artificial intelligence research paper writing

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AI writing tools promise faster manuscripts for researchers

Automation brings plagiarism risks, and software still needs human input for analysis and narrative.

Credit: gmast3r/Getty Images

17 August 2021

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Writing tools powered by artificial intelligence (AI) have the potential to reduce manuscript preparation time to a few days, or hours. Deep-learning technologies that run chatbots, spellchecks and auto-generated tweets are being used in a growing number of products pitched at students and academics.

Grammarly, for example, claims to “inspect your writing carefully to improve clarity, word choice and more”, offering free and fee-based services.

But are these tools up to the task? In an experiment through education information site EduRef, a group of recent graduates, undergraduates and self-described undergraduate-level writers were given the same assignments as GPT-3, an AI language program developed by OpenAI, a research company co-founded by Elon Musk.

The assignments were evaluated by instructors who did not know who (or what) had written them. GPT-3 performed in line with the humans, according to EduRef, and received “more or less the same feedback”.

The program was praised for writing excellent openings and transitions, but was criticised for using vague, blunt and awkward language, and for failing to craft a strong narrative. It wrote shallow, less descriptive papers than the students, according to EduRef’s write-up on its website, but it took between three and 20 minutes to write a paper, compared to three days for the students.

Hilde van Zeeland is chief applied linguist at start-up company Writefull, which offers AI-based language editing, and is part of London-based Digital Science (see disclosure, below). She says AI tools are already powerful enough to improve a writer’s sentence flow and structure, and will continue to improve.

The company recently analysed more than 250,000 abstracts to identify the most commonly used phrases in each of four different parts of the abstract.

They found, for example, that the words ‘aim of this study’ occurred most frequently in part 1 of the abstract (where study aim and background are described) and the phrase ‘95% confidence interval’ occurred most often in part 4 (which deals with meaning of results, contribution, future research). Users can choose phrases and connecting sentences to use in their own papers.

“With this database of phrases, when a user struggles with the right word to use for each section, our software will be able to provide good alternatives,” says van Zeeland.

The website tells users not to worry about plagiarism, reassuring them that certain phrases won’t be flagged by a plagiarism checker because they are short and commonly used.

Writefull is running a separate experiment that involves feeding an abstract into an AI tool, which generates a paper title based on the input. This function can enhance title readability, draw readership to the abstract and make the article more visible to search engines, according to van Zeeland.

AI tools can do more than check a writer’s grammar and spelling and suggest frequently used phrases, says computer scientist, Guillaume Cabanac, from the University of Toulouse in France.

An analysis of journal-published computer-science papers by Cabanac and his colleagues, posted as a preprint on arXiv in July and yet to be peer-reviewed, found swathes of articles containing tortured phrases and nonsensical text. For example, the phrase ‘colossal information’ was used instead of ‘big data’.

The authors suspect that these papers were the result of using automated translations or software that rewrites existing text to disguise plagiarism, according to a report in Nature .

Their study prompted warnings from research integrity experts that a new type of fabricated paper was entering the scientific literature, which will be hard to spot as AI tools learn to use more sophisticated language.

Considerations for using AI writing tools in academic work

Shu Chian Tay, a science communicator at the National University of Singapore , fears that AI writing tools could exacerbate inequality between labs with different access to resources or openness to trying new technologies.

Shu Chian Tay

“Consider a hypothetical situation where AI science-writing is possible and two labs have made the same research breakthrough at the same time,” says Tay.

“One lab stuck to human writing, which took weeks, while the other made use of AI writing tools. The latter, who is likely to publish earlier would get most, if not all, of the scientific recognition and lucrative intellectual property rights.”

Will AI replace human writing?

Tay notes that although AI writing tools are quite powerful, they have not yet reached a point where they can write a scientific manuscript from scratch. “We still need researchers to analyse data, present them as figures, and develop a coherent story before feeding all this information to the AI machine,” she says.

Ryan Morrison, professor of English as a second language at George Brown College in Toronto, Canada, says that although the adoption of AI in academic writing is inevitable, it is unlikely to replace human writing in the near future.

Ryan Morrison

“Just as super-computer calculators can process large sets of numbers fast, AI writing tools outperform humans in completing tasks like spell checks and text generation at a much faster rate,” says Morrison. “But the creativity of AI is ultimately limited by the input materials and the discretion of the human curator.”

Software such as Turnitin is also incorporating AI technology to enhance its ability to detect plagiarism. This could potentially be used to identify documents written using AI tools.

Be transparent about using AI writing tools in academic work

Michael Mindzak, assistant professor in the department of educational studies at Brock University in Ontario, Canada, cautions that the academic community has not yet agreed on how to manage potential problems related to AI writing tools, such as plagiarism and authorship credits.

Michael Mindzak

Most institutions are yet to formulate policies on the use of these tools by students and staff. This can be problematic when committee members making decisions on tenure and promotion have different views about the appropriateness of using them, says Mindzak.

“My advice is to be transparent,” says Mindzak. “Declare and add a disclaimer if you have used AI-assisted writing. As more people in the community do this, it may become a norm, just like how the ‘conflict of interest’ section has been added to academic papers in response to a rise in company-funded research and start-ups from academic labs.”

*Digital Science is a subsidiary of Holtzbrinck Publishing Group, which owns 53% of Springer Nature, publisher of the Nature Index. Nature Index is editorially independent of its publisher.

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Can artificial intelligence help for scientific writing?

Michele salvagno.

1 Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles, 1070 Brussels, Belgium

Fabio Silvio Taccone

Alberto giovanni gerli.

2 Department of Clinical Sciences and Community Health, Università Degli Studi di Milano, 20122 Milan, Italy

Associated Data

Not applicable.

This paper discusses the use of Artificial Intelligence Chatbot in scientific writing. ChatGPT is a type of chatbot, developed by OpenAI, that uses the Generative Pre-trained Transformer (GPT) language model to understand and respond to natural language inputs. AI chatbot and ChatGPT in particular appear to be useful tools in scientific writing, assisting researchers and scientists in organizing material, generating an initial draft and/or in proofreading. There is no publication in the field of critical care medicine prepared using this approach; however, this will be a possibility in the next future. ChatGPT work should not be used as a replacement for human judgment and the output should always be reviewed by experts before being used in any critical decision-making or application. Moreover, several ethical issues arise about using these tools, such as the risk of plagiarism and inaccuracies, as well as a potential imbalance in its accessibility between high- and low-income countries, if the software becomes paying. For this reason, a consensus on how to regulate the use of chatbots in scientific writing will soon be required.

Introduction

A chatbot is an electronic system (generally a software) that simulates conversations by responding to keywords or phrases it recognizes and that can be integrated into various platforms, such as websites, mobile apps, and messaging platforms.

The Chatbot Generative Pre-trained Transformer (ChatGPT), developed by OpenAI, is a type of Artificial Intelligence (AI) software designed to simulate conversations with human users. This chatbot works through algorithms programmed to understand natural language inputs and answer with appropriate responses, either pre-written or newly generated by the AI. ChatGPT is constantly improved with reinforcement techniques, natural language processing, and machine learning, to improve its ability to understand and thoroughly respond to users’ needs. Concretely, you can conversationally ask anything and receive a fast and adequate human-like written reply to your questions or requests such as: (a) write a small text on a given topic; (b) get information on a topic of interest; (c) compose an email or message with a certain tone, specific content, and intended for a particular person; (d) correct the shape of a text or change its wording; (e) solve problems.

As such, this chatbot could also be used in scientific writing [ 1 ]. Indeed, ChatGPT could become a promising and powerful tool for tasks such as automated draft generation, article summarizing, and language translation, which may be useful in academic activities to make writing work faster and easier. However, the use of this tool in scientific writing raises some ethical concerns and should therefore be regulated.

ChatGPT in scientific writing

ChatGPT is already able to help medical researchers and scientists to write articles and abstracts, in literature research, to summarize data or information, to provide suggestions for structure, references, and titles, in language reviews to make the text more readable, or even to generate a full draft of a paper [ 2 ]. At this stage, although feasible, no article dealing with critical care medicine has been published so far using this application. Moreover, whether writing a manuscript dealing with a topic of critical care medicine would be easier or more difficult when compared to other medical disciplines remains unknown. Which are the limits of possible applications of these tools have to be clarified.

ChatGPT can generate text on a wide variety of topics. Recently, an entire letter to the editor was written by ChatGPT, answering the author's questions [ 1 ]. Artificial Intelligence cannot generate new ideas, but it can organize and develop the ones of the researcher, creating an initial draft. However, this appears to be a starting point for a human-based development of the text, as the automatic text generated is far from being a substitute for the knowledge, creativity, and critical thinking of human experts.

For the literature search, ChatGPT and AI research assistants (such as “elicit.org”) can aid researchers in the review process by finding academic papers, summarizing their conclusions, and highlighting areas of uncertainty (i.e., summarizing the recent randomized clinical trial on the use of extracorporeal membrane oxygenation for refractory cardiac arrest [ 3 ], Fig.  1 ). This could help physicians, as an example, to quickly gain an understanding of the current state of knowledge on a particular topic, and to identify potential gaps that need to be addressed, although the provided summary might be quite generic and do not critically analyze differences among studies.

Example of a summary of the existing literature on a specific topic

During the writing process, ChatGPT can help to generate an initial draft of a scientific paper and even suggest titles. By providing raw information, ChatGPT can also assist in composing the section on the methods used in the study, justify sample size and describe data analysis techniques. From author’s experience, when the manuscript has been finalized, ChatGPT is extremely effective for the editing process; formatting and language editing, rewriting a particularly complex sentence in a clearer way, and even summarizing the entire text in order to compose a suitable abstract, are feasible using this approach, although the results are not always satisfactory, but they certainly save time. ChatGPT has been recently asked to prepare regular discharge summaries [ 4 ], but the quality of the content has not been specifically evaluated. To our knowledge, a structured evaluation to determine the quality of the output has not been performed yet. More complicated writing processes, such as systematic review and meta-analyses, require the human intervention and ChatGPT might be helpful mainly for editing.

A future potential application of AI is in the automatic generation of figures, tables, and other visual elements of the manuscript, which can aid in summarizing data. These elements are important for the clarity and understanding of the manuscript, but they are often time-consuming to create.

Importantly, the writing process of a scientific paper requires, for the moment, the guidance and supervision of human researchers who are experts in the field to ensure the accuracy, coherence, and credibility of the content before being used or submitted for publication. Chatbots can help but needs the researcher’s input, and inadequate inputs would lead to inadequate results. For this reason, chatbots and AI, in general, should not replace human researchers' expertise, judgment, personality, and—in the end—responsibility.

Chatbots vs. human beings

As AI, ChatGPT has a superior advantage in terms of fast comprehending information deeply and connecting evidence to reach conclusions, compared to humans who have limitations in their ability to read a comprehensive range of literature and distinguish the connections between seemingly separate pieces of information.

Moreover, it may be difficult to recognize whether a paper is written by a chatbot or a human being [ 5 ], because chatbots use advanced techniques, such as natural language processing (NLP) and machine learning, to generate text that is similar to human writing. To detect the author is a complex task and requires thorough critical reading to reach a conclusion. However, a few characteristics might reveal that a paper was written by a chatbot, such as the lack of nuance, style, or originality, which could allow the identification by AI output detectors and skeptical human reviewers [ 6 ]. Interestingly, the same writing traits could be found in texts written in a language that is not an individual's native tongue. By focusing on these traits, it is possible that AI plagiarism detectors would identify non-native English language papers as AI-generated text. It would be interesting to find these tools' sensibility in detecting the authors of texts written by these two groups.

Nevertheless, the chatbot-generated text might lack the subtle phrasing and word choice that a human author might use to convey a certain meaning or tone. It might also be vaguer and contain inconsistencies that would not be present in a human-written paper. Instead, if the paper contains a high degree of structural and grammatical errors, it may suggest that it was written by a human being (but it should not be the other way around). Lastly, if the paper is discussing a topic that is very specific and highly technical, it is less likely that a chatbot could generate such a text, as it would require a deep understanding of the topic and the ability to generate scientific analysis and conclusions.

Ethical considerations

Ethical concerns could also limit the use of these chatbots for scientific writing [ 7 ].

The process of acquiring knowledge from others and writing new or review articles involves humans incorporating both what they have learned from others and their ideas. It is natural for humans to repeat the findings, statements, and written works of others, and thus to come close to committing plagiarism by presenting an idea without proper referencing to the original authors. AI or ChatGPT systems can commit plagiarism under this definition but can also be programmed to avoid copying others by rephrasing their work in a manner similar to what human authors do. However, using programs to reformulate sentences and writing to reduce the percentage of plagiarism (i.e., asking the software to rewrite a section written by other authors with different words) could not be considered acceptable in scientific research. If we define “plagiarism” as a mere act to copy someone else work, just rephrasing what it was written, regardless of the method used, and without adding anything personal, it is a violation of academic integrity. For this reason, journal editors should use programs to detect written content using AI to detect plagiarism better.

Second, the lack of an expert and critical human mind behind scientific work (which is the basis of the scientific method) could lead to a risk of perpetuating or amplifying existing biases and inaccuracies in the data, providing unfair results and hampering scientific growth. Whatever the use of AI, we believe that the presence of an expert in the field in conducting scientific activity and writing is a necessary cornerstone even to guarantee the quality of the work.

Third, the incredible development of AI tools can lead to a significant increase in publication numbers from some researchers, but not accompanied by a real increase in her or his experience in that field. Ethical issues can therefore arise regarding hiring professionals by academic institutions that score on the number of publications rather than on their quality.

Fourth, whether the ChatGPT should be mentioned within the authors of the manuscript written using this approach remains not adequately defined. Finally, if at the moment ChatGPT and other chatbot services are free of charge, it is not guaranteed that they will not become paying in the future. The introduction of charges to access these chatbots could lead to a further disparity between high- and low-income countries (as well as between more junior to older professionals), for scientific production, resulting in unfair facilitation for the formers with unpredictable consequences.

Chatbot as a tool in the ICU

In addition to scientific writing, ChatGPT has the potential to assist physicians in their hospital work by saving time and allowing them to focus on providing patient care. In an Intensive Care Unit (ICU), where constant monitoring of multiple patient information is required, such as treatment progression, laboratory values, microbiological results, and fluid balance calculation, ChatGPT can assist in several ways.

First, ChatGPT can provide general information about recognized ICU protocols: when given a specific request, ChatGPT would be able to generate a response (i.e., initial management of sepsis) by analyzing the input and identifying patterns in the text data that it has been trained on. Furthermore, ChatGPT has a distinct advantage over humans in quickly gathering, comprehending, and utilizing information. In future, it may eventually be taught to apply this knowledge in clinical practice by presenting the latest evidence to healthcare professionals, if not directly creating patient-tailored protocols to reflect new findings.

Currently, it could already be used for generating clinical notes by just providing raw information, such as daily summaries and discharge summaries, which could save time and increase accuracy. Moreover, it could help in communicating with patients and families, translating into other languages, and generating personalized messages with accurate and timely information about the patient's condition, which would not have the purpose of replacing, but add to, the doctor-patient (or doctor-relatives) relationship. Unfortunately, depending on the applicable legislation, privacy issues may arise when providing patients' information.

Anecdotally, when provided with clinical information, laboratory values, past medical history, and other relevant data, ChatGPT may already assist physicians in, for example, determining appropriate treatment options; however, it is important to note that the answers provided by the chatbot can be erroneous or dated, as the technology is still in development and may not have the level of accuracy, current knowledge, or precision that is desired. Nevertheless, it is believable that AI will continue to improve in the future and potentially provide more accurate and reliable results.

As next future perspectives, AI in general could potentially be trained to automatically extract and understand all the relevant information from electronic health records and by analyzing patient data, such as vital signs, laboratory results, and medical history, helping doctors to quickly access patient information, providing recommendations for interventions, and allowing more fast and comprehensive decisions. The implementations of these AI systems, which already exist in several areas of the world, with chatbots, could create an interacting system which would provide immediately elaborated information to the treating physician.

Conclusions

ChatGPT is an AI software potentially able to assist in the writing process of a scientific paper and can help in the literature review, identify research questions, provide an overview of the current state of the field, and assist with tasks, such as formatting and language review. Moreover, it can have applications in clinical practice as time-savers. As chatbot tools will be widely adopted in the near future, it is crucial to have international academic regulations in place to regulate their use in scientific writing and establish mechanisms for identifying and penalizing unethical usage. Chatbots are simply tools, they can assist human researchers but should not be used as a replacement for human researchers' expertise, judgment, and personality.

We have requested to ChatGPT “Could you review this paper and tell us if you (as an author!) agree to submit it to Critical Care Journal?”. The (non-modified) response from ChatGPT has been: “ As an AI model, I am not able to review or submit papers to journals as I am not a researcher or author. However, I can give you some feedback on the paper you've provided. The paper presents a clear and comprehensive overview of the potential uses of ChatGPT in scientific writing, specifically in the field of critical care medicine. The introduction provides a good background on chatbots and ChatGPT and how it can be used in various tasks. The paper goes on to discuss the potential uses of ChatGPT in scientific writing, such as draft generation, literature research and language review. The paper also touches on the ethical concerns and limitations of using ChatGPT in scientific writing. I would recommend that you review the paper again, check for grammar and spelling errors, and make sure that the citations and references are correctly formatted. It would be also important to have a proper conclusion that summarizes the main ideas of the paper and the future perspectives. It's important to keep in mind that ChatGPT should always be used in combination with the expertise and judgement of human experts and its output should be validated before it is used in clinical practice.”

Acknowledgements

For the writing of this article, we have not received funds or support from OpenAI, which is not associated with the entire process that led to the preparation of this article. The text, written with the support of the ChatGPT by OpenAI, has however been modified by the human authors, who assume full responsibility for form and content.

Author contributions

MS, FST, AGG conceived of the study, and participated in its design and coordination and helped to draft the manuscript; MS, FST, AGG participated in the design of the study; MS, FST, AGG wrote, reviewed and made extensive editing of the final content; FST conceived and took the screenshot. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Availability of data and materials

Declarations.

The original online version of this article was revised: shortly after initial publication of this article, the authorship and Acknowledgements were updated in line with Springer Nature authorship policies. Large Language Models (LLM), such as ChatGPT, do not currently satisfy our authorship criteria. An attribution of authorship carries with it accountability for the work, which cannot be effectively applied to LLMs.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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A Correction to this paper has been published: 10.1186/s13054-023-04390-0

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Research Writing and Generative AI Large Language Models

A rapidly evolving phenomenon impacting higher education is the availability of generative artificial intelligence systems [such as Chat Generative Pre-trained Transformer or ChatGPT]. These systems have been developed from scanning text from millions of books, web sites, and other sources to enable algorithms within the system to learn patterns in how words and sentences are constructed. This allows the platforms to respond to a broad range of questions and prompts, generate stories, compose essays, create lists, and more. Generative AI systems are not actually thinking or understanding like a human, but they are good at mimicking written text based on what it has learned from the sources of input data used to build and enhance its artificial intelligence algorithms, protocols, and standards.

As such, generative AI systems [a.k.a., “Large Language Models”] have emerged , depending on one’s perspective, as either a threat or an opportunity in how faculty create or modify class assignments and how students approach the task of writing a college-level research paper. We are in the early stages of understanding how LLMs may impact learning outcomes associated with information literacy, i.e., fluency in effectively applying the skills needed to effectively identify, gather, organize, critically evaluate, interpret, and report information. However, before this is fully understood, Large Language Models w ill continue to improve and become more sophisticated, as will academic integrity detection programs used to identify AI generated text in student papers.

When assigned to write a research paper, it is up to your professor if using ChatGTP is permitted or not. Some professors embrace using these systems as part of an in-class writing exercise to help understand their limitations, while others will warn against its use because of their current defects and biases. That said, the future of information seeking using LLMs means that the intellectual spaces associated with research and writing will likely collapse into a single online environment in which students will be able to perform in-depth searches for information connected to the Libraries' many electronic resources.

As LLMs quickly become more sophisticated, here are some potential ways generative artificial intelligence programs could facilitate organizing and writing your social sciences research paper:

• Explore a Topic – develop a research problem related to the questions you have about a general subject of inquiry.
• Formulate Ideas – obtain background information and explore ways to place the research problem within specific contexts .
• Zero in on Specific Research Questions and Related Sub-questions – create a query-based framework for how to investigate the research problem.
• Locate Sources to Answer those Questions – begin the initial search for sources concerning your research questions.
• Obtain Summaries of Sources – build a synopsis of the sources to help determine their relevance to the research questions underpinning the problem.
• Outline and Structure an Argument – present information that assists in formulating an argument or an explanation for a stated position.
• Draft and Iterate on a Final Essay – create a final essay based on a process of repeating the action of text generation on the results of each prior action [i.e., ask follow up questions to build on or clarify initial results].

Despite their power to create text, generative AI systems are far from perfect and their ability to “answer” questions can be misleading, deceiving, or outright false. Described below are some current problems adapted from an essay written by Bernard Marr at Forbes Magazine and reiterated by researchers studying LLMs and writing. These issues focus on problems with using ChatGPT, but they are applicable to any current Large Language Model program .

• Not Connected to the Internet . Although the generative AI systems may appear to possess a significant amount of information, most LLM’s are currently not mining the Internet for that information [note that this is changing quickly. For example, an AI chatbot feature is now embedded into Microsoft’s Bing search engine, but you'll probably need to pay for this feature in the future]. Without a connection to the Internet, LLMs cannot provide real-time information about a topic. As a result, the scope of research is limited and any new developments in a particular field of study will not be included in the responses. In addition, the LLMs can only accept input in text format. Therefore, other forms of knowledge such as videos, web sites, audio recordings, or images, are excluded as part of the inquiry prompts.
• The Time-consuming Consequences of AI Generated Hallucinations . If proofreading AI generated text results in discovering nonsensical information or an invalid list of scholarly sources [e.g., the title of a book is not in the library catalog or found anywhere online], you obviously must correct these errors before handing in your paper. The challenge is that you have to replace nonsensical or false statements with accurate information and you must support any AI generated declarative statements [e.g., "Integrated reading strategies are widely beneficial for children in middle school"] with citations to valid academic research that supports this argument . This requires reviewing the literature to locate real sources and real information, which is time consuming and challenging if you didn't actually compose the text. And, of course, if your professor asks you to show what page in a book or journal article you got the information from to support a generated statement of fact, well, that's a problem. Given this, ChatGPT and other systems should be viewed as a help tool and never a shortcut to actually doing the work of investigating a research problem.
• Trouble Generating Long-form, Structured Content . ChatGPT and other systems are inadequate at producing long-form content that follows a particular structure, format, or narrative flow. The models are capable of creating coherent and grammatically correct text and, as a result, they are currently best suited for generating shorter pieces of content like summaries of topics, bullet point lists, or brief explanations. However, they are poor at creating a comprehensive, coherent, and well-structured college-level research paper.
• Limitations in Handling Multiple Tasks . Generative AI systems perform best when given a single task or objective to focus on. If you ask LLMs to perform multiple tasks at the same time [e.g., a question that includes multiple sub-questions], the models struggle to prioritize them, which will lead to a decrease in the accuracy and reliability of the results.
• Biased Responses . This is important to understand. While ChatGPT and other systems are trained on a large set of text data, that data has not been widely shared so that it can be reviewed and critically analyzed. You can ask the systems what sources they are using, but any responses can not be independently verified. Therefore, it is not possible to identify any hidden biases or prejudices that exist within the data [i.e., it doesn't cite its sources]. This means the LLM may generate responses that are biased, discriminatory, or inappropriate in certain contexts .
• Accuracy Problems or Grammatical Issues . The sensitivity to typographical errors, grammatical errors, and misspellings is currently very limited in LLMs. The models may produce responses that are technically correct, but they may not be entirely accurate in terms of context or relevance. This limitation can be particularly challenging when processing complex or specialized information where accuracy and precision are essential. Given this, never take the information that is generated at face value; always proofread and verify the results!

As they currently exist, ChatGPT and other Large Language Models truly are artificial in their intelligence. They cannot express thoughts, feelings, or other affective constructs that help a reader intimately engage with the author's written words; the output contains text, but the systems are incapable of producing creative expressions or thoughts, such as, conveying the idea of willful deception and other narrative devices that you might find in a poem or song lyric. Although creative devices, such as metaphors, idioms, imagery or subtleties in narrative rhythm, style, or voice, are rarely used in academic writing, it does illustrate that personalizing the way you present your research [e.g., sharing a personal story relating to the significance of the topic or being asked to write a reflective paper ] cannot be generated artificially.

Ethical Considerations

In the end, the ethical choice of whether to use ChatGTP or similar platforms to help write your research paper is up to you; it’s an introspective negotiation between you and your conscience. As noted by Bjork (2023) and others, though, it is important to keep in mind the overarching ethical problems related to the use of LLMs. These include:

• LLMs Do Not Understand the Meaning of Words . Without meaning as a guide, these systems use algorithms that rely on formulating context clues, stylistic structures, writing forms, linguistic patterns, and word frequency in determining how to respond to queries. This functionality means that, by default, LLMs perpetuate dominant modes of writing and language use while minimizing or hiding less common ones. As a result,...
• LLMs Prioritize Standard American English . White English-speaking men have dominated most writing-intensive sectors of the knowledge economy, such as, journalism, law, politics, medicine, academia, and perhaps most importantly, computer programming. As a result, writers and speakers of African American, Indigenous English, and other sociolinguistic dialects that use forms of language with its own grammar, lexicon, slang, and history of resistance within the dominant culture, are penalized and shamed for writing as they speak. The default functionality and outputs of LLMs, therefore, can privilege forms of English writing developed primarily by the dominant culture.
• LLMs Do Not Protect User Privacy . ChatGPT and other platforms record and retain the entire content of your conversations with the systems. This means any information you enter, including personal information or, for example, any documents you ask the systems to revise is retained and cannot be removed. Although the American Data Privacy and Protection Act was being considered within the 117th Congress, there is no federal privacy law that regulates how these for-profit companies can store, use, or possibly sell information entered into their platforms. Given this, it is highly recommended that personal information should never be included in any queries.

NOTE:   If your professor allows you to use generative AI programs or you decide on your own to use an LLM for a writing assignment, then this fact should be cited in your research paper, just as any other source of information used to write your paper should be acknowledged. Why? Because unlike grammar or citation tools, such as Grammarly or Citation Machine that correct text you've already written, generative AI programs are creating new content that is not in your own words. Currently, the American Psychological Association (APA), Modern Language Association (MLA) and the Chicago Manual of Style provide recommendations on how to cite generated text.

ANOTHER NOTE: LLMs have significant deficiencies that still require attention to thorough proofreading and source verification, an ability to discern quality information from misleading, false, irrelevant, or even made up information, a capacity to interpret and critically analyze what you have found, and the skills required to extrapolate meaning from the research your have conducted. For help with any or all of these elements of college-level research and writing, you should still contact a librarian for help.

YET ANOTHER NOTE: Researchers are finding early evidence that suggests over-reliance on ChatGPT and other LLM platforms for even the simplest writing task may, over time, undermine confidence in a student's own writing ability. Just like getting better at giving a class presentation or working on a group project, good writing is an acquired skill that can only be improved upon through the act of doing; the more you write, the more comfortable and confident you become expressing your own ideas, opinions, and judgements applied to the problem you have researched. Substituting LLMs with your own voice can inhibit your growth as a writer, so give yourself room to think and write creatively and with confidence by accepting LLMs as a tool rather than a definitive source of text.

For more information about Generative AI platforms and guidance on their ethical use in an academic setting, review the USC Libraries' Using Generative AI in Research guide for students and faculty. For an introduction to the limitations and potential pitfalls generative AI text generators applied to law, GO HERE .

Introduction to ChatGPT for Library Professionals. Mike Jones and Curtis Fletcher. USC Libraries, Library Forum, May 18, 2023; Aikins, Ross and Albert Kuo. “What Students Said About the Spring of ChatGPT.” Inside Higher Education , September 3, 2023; Baugh, John. “Linguistic Profiling across International Geopolitical Landscapes.” 152 Dædalus (Summer 2023): 167-177; ChatGPT. Library, Wesleyan University; Bjork, Collin. "ChatGPT Threatens Language Diversity." The Conversation , February 9, 2023; Understanding AI Writing Tools and their Uses for Teaching and Learning at UC Berkeley . Center for Teaching & Learning, University of California, Berkeley; Ellis, Amanda R., and Emily Slade. "A New Era of Learning: Considerations for ChatGPT as a Tool to Enhance Statistics and Data Science Education." Journal of Statistics and Data Science Education 31 (2023): 1-10; Ray, Partha Pratim. “ChatGPT: A Comprehensive Review on Background, Applications, Key Challenges, Bias, Ethics, Limitations and Future Scope.” Internet of Things and Cyber-Physical Systems (2023); Uzun, Levent. "ChatGPT and Academic Integrity Concerns: Detecting Artificial Intelligence Generated Content." Language Education and Technology 3, no. 1 (2023); Lund, Brady D. Et al. “ChatGPT and a New Academic Reality: Artificial Intelligence Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishing.” Journal of the Association for Information Science and Technology 74 (February 2023): 570–581; Rasul, Tareq et al. "The Role of ChatGPT in Higher Education: Benefits, Challenges, and Future Research Directions.” Journal of Applied Learning and Teaching 6 (2023); Rudolph, Jürgen, Samson Tan, and Shannon Tan. "ChatGPT: Bullshit Spewer or the End of Traditional Assessments in Higher Education?" Journal of Applied Learning and Teaching 6, no. 1 (2023): 342-362; Marr, Bernard. “The Top 10 Limitations Of ChatGPT.” Forbes (March 3, 2023): https://www.forbes.com/sites/bernardmarr/2023/03/03/the-top-10-limitations-of-chatgpt/?sh=41ae78e8f355; Thinking about ChatGPT? Academic Integrity at UBC, Office of the Provost and Vice-President Academic, University of British Columbia.

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The best AI tools for research papers and academic research (Literature review, grants, PDFs and more)

As our collective understanding and application of artificial intelligence (AI) continues to evolve, so too does the realm of academic research. Some people are scared by it while others are openly embracing the change. 

Make no mistake, AI is here to stay!

Instead of tirelessly scrolling through hundreds of PDFs, a powerful AI tool comes to your rescue, summarizing key information in your research papers. Instead of manually combing through citations and conducting literature reviews, an AI research assistant proficiently handles these tasks.

These aren’t futuristic dreams, but today’s reality. Welcome to the transformative world of AI-powered research tools!

This blog post will dive deeper into these tools, providing a detailed review of how AI is revolutionizing academic research. We’ll look at the tools that can make your literature review process less tedious, your search for relevant papers more precise, and your overall research process more efficient and fruitful.

I know that I wish these were around during my time in academia. It can be quite confronting when trying to work out what ones you should and shouldn’t use. A new one seems to be coming out every day!

Here is everything you need to know about AI for academic research and the ones I have personally trialed on my YouTube channel.

My Top AI Tools for Researchers and Academics – Tested and Reviewed!

There are many different tools now available on the market but there are only a handful that are specifically designed with researchers and academics as their primary user.

These are my recommendations that’ll cover almost everything that you’ll want to do:

Want to find out all of the tools that you could use?

Here they are, below:

AI literature search and mapping – best AI tools for a literature review – elicit and more

Harnessing AI tools for literature reviews and mapping brings a new level of efficiency and precision to academic research. No longer do you have to spend hours looking in obscure research databases to find what you need!

AI-powered tools like Semantic Scholar and elicit.org use sophisticated search engines to quickly identify relevant papers.

They can mine key information from countless PDFs, drastically reducing research time. You can even search with semantic questions, rather than having to deal with key words etc.

With AI as your research assistant, you can navigate the vast sea of scientific research with ease, uncovering citations and focusing on academic writing. It’s a revolutionary way to take on literature reviews.

• Elicit –  https://elicit.org
• Litmaps –  https://www.litmaps.com
• Research rabbit – https://www.researchrabbit.ai/
• Connected Papers –  https://www.connectedpapers.com/
• Supersymmetry.ai: https://www.supersymmetry.ai
• Semantic Scholar: https://www.semanticscholar.org
• Laser AI –  https://laser.ai/
• Inciteful –  https://inciteful.xyz/
• Scite –  https://scite.ai/
• System –  https://www.system.com

If you like AI tools you may want to check out this article:

• How to get ChatGPT to write an essay [The prompts you need]

AI-powered research tools and AI for academic research

AI research tools, like Concensus, offer immense benefits in scientific research. Here are the general AI-powered tools for academic research. 

These AI-powered tools can efficiently summarize PDFs, extract key information, and perform AI-powered searches, and much more. Some are even working towards adding your own data base of files to ask questions from. 

Tools like scite even analyze citations in depth, while AI models like ChatGPT elicit new perspectives.

The result? The research process, previously a grueling endeavor, becomes significantly streamlined, offering you time for deeper exploration and understanding. Say goodbye to traditional struggles, and hello to your new AI research assistant!

• Consensus –  https://consensus.app/
• Iris AI –  https://iris.ai/
• Research Buddy –  https://researchbuddy.app/
• Mirror Think – https://mirrorthink.ai

AI for reading peer-reviewed papers easily

Using AI tools like Explain paper and Humata can significantly enhance your engagement with peer-reviewed papers. I always used to skip over the details of the papers because I had reached saturation point with the information coming in. 

These AI-powered research tools provide succinct summaries, saving you from sifting through extensive PDFs – no more boring nights trying to figure out which papers are the most important ones for you to read!

They not only facilitate efficient literature reviews by presenting key information, but also find overlooked insights.

With AI, deciphering complex citations and accelerating research has never been easier.

• Aetherbrain – https://aetherbrain.ai
• Explain Paper – https://www.explainpaper.com
• Chat PDF – https://www.chatpdf.com
• Humata – https://www.humata.ai/
• Lateral AI –  https://www.lateral.io/
• Paper Brain –  https://www.paperbrain.study/
• Scholarcy – https://www.scholarcy.com/
• SciSpace Copilot –  https://typeset.io/
• Unriddle – https://www.unriddle.ai/
• Sharly.ai – https://www.sharly.ai/
• Open Read –  https://www.openread.academy

AI for scientific writing and research papers

In the ever-evolving realm of academic research, AI tools are increasingly taking center stage.

Enter Paper Wizard, Jenny.AI, and Wisio – these groundbreaking platforms are set to revolutionize the way we approach scientific writing.

Together, these AI tools are pioneering a new era of efficient, streamlined scientific writing.

• Jenny.AI – https://jenni.ai/ (20% off with code ANDY20)
• Yomu – https://www.yomu.ai
• Wisio – https://www.wisio.app

AI academic editing tools

In the realm of scientific writing and editing, artificial intelligence (AI) tools are making a world of difference, offering precision and efficiency like never before. Consider tools such as Paper Pal, Writefull, and Trinka.

Together, these tools usher in a new era of scientific writing, where AI is your dedicated partner in the quest for impeccable composition.

• PaperPal –  https://paperpal.com/
• Writefull –  https://www.writefull.com/
• Trinka –  https://www.trinka.ai/

AI tools for grant writing

In the challenging realm of science grant writing, two innovative AI tools are making waves: Granted AI and Grantable.

These platforms are game-changers, leveraging the power of artificial intelligence to streamline and enhance the grant application process.

Granted AI, an intelligent tool, uses AI algorithms to simplify the process of finding, applying, and managing grants. Meanwhile, Grantable offers a platform that automates and organizes grant application processes, making it easier than ever to secure funding.

Together, these tools are transforming the way we approach grant writing, using the power of AI to turn a complex, often arduous task into a more manageable, efficient, and successful endeavor.

• Granted AI – https://grantedai.com/
• Grantable – https://grantable.co/

Best free AI research tools

There are many different tools online that are emerging for researchers to be able to streamline their research processes. There’s no need for convience to come at a massive cost and break the bank.

The best free ones at time of writing are:

• Elicit – https://elicit.org
• Connected Papers – https://www.connectedpapers.com/
• Litmaps – https://www.litmaps.com ( 10% off Pro subscription using the code “STAPLETON” )
• Consensus – https://consensus.app/

Wrapping up

The integration of artificial intelligence in the world of academic research is nothing short of revolutionary.

With the array of AI tools we’ve explored today – from research and mapping, literature review, peer-reviewed papers reading, scientific writing, to academic editing and grant writing – the landscape of research is significantly transformed.

The advantages that AI-powered research tools bring to the table – efficiency, precision, time saving, and a more streamlined process – cannot be overstated.

These AI research tools aren’t just about convenience; they are transforming the way we conduct and comprehend research.

They liberate researchers from the clutches of tedium and overwhelm, allowing for more space for deep exploration, innovative thinking, and in-depth comprehension.

Whether you’re an experienced academic researcher or a student just starting out, these tools provide indispensable aid in your research journey.

And with a suite of free AI tools also available, there is no reason to not explore and embrace this AI revolution in academic research.

We are on the precipice of a new era of academic research, one where AI and human ingenuity work in tandem for richer, more profound scientific exploration. The future of research is here, and it is smart, efficient, and AI-powered.

Before we get too excited however, let us remember that AI tools are meant to be our assistants, not our masters. As we engage with these advanced technologies, let’s not lose sight of the human intellect, intuition, and imagination that form the heart of all meaningful research. Happy researching!

Thank you to Ivan Aguilar – Ph.D. Student at SFU (Simon Fraser University), for starting this list for me!

Dr Andrew Stapleton has a Masters and PhD in Chemistry from the UK and Australia. He has many years of research experience and has worked as a Postdoctoral Fellow and Associate at a number of Universities. Although having secured funding for his own research, he left academia to help others with his YouTube channel all about the inner workings of academia and how to make it work for you.

Thank you for visiting Academia Insider.

We are here to help you navigate Academia as painlessly as possible. We are supported by our readers and by visiting you are helping us earn a small amount through ads and affiliate revenue - Thank you!

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Artificial intelligence is getting better at writing, and universities should worry about plagiarism

Assistant Professor, Faculty of Education, Brock University

Educational Leader in Residence, Academic Integrity and Assistant Professor, University of Calgary

Disclosure statement

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

University of Calgary provides funding as a founding partner of The Conversation CA.

Brock University and University of Calgary provide funding as members of The Conversation CA-FR.

Brock University provides funding as a member of The Conversation CA.

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The dramatic rise of online learning during the COVID-19 pandemic has spotlit concerns about the role of technology in exam surveillance — and also in student cheating .

Some universities have reported more cheating during the pandemic, and such concerns are unfolding in a climate where technologies that allow for the automation of writing continue to improve.

Over the past two years, the ability of artificial intelligence to generate writing has leapt forward significantly , particularly with the development of what’s known as the language generator GPT-3. With this, companies such as Google , Microsoft and NVIDIA can now produce “human-like” text .

AI-generated writing has raised the stakes of how universities and schools will gauge what constitutes academic misconduct, such as plagiarism . As scholars with an interest in academic integrity and the intersections of work, society and educators’ labour, we believe that educators and parents should be, at the very least, paying close attention to these significant developments .

AI & academic writing

The use of technology in academic writing is already widespread. For example, many universities already use text-based plagiarism detectors like Turnitin , while students might use Grammarly , a cloud-based writing assistant. Examples of writing support include automatic text generation, extraction, prediction, mining, form-filling, paraphrasing , translation and transcription.

Read more: In an AI world we need to teach students how to work with robot writers

Advancements in AI technology have led to new tools, products and services being offered to writers to improve content and efficiency . As these improve, soon entire articles or essays might be generated and written entirely by artificial intelligence . In schools, the implications of such developments will undoubtedly shape the future of learning, writing and teaching.

Misconduct concerns already widespread

Research has revealed that concerns over academic misconduct are already widespread across institutions higher education in Canada and internationally.

In Canada, there is little data regarding the rates of misconduct. Research published in 2006 based on data from mostly undergraduate students at 11 higher education institutions found 53 per cent reported having engaged in one or more instances of serious cheating on written work, which was defined as copying material without footnoting, copying material almost word for word, submitting work done by someone else, fabricating or falsifying a bibliography, submitting a paper they either bought or got from someone else for free.

Academic misconduct is in all likelihood under-reported across Canadian higher education institutions .

There are different types of violations of academic integrity, including plagiarism , contract cheating (where students hire other people to write their papers) and exam cheating, among others .

Unfortunately, with technology, students can use their ingenuity and entrepreneurialism to cheat. These concerns are also applicable to faculty members, academics and writers in other fields, bringing new concerns surrounding academic integrity and AI such as:

• If a piece of writing was 49 per cent written by AI, with the remaining 51 per cent written by a human, is this considered original work?
• What if an essay was 100 per cent written by AI, but a student did some of the coding themselves?
• What qualifies as “AI assistance” as opposed to “academic cheating”?
• Do the same rules apply to students as they would to academics and researchers?

We are asking these questions in our own research , and we know that in the face of all this, educators will be required to consider how writing can be effectively assessed or evaluated as these technologies improve.

Augmenting or diminishing integrity?

At the moment, little guidance, policy or oversight is available regarding technology, AI and academic integrity for teachers and educational leaders.

Over the past year, COVID-19 has pushed more students towards online learning — a sphere where teachers may become less familiar with their own students and thus, potentially, their writing.

While it remains impossible to predict the future of these technologies and their implications in education, we can attempt to discern some of the larger trends and trajectories that will impact teaching, learning and research.

Technology & automation in education

A key concern moving forward is the apparent movement towards the increased automation of education where educational technology companies offer commodities such as writing tools as proposed solutions for the various “problems” within education.

An example of this is automated assessment of student work, such as automated grading of student writing . Numerous commercial products already exist for automated grading, though the ethics of these technologies are yet to be fully explored by scholars and educators.

Read more: Online exam monitoring can invade privacy and erode trust at universities

Overall, the traditional landscape surrounding academic integrity and authorship is being rapidly reshaped by technological developments. Such technological developments also spark concerns about a shift of professional control away from educators and ever-increasing new expectations of digital literacy in precarious working environments .

Read more: Precarious employment in education impacts workers, families and students

These complexities, concerns and questions will require further thought and discussion. Educational stakeholders at all levels will be required to respond and rethink definitions as well as values surrounding plagiarism, originality, academic ethics and academic labour in the very near future.

The authors would like to sincerely thank Ryan Morrison, from George Brown College, who provided significant expertise, advice and assistance with the development of this article.

• Artificial intelligence (AI)
• Academic cheating
• Academic integrity
• Academic writing

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How to Write a Research Paper (+ Free AI Research Paper Writer)

Table of contents

Meredith Sell

Over the years, I've managed to vastly improve how I write research papers.

The three major game-changers for me, in terms of quality of the finished piece, have been:

• Following the research paper checklist (see below)
• Developing the thesis before starting to write
• And, more recently, using AI to improve my research paper draft

Let's break down each of these elements and produce the kind of research papers that get cited in magazines.

FREE AI research paper writer > FREE AI research paper writer >

What is a research paper, and how is it written differently?

Research papers are longer and more in-depth than essays. They require extensive research and evidence-based arguments. Research papers also typically have a more formal structure and require citations and references.When academics want to find a balanced and comprehensive view on a given topic, they usually seek a research paper.

Like most writing assignments, a research paper can be broken down into simple steps. Research papers follow the same basic writing process as explanatory or persuasive essays — but instead of making an argument or drawing greater meaning from the topic, the research paper is primarily concerned with concrete facts that may be analyzed, examined, or interpreted to better understand the paper’s central topic.

This is good news if you enjoy research: you’ll be doing a lot of it. The ultimate quality of your paper depends on you conducting thorough, complete research — and relying on reputable sources.

How to Properly Write a Research Paper Using AI

1. make a checklist based on the assignment description, and fill it out with ai.

Your professor has likely specified some criteria for your research paper:

• Length (in pages or words)
• Type of topic (the War of 1812, ancient Greece, agriculture, etc.)
• Elements that must be included, such as analysis, discussion, and comparison.
• Types of sources you must draw from (academic papers, encyclopedias, etc.)
• Source attribution style
• Formatting style

Go through the assignment description and create a checklist of those criteria. You can use this checklist throughout the research and writing process as well:

AI can really help you get some traction with your research paper in the preperation stage. This includes two main steps:

• Brainstorming paper topic idea
• Outlining based on your topic, basing the prompt on the assignment

2. Choose a topic you’re curious about, or use AI to help you with that

A sure way to write a boring research paper is to pick a topic you have no interest in, like summer temperatures in the desert or the life cycle of a flea. (Though someone’s probably interested in those things.)

Instead, follow your curiosity.

If your paper is for a writing class, you may have a lot of freedom to choose what you write about, so tap into your interests. Are you intrigued by the history of roller skating or the invention of the soccer cleat? Or how teen social dynamics have changed with evolving technology (think: home phones → online instant messaging → flip phones → smartphones)?

If you’re writing for a class in a subject like history, art, or science, you’ll probably have more restrictions on what you can write about — like a time period or type of art or science — but you can still use your curiosity to pick an interesting topic.

If you’re having a tough time, try brainstorming a list of things you’ve wondered about. Ask “ what’s up with… ” and see what comes to mind.

For example:

What’s up with traffic circles and why are they supposedly better for traffic patterns than a light or four-way stop?

What’s up with country music sounding more and more like hip-hop?

What’s up with people who have gluten allergies being able to eat bread in Europe but not the US?

Once you have a list, choose the topic you find most interesting (and appropriate for the assignment).

If your mind draws a blank, you can utilize AI to help you choose a topic. Let's say your course is about mid century art. You can go to a tool like Wotdtune and ask it to give you ideas for creative mid century art essays. See example below.

3. Develop your thesis (and guide your research) by asking a research question

Even though a research paper may not necessarily take a side on a topic, it still needs a thesis, aka a central idea or focus that drives the piece from beginning to end. 

We wrote a whole guide on writing thesis statements , so here we’ll just give you this tip:

Use a research question to develop your thesis

A research question is a variation on the “What’s up with…” questions from the last tip — but it will zoom in more specifically on the aspect of your topic that you’re investigating.

Why were the Irish so dependent on potatoes?

Did any women in ancient Greece enjoy relative freedom and autonomy?

You may already know the answer to these questions, or you may not. Either way, they give you a place to start in your research. Once you have your question, set out to:

• Find the initial answer.
• Gather more context (the who, what, when, where, why, how) around that answer.
• Revise your research question and turn it into your thesis.

This process helps tighten your focus from a broad topic that could fill books to a specific angle that can be meaningfully explored in the few pages of your paper.

Instead of the potato famine , write about why England was to blame for the potato famine’s devastating effects on the Irish.

Instead of ancient Greece or women in ancient Greece , write about how Spartan women’s lives differed from the lives of women in Athens.

4. Skim sources and use AI to perform research for your paper

Your research question can help you quickly determine whether information is relevant to your paper. As you gather initial sources, skim them — and then use your research question to decide whether to keep or discard the source. 

Does the source cover information relevant to my research question?

Yes: Keep to read later.

No: Discard and move on to the next source.

This approach will save you precious research time. You won’t waste limited hours reading sources that don’t have a single helpful fact.

If skimming is hard for you (as a deep reader, I get it), Wordtune can help. Paste the link to your online source, upload a scanned PDF, or copy the text, and the tool will scan and summarize for you. You can always come back later and closely read the most useful sources.

5. Make note of the most interesting facts you find

Along with taking detailed notes of your research (complete with all the source info you need to make proper citations), highlight the most interesting facts you come across. You could stick these in a section together or mark them in a way that makes them stand out.

Why should you do this?

Because later on, one of these fascinating factoids could have a direct connection to your thesis — and make a great hook for the start of your paper. Instead of digging through all of your notes to try to remember what that interesting tidbit was, you’ll be able to find it easily.

6. Organize your research

There are plenty of ways to organize your notes, but I suggest breaking them up into subtopics and categories.

• Subtopic: A topic related to your main topic or thesis that needs to be explained and understood by readers in order to understand your main topic or thesis. For example: Land ownership in Ireland under British rule.
• Category: An overarching concept that several subtopics fall under. For example: British restrictions on the Irish.

To start, I would focus on the subtopics and then group them into categories.

As you organize, use the formatting tools in your word processor to tag headings and subheadings. For example, all categories would be an H2 (Heading 2), while all subtopics would be an H3 (Heading 3). 

Tagging your categories and subtopics this way will help you develop your outline. Just organize your categories and subtopics in a logical order, and you’ll have a skeleton of an outline ready to go.

7. Write with your research document open

No one can remember everything they found while researching — you’ll need to reference your research document throughout the writing process. No question there.

But you can make this easier (and keep your writing process efficient) by:

Keeping your research document open and in clear view.

I like to put my draft document and my research document side by side on my screen, so I can see them both at the same time. 

Another approach would be to paste the information you need directly into your draft document — in the order you’ll need it. (Your outline will help you know what you need.)

8. Steal the TK trick from journalists

In the middle of drafting your paper, you find that you’re missing a fact. 

You neglected to write down how many Irish people starved due to the potato famine.

You don’t know what age Spartan women were able to own property.

Instead of derailing your writing and searching for that information, write the sentence you want to write and stick a “TK” where the missing fact should go.

“TK” stands for “to come” (don't ask us why) and is a placeholder used by journalists to mark missing information they’ll fill in later. Using TK allows you to keep writing without getting off track every time you discover your research didn’t cover everything.

A whopping TK Irish people starved, thanks to the combination of famine and British oppression.

At age TK , Spartan girls became women who were able to own property, a right that their sisters in Athens did not enjoy.

9. Revise, explain, paraphrase with AI as your research/writing assistant

Using the right researching tools can get you a lot way.

If you’re ever at a loss for words — writing clunky, clumsy sentences, struggling to explain a concept, or having a hard time paraphrasing a source — Wordtune can serve as your AI sidekick.  

Simply highlight the sentence in question and browse Wordtune’s suggestion for a better wording.

You can also use Wordtune Spices to come up with examples and counter arguments for whatever you're writing about or even find stats and facts, complete with source citations

Wordtune doesn’t do all of the writing for you, but it can help you sharpen your ideas on the sentence level, so you can hand in a research paper with good writing that’s still very much your own.

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The Role of Artificial Intelligence in Enhancing Creative Writing

Artificial Intelligence has brought a digital revolution and a renaissance into creative writing. Over time, AI technologies are harnessed to further strengthen the writer’s creative processes through increasing numbers of productivity and creativity solution tools. The paper hence discusses various aspects of the use of AI in creative writing. Ranging from the very process of idea generation up to the final brush strokes of editing and honing a manuscript. The future of writing is no doubt being rewritten through this continued expansion of AI. This ushers in changes for better access, efficiency, and diversity in the traditional writing landscape. Let’s take a look at the role of artificial intelligence in enhancing creative writing.

Table of Contents

The Emergence of Artificial Intelligence in Creative Writing

Creative writing was not just something that AI suddenly dawned on. First applications were in the areas of language translation, followed by data-driven reporting. But as technology grew, so did the abilities of AI systems, and the potential started shining in more creative disciplines. Today, AI tools have very complex algorithms that are able to understand and manipulate language in ways that sometimes even mimic human creativity.

AI-Powered Writing Assistants

One of the most important applications of AI in creative writing is the development of AI-powered writing assistants. This can give writers suggestions for improvement in grammar, style, and tone. More advanced ones even suggest narrative ideas, plot development, or character traits using input and directives from the user. In such a way, such help really supports those authors who want to improve their work or overcome writer’s block.

Enhanced Research Capabilities

AI applications are able to pass through huge data sets within no time. Putting them in a position to conduct ample research with ease. The AI system can track any detail, either historical or scientific data, and even bring forth some cultural anecdotes that allow the writer access to that information, which can be useful for narrative enrichment and the attainment of a deep understanding of the subject.

AI to streamline the writing process

The use of technologies for natural language processing has made it possible for AI to be a good tool for streamlining the writing process. From the initial draft to the final product, AI can be of paramount importance at every step.

Idea Generation and Expansion

AI tools are good at developing and expanding the idea. Through the analysis of current literature and trends, AI can provide hints and help motivate the writer. This becomes more useful when one is stuck and out of ideas or is looking into new genres and themes.

Drafting and Editing

Drafting using AI helps to flesh out outline notes into coherent text and aids in suggesting how one can state ideas in many other ways. Even with structural modifications, AI can give suggestions on how to rephrase the ideas. AI-powered editors can further fine-tune syntax and ensure the consistent use of language by correcting grammar so that the writer can concentrate more on creative writing.

AI Script Generator: A Game Changer for Scriptwriting

The automation of script generation through specialized AI tools has revolutionized the process of writing a script and making a screenplay. An example is using an AI script generator for suggestions on what dialogue might work best, what plot twists should be thrown in, and at what point in the script the pacing should be increased, all done in strict alignment with the genre and style of the screenplay. In this sense, the writing process is expedited and the quality of the script established. From which all sorts of linguistic styles and cultural nuances are included, which human writers would not be able to detect.

Customization and Adaptability

These AI script generators are quite flexible in terms of customization, depending on the needs and preferences of the user or the scriptwriter. For this reason, these AI utilities can be applied for sitcoms, dramas, or even feature films and generate outputs accordingly in tone and format. In that sense, it is one of the most powerful tools within the scriptwriting industry.

Ethical Considerations and Future Prospects

AI, as it deepens into creative industries, brings with it some ethical issues. Autonomy in creative processes steered by AI, questions of originality and copyright, and the potential of AIs to lead to replacement of human jobs are all areas of heated debate. The writing industry needs to be proactive in handling the issues. However, it is bound to become much more sophisticated. Most likely extending into the more complex areas of creative writing, from here on out. While it will not totally replace the creativity of humans, it will be a great collaborator by enhancing the creative capabilities of human writers in the telling and experiencing of stories.

Continue Reading: AI in E-commerce Content Strategy

Surely, artificial intelligence plays a huge and deep role in augmenting creative writing. AI technologies help augment it in two ways: mechanical support. These emerging, more advanced tools readily available will tap new potentials. Opening a landscape for new and innovative ways in the art of writing. With every stride we make learning the ways through which AI influences writing. There is a sense that such a synergy will create magic and transform into a new tradition of writing practices.

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SSGS300 Week2 2

American Military University *

Information Systems

May 26, 2024

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