannable, visually engaging content.
  • Editor: AI tools help writers refine their prose, ensuring stylistic consistency, grammatical correctness, and overall coherence.
  • Citation Assistant: AI tools streamline citation management, ensuring proper formatting and organization of sources.
  • Publishing Assistant: AI supports the final steps of publication, helping writers prepare content for different platforms and formats.
RoleAI Support in Composing Process
Thought PartnerAI tools like Replika may act as reflective companions, helping writers by asking questions about their goals and prompting introspection. ChatGPT may simulate brainstorming sessions or challenge a writer’s ideas by playing the “devil’s advocate,” sparking deeper thought.
Research AssistantAI tools like LitMaps, Elicit, and Semantic Scholar may assist in identifying key texts, tracking the evolution of scholarly conversations, and mapping out research gaps. These tools may summarize relevant academic articles and suggest related sources to strengthen a writer’s research foundation. Consensus and Keenious may help writers synthesize findings from multiple sources.
Composing AssistantDuring the drafting phase, tools like ChatGPT or Perplexity may help writers organize thoughts, explore various drafting techniques (inductive vs. deductive), and refine ideas. HyperWrite may assist with ongoing coaching to help writers remain focused and productive. AI can also help generate alternative arguments or test out various rhetorical strategies, helping writers experiment with their writing.
DesignerAI tools like SciSpace or HeyGen may assist in visual design by helping create infographics, videos, or document layouts that are scannable and accessible. AI may help writers implement design principles such as proximity, contrast, and alignment in documents. Additionally, tools like Midjourney may generate visuals from text, making documents more engaging and easier to scan.
EditorAI tools like Grammarly and ChatGPT may provide feedback on grammar, syntax, and clarity, while also offering stylistic suggestions. Writers may use AI to edit documents for brevity, coherence, and inclusivity. AI may also assist in detecting tone and style inconsistencies. This role also overlaps with the editing-focused sections covered under Style in our discussion.
Citation AssistantTools like Scite AI and Semantic Scholar may generate, format, and organize references in appropriate citation styles (APA, MLA, etc.). AI helps ensure that citations are consistent and complete, helping writers stay organized when handling large numbers of references. Keenious can recommend relevant papers to cite based on existing research in the document.
Publishing AssistantAI may assist in preparing work for final publication or sharing by ensuring it meets the necessary format, media, and SEO requirements. Tools like SciSpace help format academic papers, while HeyGen generates AI-powered videos, transforming written content into multimedia such as video presentations or summaries. Additionally, AI tools like Frase or SurferSEO can handle SEO tasks, such as writing meta descriptions, generating keywords, and analyzing content to ensure it ranks well on search engines. These tools ensure that the work is optimized not just for various platforms but also for SEO performance, enhancing visibility in digital spaces.

Examples of MetaProcess Footnotes for Academic and Professional Disciplines

  1. I used ChatGPT as a Thought Partner to help generate initial ideas for this project. Throughout the drafting process, ChatGPT prompted me with questions about my thesis and argument structure, which helped refine the focus of the final draft.
  2. During the research phase, I employed Semantic Scholar and ResearchRabbit as Research Assistants. These tools helped me identify relevant research studies, track the evolution of scholarly conversations in the field, and map out potential gaps in the literature.
  3. In preparing this manuscript, I relied on ChatGPT as a Composing Assistant to suggest ways to organize my argument and improve transitions between sections. I also used Claude to explore alternative perspectives on the topic, which helped diversify the rhetorical strategies used in the discussion section.
  4. For the design of this report, I utilized SciSpace as a Designer to create a set of visually engaging charts and infographics that summarize the data. I also used HeyGen to generate an AI-powered video summary, providing a multimedia option for readers.
  5. To ensure clarity and style consistency, I used Grammarly as an Editor. It was particularly helpful in identifying sentences that required rephrasing for brevity and clarity, and it highlighted areas where the tone did not align with the formal nature of the document.
  6. I used Scite AI and Zotero as Citation Assistants to organize and manage all references, ensuring adherence to the latest APA citation guidelines. These tools also helped me discover relevant articles that were cited in recent studies in my field.
  7. For publication, I used SciSpace as a Publishing Assistant to format the document according to the submission guidelines of the targeted journal. It also helped generate an accessible version of the article for online readers by creating a video abstract.

Sample MetaProcess Footnotes for Writing Classrooms

Depending on the assignment, teachers may find it useful to ask their students how they used AI to facilitate

  1. Rhetorical Processes
  2. Composing Processes
  3. Style

AI Support for Rhetorical Processes

  • Rhetorical Analysis: This process involves breaking down the elements of a rhetorical situation—such as exigence, audience, and constraints—that influence communication. Writers use rhetorical analysis to understand the dynamics shaping a particular discourse and to critique the effectiveness of various rhetorical strategies. AI tools like ChatGPT can assist in analyzing these components by offering feedback on tone, audience expectations, and potential rhetorical challenges. Additionally, tools like Consensus can help writers summarize and critique texts, providing alternative rhetorical frameworks.
  • Rhetorical Reasoning: This analytical process allows writers to decide on the most appropriate rhetorical stance by sorting through different rhetorical moves (e.g., appeals, devices, and genres). Writers engage in rhetorical reasoning to determine how best to respond to an exigency or call for discourse. AI tools like ChatGPT and Perplexity assist by generating multiple argument structures, helping writers evaluate various rhetorical strategies and approaches to a topic. AI can also help writers investigate how scholarly conversations around a topic have evolved and identify gaps in the discourse that need to be addressed.
Rhetorical ProcessAI Role
Rhetorical AnalysisAI tools help writers break down rhetorical situations—identifying exigence, audience, and constraints. Writers can use AI to analyze how these elements influence the text and communication. For instance, ChatGPT or Perplexity can assist in identifying audience expectations or providing analyses of how a particular argument resonates with different demographics.
Rhetorical ReasoningAI can aid in sorting through rhetorical strategies, providing data or suggestions on rhetorical appeals (ethos, pathos, logos), rhetorical devices, and modes to use for a specific audience. For example, ChatGPT or Claude can help writers explore potential rhetorical moves or generate multiple argument structures, while Elicit can summarize how scholarly conversations around a topic have evolved over time. AI can help writers identify gaps in existing discourse or offer diverse perspectives on how best to craft their argument to resonate with their audience.

Sample Metaprocess Footnotes for Rhetorical Analysis

  1. In conducting the rhetorical analysis for this essay, I used ChatGPT to help identify the rhetorical elements of the chosen texts, such as their appeals to ethos and pathos, and the constraints shaping the discourse. The AI assisted in generating a comparative analysis of audience expectations between two texts, helping to clarify the persuasive strategies each author employed.
  2. To critique the effectiveness of the rhetorical strategies used in this speech, I relied on Consensus to summarize key rhetorical moves and critique the argument’s reliance on logical appeals (logos). ChatGPT provided feedback on how well the speaker adapted their rhetorical stance based on audience constraints.
  3. For this project, I used Perplexity to explore how various rhetorical appeals (ethos, pathos, and logos) were employed across different genres, particularly comparing academic articles with media reports. This tool helped summarize how each genre’s rhetorical strategies catered to different audience expectations.
  4. During my analysis of the rhetorical situation in this case study, I utilized ChatGPT to provide insights into how exigence and audience influenced the structure of the argument. ChatGPT helped me identify potential areas where the rhetorical devices were either underused or overly reliant on certain appeals, guiding my critique of the argument’s balance.

AI Support Across Composing Processes

Process/Intellectual StrategyAI Role
PrewritingAI assists in generating ideas, exploring topics, and organizing initial thoughts. AI tools like Replika can coach writers by asking reflective questions, while LitMaps and Semantic Scholar visualize research gaps and key texts. Perplexity helps organize early ideas.
InventionAI helps writers generate new ideas and foraging methods from other disciplines. Tools like ResearchRabbit and SciSpace create visual maps and relationships between research. AI fosters interdisciplinary foraging, helping writers experiment with ethnographic methods in new contexts.
ResearchingAI supports the discovery of new knowledge and the evaluation of research methods. Corpus analysis tools like AntConc or Voyant Tools analyze large datasets, while SciSpace and ResearchRabbit visualize scholarly trends and research networks. AI can forage research methods from other fields and gather multimedia data.
PlanningAI helps writers set goals, organize ideas, and transition from inductive to deductive reasoning. Tools like Rocky.ai and HyperWrite guide the writing process and keep writers accountable. AI like Perplexity can aid in synthesizing ideas to help form structured, deductive arguments. ChatGPT assists with strategic planning.
DesigningAI assists with making documents scannable and translating them into other formats, such as infographics or AI-generated videos. SciSpace helps with data visualizations, while tools like HeyGen generate AI-driven video summaries. AI tools also help writers use headings and visual design to make information more accessible.
OrganizingAI assists with structuring content, ensuring that documents follow genre conventions and adhere to deductive structures. AI tools like Grammarly and ChatGPT help writers maintain the Given-to-New Contract, ensuring coherence between familiar and new information. Perplexity can ensure the logical flow of content, adhering to genre norms.
RereadingAI tools can read drafts aloud, helping writers catch awkward phrases, gaps, or errors. Tools like Grammarly assist in sentiment analysis and document comparison. ChatGPT can read drafts at different speeds or voices to help writers identify issues with tone, style, and organization.
RevisingAI aids in adopting multiple stakeholder perspectives during revision, helping writers re-envision their work. Grammarly and ChatGPT provide feedback on content revisions, clarity, and coherence. AI tools can simulate stakeholder critiques, offering feedback to improve the argument. Sybill offers real-time meeting summaries and feedback.
EditingAI tools support editing by offering suggestions for brevity, clarity, and style, with tools like Grammarly focusing on grammar, punctuation, and syntax. ChatGPT helps refine style and tone, while other tools provide personalized feedback on linguistic choices. (Linked with Style elements).
ProofreadingAI tools help with final checks on grammar, mechanics, and consistency. Grammarly identifies mechanical errors, while ChatGPT helps polish the final draft for readability, catching small stylistic or mechanical errors that might be missed during manual proofreading.
Citation ManagementAI assists in managing citations, ensuring accuracy and consistency. Scite AI and Keenious help generate and organize citations, while tools like SciSpace ensure that citations adhere to the required formatting standards.
Sharing or PublishingAI helps prepare documents for publication, translating them into various formats and ensuring they adhere to specific media standards. Tools like HeyGen generate AI-powered videos, and SciSpace assists with final formatting for academic publishing.

Sample Metaprocess Footnotes for Composing Strategies

  1. In this essay, I used ChatGPT during prewriting to brainstorm ideas and generate initial topic outlines. I then used ResearchRabbit to explore interdisciplinary connections and track research gaps within related fields. To refine the clarity and flow, I employed Grammarly during editing, and used Scite AI to organize and format my citations.
  2. For the revision process, I used ChatGPT to simulate feedback from multiple stakeholder perspectives, which helped me improve the argument’s clarity and coherence. Additionally, I leveraged Rocky.ai to stay accountable for my writing deadlines and reflect on the inductive reasoning present in the draft, transitioning it toward a deductive structure.
  3. Throughout my research process, I used Semantic Scholar to identify key studies and applied Voyant Tools for corpus analysis, helping to analyze trends within the data. To prepare the final document for submission, I utilized SciSpace to generate a video summary, making the document accessible in a different format.

Style Categories: Using AI to Enhance Style

This table focuses on how AI tools can help writers refine their style, including clarity, brevity, coherence, and more. It shows how AI can be used to improve specific stylistic elements and make the writing more effective.

Style ElementAI Role
ClarityAI tools help writers achieve clarity by refining sentences, ensuring that the language is clear and accessible for the intended audience. Writers should disclose how AI tools contributed to improving clarity in their writing. Examples: Grammarly for clarity checks, ChatGPT for revising unclear passages.
BrevityAI assists writers in condensing ideas and eliminating unnecessary words to achieve conciseness. Writers should specify if AI helped in reducing verbosity while maintaining meaning. Examples: Grammarly for brevity suggestions, ChatGPT for shortening sentences without losing essential meaning.
CoherenceAI tools can evaluate whether ideas are logically connected and help writers improve the overall coherence of their arguments. Writers should indicate if AI was used to ensure logical flow between sections. Examples: Grammarly for ensuring coherence, Scite AI for checking the logical consistency of arguments and citations.
FlowAI aids in maintaining a smooth transition between ideas, helping writers ensure that their work flows naturally. Writers should disclose if AI tools were used to enhance the flow of ideas between paragraphs. Examples: Grammarly for checking transitions, ChatGPT for reordering sentences or paragraphs to improve flow.
InclusivityAI tools help ensure that language is inclusive and respectful, aligning with modern expectations of diversity and inclusivity in writing. Writers should disclose if AI was used to check for inclusivity in language. Examples: Grammarly for checking language sensitivity and inclusiveness, ChatGPT for ensuring diverse and respectful phrasing.
SimplicityAI helps writers simplify complex ideas, making their writing more accessible without oversimplifying important content. Writers should specify how AI was used to achieve simplicity in the text. Examples: Grammarly for simplifying complex sentences, ChatGPT for rephrasing overly complicated sections to make them clearer.
UnityAI ensures that every part of the document contributes to the overall narrative or argument, helping writers maintain unity. Writers should indicate how AI contributed to achieving unity in the text. Examples: Grammarly for checking whether every section contributes to the thesis, ChatGPT for identifying and cutting irrelevant information.
  1. To improve the clarity of my writing, I used Grammarly to identify unclear or ambiguous phrases. Grammarly flagged several sentences that could be rephrased for greater clarity, particularly in the introduction and conclusion. I also employed ChatGPT to suggest alternative phrasing for complex ideas, ensuring that my audience could easily understand key points.
  2. For brevity, I used Grammarly to help condense my ideas and eliminate redundant phrases. The tool suggested reducing wordiness in several paragraphs without sacrificing meaning, and I accepted its recommendations to keep the text concise. Additionally, ChatGPT helped shorten a few sections by offering more succinct versions of long-winded explanations.
  3. To enhance the coherence of my argument, I used Scite AI to check the logical flow between my claims and the supporting evidence. The tool helped ensure that my transitions between sections were smooth and that my argument progressed logically from one point to the next. I also used Grammarly to ensure that each paragraph connected cohesively with the next.
  4. In order to improve the overall flow of my document, I used ChatGPT to reorganize several sentences and paragraphs for better readability. The tool suggested different ways to order my ideas, which helped create a more natural progression of thoughts. Additionally, Grammarly flagged transitions between sections that could be improved for smoother reading.
  5. To ensure my writing was inclusive and respectful, I used Grammarly to check for any potentially biased language. The tool highlighted instances where my language could be more gender-neutral and provided suggestions to make my writing more inclusive. I also employed ChatGPT to rephrase sections that discussed sensitive topics, ensuring that the language remained respectful and inclusive.
  6. For simplicity, I used ChatGPT to help simplify complex ideas in the discussion section. The tool suggested rephrasing technical jargon and breaking down longer sentences, making the information more accessible to a broader audience without oversimplifying the content.
  7. To maintain unity throughout the essay, I used Grammarly to check that every section contributed directly to the main thesis. The tool helped identify a few sections where I had gone off-topic, allowing me to remove irrelevant content and ensure that all parts of the essay were aligned with my central argument.

Related Concepts

References

Bolter, J. D. (2001). Writing space: Computers, hypertext, and the remediation of print (2nd ed.). Lawrence Erlbaum Associates.
Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence. (2023, March 16). Federal Register. https://www.federalregister.gov/documents/2023/03/16/2023-05321/copyright-registration-guidance-works-containing-material-generated-by-artificial-intelligence.
Dobrin, S. I. (2023). AI and writing. Broadview Press.
Lessig, L. (2004). Free culture: How big media uses technology and the law to lock down culture and control creativity. Penguin Press.

Rainie, L., & Anderson, J. (2023, February 24). The Future of Human Agency. Pew Research Center: Internet, Science & Tech. https://www.pewresearch.org/internet/2023/02/24/the-future-of-human-agency/

Wang, H., Dang, A., Wu, Z., & Mac, S. (2024). Generative AI in higher education: Seeing ChatGPT through universities’ policies, resources, and guidelines. GenerativeAI.pdf. University of Arizona and University of Georgia. https://arxiv.org.

Xiao, P., Chen, Y., & Bao, W. (n.d.). Waiting, banning, and embracing: An empirical analysis of adapting policies for generative AI in higher education. Retrieved from https://ar5iv.org/pdf/2305.18617​.

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