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How to use ChatGPT to do research for papers, presentations, studies, and more

sabrina-ortiz

ChatGPT is often thought of as a tool that will replace human work on tasks such as writing papers for students or professionals. But ChatGPT can also be used to support human work, and research is an excellent example. 

Whether you're working on a research paper for school or doing market research for your job, initiating the research process and finding the correct sources can be challenging and time-consuming. 

Also:  5 handy AI tools for school that students, teachers, and parents can use, too

ChatGPT and other AI chatbots can help by curtailing the amount of time spent finding sources, allowing you to jump more quickly to the actual reading and research portion of your work.

Picking the right chatbot 

Before we get started, it's important to understand the limitations of using ChatGPT . Because ChatGPT is not connected to the internet, it will not be able to give you access to information or resources after 2021, and it will also not be able to provide you with a direct link to the source of the information. 

Also :  The best AI chatbots: ChatGPT and other noteworthy alternatives

Being able to ask a chatbot to provide you with links for the topic you are interested in is very valuable. If you'd like to do that, I recommend using a chatbot connected to the internet, such as Bing Chat , Claude , ChatGPT Plus , or Perplexity . 

This how-to guide will use ChatGPT as an example of how prompts can be used, but the principles are the same for whichever chatbot you choose.

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1. Brainstorm

When you're assigned research papers, the general topic area is generally assigned, but you'll be required to identify the exact topic you want to pick for your paper or research. ChatGPT can help with the brainstorming process by suggesting ideas or even tweaking your own. 

Also:  How ChatGPT (and other AI chatbots) can help you write an essay

For this sample research paper, I will use the general topic of "Monumental technological inventions that caused pivotal changes in history." If I didn't have a specific idea to write about, I would tell ChatGPT the general theme of the assignment with as much detail as possible and ask it for some proposals. 

My prompt: I have to write a research paper on "Monumental technological inventions that caused pivotal changes in history." It needs to be ten pages long and source five different primary sources. Can you help me think of a specific topic? 

As seen by the screenshot (below), ChatGPT produced 10 viable topics, including "The Printing Press and the Spread of Knowledge", "The Internet and the Digital Age", "The Telegraph and the Communication Revolution", and more. 

Also:  How to use the new Bing (and how it's different from ChatGPT)

You can then follow up with ChatGPT to ask for further information. You can even tweak these topics with an angle you like more, and continue the feedback loop until you have a topic you are settled on. 

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2. Generate an outline

Once you have selected a topic, you can ask ChatGPT to generate an outline, including as much detail for your assignment as possible. For this example, I used the first topic that ChatGPT suggested in the previous step.

My prompt: Can you give me an outline for a research paper that is ten pages long and needs to use five primary sources on this topic, "The Printing Press and the Spread of Knowledge"? 

ChatGPT generated a 13-point outline that carefully described the areas I should touch on in my paper, as seen in the photo (above). You can then use this outline to structure your paper and use the points to find sources, using ChatGPT as delineated below. 

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3. Tell ChatGPT your topic and ask for sources

Now that you have a topic and outline established, you can ask ChatGPT about the topic of your project and ask it to deliver sources for you.

My prompt: Can you give me sources for a ten-page long paper on this topic, "The Printing Press and the Spread of Knowledge"?

ChatGPT outputs a list of five primary and five secondary sources that you can include in your paper. Remember, because ChatGPT can't give you internet links, you will need to seek out the specific resources on your own, whether that's Googling or visiting your school library. 

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When I asked Bing Chat the same question, it provided sources with clickable links that you can use to access the material you need quicker. For that reason, I would use Bing Chat for this step. 

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4. Describe a specific idea and ask for sources

Instead of describing the whole topic, you can also use a chatbot to find sources for a specific aspect of your paper.

Also:  How (and why) to subscribe to ChatGPT Plus

For example, I asked ChatGPT for sources for a specific bullet in the paper outline that it generated above. 

My prompt: Can you give me sources for the social and intellectual climate of when the printing press was generated?

As in the prior example, ChatGPT generated five primary and five secondary resources for the topic. 

Using this feature for smaller chunks of your essay is a good alternative because it gives you more options on sources and provides tailored insight that you can use to carefully craft your piece. 

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5. Ask for examples of a specific incident

I use this prompt a lot in my workflow because I can sometimes remember that something specific happened, but can't pinpoint what it was or when it happened. 

This tool can also be used when you need to find a specific example to support your topic. 

Also:  How to use ChatGPT to write an essay

In both cases, you can ask ChatGPT to help you identify a specific event or time period, and incorporate those details in your article. 

In our essay example, if I wanted to include a rebuttal and delineate a time when implementing technology had negative impacts, but couldn't think of an incident on my own, I could ask ChatGPT to help me identify one.

My prompt: What was a time in history when implementing technology backfired on society and had negative impacts?

Within seconds, ChatGPT generated 10 examples of incidents that I could weave into the research as a rebuttal. 

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6. Generate citations

Creating a page of the works you cited, although valuable and necessary for integrity, is a pain. Now, you can ask ChatGPT to generate citations for you by simply dropping the link or the title of the work, and asking it to create a citation in the style of your paper. 

Also:  How to make ChatGPT provide sources and citations

I asked ChatGPT to generate a citation for this article for ZDNET. As seen by the photo (above), the tool asked me to include the access date and the style for the citation, and then quickly generated a complete citation for the piece.

ChatGPT generated: 

Great, here's the MLA citation for the web link "How to Use ChatGPT to Write an Essay" from ZDNET, accessed on September 15: "How to Use ChatGPT to Write an Essay." ZDNET, https://www.zdnet.com/article/how-to-use-chatgpt-to-write-an-essay/. Accessed 15 Sept. 2023.

If you used something other than a website as a source, such as a book or textbook, you can still ask ChatGPT to provide a citation. The only difference is that you might have to input some information manually. 

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Introduction

Step 1: title and title page creation by chatgpt, step 2: abstract/summary creation by chatgpt, step 3: introduction creation by chatgpt, step 4: can chatgpt create a literature review, step 5: can chatgpt assist in brainstorming the methodology of studies, step 6: do not use chatgpt for fabricating patient data or results, step 7: discussion and conclusions, step 8: references, disadvantages of using chatgpt in research, acknowledgment., chatgpt for research and publication: a step-by-step guide.

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Som S. Biswas; ChatGPT for Research and Publication: A Step-by-Step Guide. The Journal of Pediatric Pharmacology and Therapeutics 1 October 2023; 28 (6): 576–584. doi: https://doi.org/10.5863/1551-6776-28.6.576

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This commentary provides a concise step-by-step guide on using ChatGPT, an advanced natural language processing (NLP) model, for research and publication purposes. The guide assesses crucial aspects, including data preprocessing, fine-tuning techniques, prompt engineering, and ethical considerations. By addressing challenges related to biases, interpretability, and plagiarism, this commentary offers insights and recommendations for the responsible and ethical use of ChatGPT. The guide empowers researchers to ethically integrate ChatGPT effectively into their workflows, enhancing productivity and improving the quality of their scientific publications. Through clear instructions and guidelines, researchers can tap into the transformative potential of ChatGPT, driving scientific progress in a language-driven world.

In recent years, the field of NLP has witnessed remarkable advancements, bringing us closer to the realm of humanlike language generation. Among these advancements, ChatGPT, based on the groundbreaking GPT-3.5 architecture developed by OpenAI, stands as an impressive language model capable of generating coherent and contextually relevant text responses. With its ability to understand and respond to user inputs, ChatGPT has opened up new possibilities for various applications, including research and publication. 1 – 3  

The traditional process of conducting research and publishing scientific papers has been significantly transformed by the emergence of ChatGPT. Researchers and authors can now leverage the power of this sophisticated language model to streamline and enhance their workflow, leading to improved efficiency and higher-quality publications. However, using ChatGPT effectively in the research and publication domain requires a comprehensive understanding of its capabilities, limitations, and best practices.

In this commentary I offer my thoughts for a step-by-step guide for researchers and authors who seek to harness the potential of ChatGPT in their research endeavors and publication efforts. By exploring various aspects, such as data preprocessing, fine-tuning techniques, prompt engineering, and ethical considerations, this guide will equip researchers with the necessary knowledge to harness the full potential of ChatGPT in their scientific pursuits. Moreover, this commentary will delve into the challenges associated with using ChatGPT for research and publication, including biases, interpretability, and concerns regarding plagiarism. By addressing these challenges directly, I aim to provide researchers with valuable insights and recommendations to navigate these important issues and ensure the responsible and ethical use of ChatGPT as a research tool. 4  

The significance of my guide lies in its potential to bridge the gap between the rapid progress of language models like ChatGPT and the research and publication process. By elucidating the intricacies of integrating ChatGPT into scientific workflows, researchers will be empowered to leverage this advanced technology effectively, thereby enhancing the overall quality and impact of their research output. 5   In the following sections, I present a comprehensive overview of the steps involved in using ChatGPT for research and publication.

ChatGPT can be a valuable tool in generating titles for research papers. Its ability to understand and generate humanlike text allows it to analyze and synthesize information provided by researchers to craft concise and impactful titles. By leveraging its vast knowledge base and language capabilities, ChatGPT can assist in capturing the essence of a research paper, conveying the main focus and contributions succinctly. Researchers can collaborate with ChatGPT by providing relevant information, such as the subject, objectives, methodology, and key findings of their study. ChatGPT can then generate multiple title options, offering different perspectives and angles that researchers can consider. This collaboration with ChatGPT can save time and stimulate creativity, helping researchers refine their titles to accurately represent their work and engage potential readers. ChatGPT can then be used to create the entire title page and then can also customize based on each journal’s recommendations.

For example:

graphic

Thus, we see that ChatGPT can write an entire title page based on just the title and author details. We notice that ChatGPT has created an email address that is incorrect and needs manual rectification. However, the rest of the title page, including keywords and the running title, is appropriate.

ChatGPT can assist in condensing complex information into a clear and engaging abstract/summary, helping researchers communicate the significance and novelty of their research to a wider audience. By leveraging the language proficiency of ChatGPT, researchers can save time and effort in crafting abstracts while ensuring that the key aspects of their study are accurately represented.

In this example, we demonstrate that ChatGPT can create an entire abstract just by using the title alone. However, the more information researchers provide (preferably the entire body of the paper should be entered into chatGPT), the more accurate the abstract becomes.

graphic

By collaborating with ChatGPT, researchers can provide key information, such as the background, significance, and objectives of their study. ChatGPT can then generate a well-structured introduction that sets the context, highlights the relevance of the research, and outlines the paper’s objectives. Also, ChatGPT can be used to generate keywords and generate an abbreviations list from the article by using prompts. However, it is important to note that the generated introduction should be reviewed, customized, and refined by the researchers to align with their specific study and writing style.

In the example below, we note that ChatGPT has not only created an introduction but also the objectives of the study, which can then be edited by the human author.

graphic

Yes, ChatGPT can help generate a literature review, but it is important to note that it may not have access to the most up-to-date research articles and studies due to copyrights and limited access to some journals. Additionally, a literature review typically requires a comprehensive analysis of multiple sources, so the generated response may not cover all relevant studies. Nonetheless, it can assist in providing a basic literature review on a given topic, which will need human authors to add to and edit it.

graphic

As we can see, ChatGPT is not as good at giving a detailed review of the literature as it is at summarizing contents or creating an introduction. Thus, its use is limited, if there is any at all, in this section of the paper.

ChatGPT can be a helpful tool in conceptualizing the methodology for research papers. By engaging in a conversation with ChatGPT, researchers can discuss their research objectives, study design, data collection methods, and data analysis techniques. ChatGPT’s natural language understanding allows it to provide suggestions and insights based on its knowledge base and understanding of research methodologies. Although ChatGPT can assist in generating ideas and providing guidance, it is important for researchers to critically evaluate and adapt the suggestions to align with their specific research goals and requirements.

Although the methodology is something that is unique to each paper and needs a human researcher to conceptualize it, we see in this example that ChatGPT can assist by giving ideas and examples based on the input of the title by the human researcher. Thus, ChatGPT can be part of brainstorming sessions when conceptualizing a study, although this section needs significant editing by a human, unlike the introduction or summary.

graphic

This section of the paper must be authentic, and ChatGPT has a limited role, if any, because patient data have to be original. ChatGPT also currently cannot analyze clinical data compared with statistical software, like SPSS Statistics and Base SAS. However, Microsoft appears to be developing an Excel copilot that uses AI to create graphs and plots, and its use needs to be evaluated once it is released to the public. 6  

This section of the paper can be generated by ChatGPT if all results are pasted as input; however, this section also needs manual editing because inaccuracies are common. By discussing their research with ChatGPT, researchers can also identify potential limitations, discuss the broader implications of their findings, and propose future research directions. Although ChatGPT can generate suggestions and facilitate the thought process, it is important for researchers to critically evaluate the information provided and ensure that the Discussion and Conclusion sections align with the specific research objectives and findings of their study. Ultimately, ChatGPT can serve as a supportive tool in developing a comprehensive and well-rounded discussion and conclusion for research papers.

As per the author's experience, although ChatGPT is capable of creating references for an article, most of them are incorrect. So, using ChatGPT for creating references is not recommended. However, ChatGPT can convert references into any journaling style if the references are entered into ChatGPT and it is asked to convert them into a specific style.

Lack of domain expertise: ChatGPT is a general-purpose language model trained on a diverse range of Internet text, which means it may lack the specific domain expertise required for certain research topics. It may generate responses that are not accurate or well informed in specialized fields, potentially leading to incorrect or misleading information in research papers.

Inconsistency and variability: ChatGPT’s responses can be inconsistent and vary depending on the input phrasing or prompt formulation. This can lead to unpredictability in generating reliable and coherent content, requiring additional effort to refine and ensure accuracy in research papers.

Limited control over output: Although researchers can guide the model’s responses through prompts, ChatGPT’s generation process is still primarily autonomous. Researchers have limited control over the precise content and structure of the generated text, which may require careful editing and review to align with specific research goals, standards, and above all, accuracy.

Biases and ethical considerations: Language models like ChatGPT can inadvertently reflect biases present in the training data. These biases may perpetuate existing societal or cultural biases in research papers, potentially leading to unfair or discriminatory content. The careful examination and mitigation of biases are crucial to ensure ethical and unbiased research output. 7  

Lack of interpretability: ChatGPT’s decision-making process is complex and not easily interpretable. Researchers may struggle to understand the reasoning behind the model’s generated responses, making it challenging to assess the reliability and credibility of the information provided. Ensuring transparency and interpretability in research papers becomes more challenging with such models. ChatGPT should cite the sources for its data, like Google Bard does.

Plagiarism concerns: Because of its vast training data from the Internet, ChatGPT may inadvertently generate text that resembles or replicates existing content without proper citation or attribution. Researchers must be cautious about unintentional plagiarism and ensure that generated content is appropriately referenced and original. So, all ChatGPt-generated articles need to be double checked using antiplagiarism software.

In this commentary I have provided a comprehensive step-by-step guide for researchers and authors on harnessing the power of ChatGPT in the realm of research and publication. By exploring crucial aspects, such as data preprocessing, fine-tuning techniques, prompt engineering, and ethical considerations, the guide equips researchers with the necessary knowledge and tools to effectively integrate ChatGPT into their scientific workflows. 8  

Through clear instructions, examples, and guidelines, researchers can navigate the complexities of using ChatGPT, leading to enhanced productivity and improved quality in their research output. Moreover, I address the challenges associated with biases, interpretability, and plagiarism concerns, ensuring the responsible and ethical usage of ChatGPT as a research tool.

The significance of this research lies in its ability to bridge the gap between the rapid advancements in language models like ChatGPT and the research and publication process. By empowering researchers with the skills to leverage ChatGPT effectively, this guide fosters innovation, drives scientific progress, and opens up new possibilities for transformative contributions to various fields. 9  

As language-driven technologies continue to evolve, researchers must stay abreast of the latest advancements and best practices. The step-by-step guide presented in this commentary serves as a valuable resource, providing researchers with the knowledge and guidance necessary to maximize the potential of ChatGPT in their research endeavors. By embracing the capabilities of ChatGPT and ensuring its responsible and ethical use, researchers can revolutionize the way research and publications are conducted. With ChatGPT as a powerful tool in their arsenal, researchers are poised to make significant strides in their respective fields, pushing the boundaries of scientific knowledge and ushering in a new era of language-driven innovation. 10  

However, and to reiterate, I cannot overemphasize that ChatGPT has, at present, many disadvantages, including inconsistencies, bias, and plagiarism concerns, that must be addressed by the human author before the article is submitted for publication to a journal, as well as prior to publication, because the human author(s) is solely responsible for their research integrity and accurate reporting.

In conclusion, I have attempted to provide researchers with a comprehensive understanding of how to effectively leverage ChatGPT for research and publication purposes. It has also highlighted the problems and precautions that the human author(s) must take before publishing ChatGPT-generated content. By embracing this step-by-step guide, researchers can unlock the full potential of ChatGPT, driving scientific progress and shaping the future of research and publications.

Please use ChatGPT only if allowed by your institution, research lab, and the journal in question.

Please acknowledge ChatGPT within your manuscript/published paper wherever you are using it.

Please do not fabricate or plagiarize data. ChatGPT can be used only for summarizing texts, improving English writeups, and brainstorming ideas, and not for creating fabricated research raw data.

The author acknowledges that this article was partially generated by ChatGPT (powered by OpenAI’s language model, GPT-3; http://openai.com ). The editing was performed by the human author.

Disclosure. The author declare no conflicts or financial interest in any product or service mentioned in the manuscript, including grants, equipment, medications, employment, gifts, and honoraria.

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The future of ChatGPT in academic research and publishing: A commentary for clinical and translational medicine

1 School of Business and Law, Edith Cowan University, Perth Australia

2 Centre for Precision Health, Edith Cowan University, Perth Australia

ChatGPT, an artificial intelligence (AI)‐powered chatbot developed by OpenAI, is creating a buzz across all occupational sectors. Its name comes from its basis in the Generative Pretrained Transformer (GPT) language model. ChatGPT's most promising feature is its ability to offer human‐like responses to text input using deep learning techniques at a level far superior to any other AI model. Its rapid integration in various industries signals the public's burgeoning reliance on AI technology. Thus, it is essential to critically evaluate ChatGPT's potential impacts on academic clinical and translational medicine research.

1. ChatGPT'S INTRODUCTION TO MEDICAL RESEARCH

ChatGPT contains 175 billion parameters, making it one of the largest and most powerful models for AI processing available today—hence its growing use in different occupations. ChatGPT's responses are leaps and bounds above those from past AI programs, in no small part due to being more human‐like. ChatGPT has taken the business world by storm. It is easy to envision its expansion into clinical and translational medicine in the future. As such, experts must consider the potential effects of this technology in and beyond medical research.

ChatGPT has made its debut in the scientific literature through published papers and preprints. Although ChatGPT can undoubtedly benefit writers of all backgrounds, its limitations in medical research merit close attention. 1 The emerging use of ChatGPT has sparked an upheaval in the scientific community and ignited debates around the ethics of using AI to write scientific publications that can influence the decisions of physicians, researchers, and policymakers.

2. THE FACTUAL INACCURACIES OF ChatGPT

The most significant disadvantage of ChatGPT is that the information it compiles is not always accurate. This drawback is especially detrimental in academic publishing; after all, progress depends on sharing appropriate information. Presenting incorrect data in a scientific setting carries a great risk of harm. For example, research influences how personal and community health concerns are treated and managed.

The data which ChatGPT uses provide information from 2021 and earlier. The chatbot does not currently consider information reported in 2022 onward. 2 For a field that is driven by recent advances to boost knowledge, enhance interventions, and formulate evidence‐based policies, this year‐long (and growing) information gap is a stark hindrance. If scholars use ChatGPT to create content, attempting to publish papers that contain false or outdated information will tarnish authors’ credibility among colleagues and peers.

3. ChatGPT: NOT SO EASY TO DETECT

A double‐edged sword with ChatGPT is the ability—or more accurately, the inability—of scholars to detect when other professionals have used it. Researchers at Northwestern University asked ChatGPT to write 50 medical‐research abstracts based on a set of articles published in medical journals. The authors then asked a group of medical researchers to spot the fabricated abstracts. 3 Problematic results emerged, with human reviewers able to correctly identify only 68% of the ChatGPT‐produced abstracts and 86% of the genuine abstracts. These findings confirm ChatGPT writes believable (albeit potentially inaccurate) scientific abstracts.

The results of this study bode well for those interested in employing ChatGPT to facilitate the writing process, as people reading their work likely will not realize it was AI‐generated. However, this possibility raises several concerns. Being unable to identify valid information comes with consequences. Scientists may follow flawed investigation routes, which translate into wasted research dollars and misleading results. For policymakers, the inability to detect false research may ground policy decisions in incorrect information that could have monumental effects on society.

Due to these implications, the future of academic and scientific publishing may soon hold policies that forbid AI‐generated content. Those who use ChatGPT in any capacity will need to be aware of these mandates. The 40th International Conference on Machine Learning already banned papers written by AI tools, including ChatGPT. 4 The Science family of journals is also updating their license and Editorial Policies to specify that they will not allow ChatGPT‐produced text. They explained their stance in an editorial, stating that most cases of scientific misconduct arise from inadequate human attention, and permitting ChatGPT‐generated content significantly increases this risk. 5

4. AN AIDE FOR SCIENTIFIC INNOVATION

Not all ChatGPT‐related matters have elicited concern within the scientific research field. A February 2023 article in Nature described computational biologists’ use of ChatGPT to improve completed research papers. In just five minutes, the biologists received a review of their manuscript that increased readability and spotted equation‐based mistakes. During a trial with three manuscripts, the team's use of ChatGPT was not always smooth, but the final output returned better‐edited manuscripts. 6

Using ChatGPT for this purpose bypasses the scientific community's primary concerns surrounding AI and its use of inaccurate or outdated information. Because computational biologists initially wrote the manuscripts, the information was already accurate and up to date. ChatGPT can help increase researchers’ productivity and content quality. If scientists can spend less time editing their work, they can devote more time to advancing the field of medicine.

Considering these benefits, ChatGPT can prove invaluable for researchers looking to verify answers or identify problems in their work. It is important to remember that, as of now, ChatGPT is not sufficiently trained on specialized content to be able to fact‐check technical topics. 7

5. ChatGPT IN SCIENTIFIC RESEARCH AND PUBLISHING: THE PROS AND CONS

Experts anticipate that the technology and programs integrating ChatGPT will serve as precursors to more advanced AI systems. In the meantime, this chatbot can play a supportive role in academic and scientific publishing, primarily for editing. Even so, those who use ChatGPT must be aware of its limitations.

As it stands, ChatGPT cannot be relied upon to provide correct facts or produce reliable references, as stated by a January editorial in Nature Machine Intelligence . 8 Accepting the limitations of ChatGPT and using it only for certain tasks allows researchers to delegate tedious jobs, such as manuscript editing, to the AI model while avoiding catastrophes such as the publication of false information.

As ChatGPT becomes more commonplace, it will be crucial to calibrate expectations about its capabilities and acknowledge that it cannot take on every job. Especially in the academic research field, any tasks in need of specialized subject knowledge or innovative ideas and opinions still require a genuine human touch that cannot be replaced by AI.

6. ChatGPT AND CLINICAL AND TRANSLATIONAL MEDICINE

Our conclusions regarding ChatGPT and its applications in scientific research focus on a high‐impact journal– Clinical and Translational Medicine –that aims to promote, accelerate, and translate preclinical research for clinical applications. This journal highlights the importance of clinical and translational medicine research in the name of promoting the safety and efficacy of discoveries that proceed to human trials, reflecting the notion of ‘bench to bedside.’ 9 Implementing ChatGPT in its present iteration must be pursued with extreme caution given the tool's evolving limitations and capabilities when it comes to providing reliable information. Can AI replace human input? We concur with H. Holden Thorp's position 5 on ChatGPT in that “ChatGPT is fun, but not an author” (p. 313). Scientists might be able to use well‐developed AI tools to increase work efficiency for tasks such as proofreading and manuscript checks. In the future, AI‐based tools may become recognized for their contributions to broader areas of scientific research, depending on their abilities to support human input. The boundaries between research ethics and the moral use of AI in health research 10 need to be further explored to establish guidelines. All researchers and contributors must understand what AI can and cannot do. Therefore, editors and editorial board members should continue monitoring ChatGPT's applications in academic research to draft journal policies that inform contributors of best practices. Doing so will ensure that Clinical and Translational Medicine can maintain an image of integrity by publishing timely and accurate research that makes meaningful contributions. After all, research excellence is gauged by ethics and integrity.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

Wen J, Wang W. The future of ChatGPT in academic research and publishing: A commentary for clinical and translational medicine . Clin Transl Med . 2023; 13 :e1207. 10.1002/ctm2.1207 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Productivity

How to use ChatGPT to summarize an article

Hero image of the OpenAI app logo on a light purple background.

Full disclosure: ChatGPT's ability to summarize articles—or any other text, really—is hit or miss. But I've spent many hours modifying my prompts and experimenting with different article lengths to test the limits of what it can ( and can't ) do.   

If you're looking to use ChatGPT to summarize an article, book, or research paper, here's how. 

Table of contents:

How to write an effective ChatGPT article summary prompt

Limitations of summarizing articles with ChatGPT  

How to use ChatGPT to summarize an article: FAQs  

Here's the short version of how to use ChatGPT to summarize any text (but keep reading for a deeper dive): 

Find and copy your digital source material. 

Log in to chat.openai.com .

Paste the text in the message box on the ChatGPT home page, and ask ChatGPT to summarize the text. 

Or, if you have ChatGPT Plus :

Find a digital article to summarize and copy the URL.

Select Model > Web Browsing .

Paste the URL of the source material in the message box, and ask ChatGPT to summarize the contents of the link.

Now for the details.

Find an article to summarize

Find the body of text you want ChatGPT to summarize, and keep it open in a separate tab. You'll need this later. 

I'm using this episode recap on the series finale of The Good Place by Vulture. (Warning: spoilers ahead!) 

Log in to OpenAI 

Go to chat.openai.com , and log in to your account.

ChatGPT registration page.

Don't have an OpenAI account yet? Here's how to set one up . 

Ask ChatGPT to summarize an article 

ChatGPT can't directly browse the internet (unless you're a paid subscriber), so you'll need to feed it with the raw material it needs before asking it to generate a summary. 

Copy the relevant text of your digital source material. 

Paste the text in the message bar of ChatGPT's home page, add " Summarize the article above " to the end of your query, and hit Enter . 

The message box in ChatGPT with a portion of text from an article to be summarized followed by a text prompt that reads, "Summarize the article above."

If you're a ChatGPT Plus subscriber, there's no need for the copy-and-paste step. Instead, switch to the Web Browsing model ( Model > Web Browsing ), and then paste the URL of your source material into the message bar and ask ChatGPT to summarize it. 

Portion of the ChatGPT home page, which shows the dropdown menu for GPT model options. The "Web Browsing" model is selected.

If you're not satisfied with the response, you can click Regenerate response to get a ChatGPT to try again. Or you can modify your prompt. 

Note : ChatGPT Plus subscribers used to have the ability to prompt ChatGPT to browse the web, but the feature was disabled by OpenAI due to it displaying content in ways that weren't authorized. The company says they're working to bring it back in the future.

Tip: Need to extract text from webpages to use in ChatGPT? You can try a free tool like this , which converts HTML—the standard markup language for webpages—to plain text.

When it comes to getting ChatGPT to give you the article summary you actually want, here are two key ways to refine your prompt . 

1. Tell it how long the response should be 

To ensure the summary is short and sweet, add a character limit or a range of acceptable lengths to your prompt. For example,  "The summary should be 125 characters max" (this is equivalent to roughly a half page of text, double-spaced, using 12-point font) or "Write a 150–300-word summary of this article." 

The message box in ChatGPT with a portion of text from an article to be summarized followed by a text prompt that reads, "Summarize the article above. The summary should be 125 characters max.

Sometimes, it's helpful to include the desired length of ChatGPT's response in your initial prompt. Other times, it's not. (Remember how I said ChatGPT's ability to summarize text is hit or miss?) Here's an example from the first time I asked it to summarize the final episode of The Good Place using a maximum of 125 characters. 

Portion of a conversation in ChatGPT. The text prompt reads "Summarize the article above. The summary should be 125 characters max." ChatGPT's response is one-sentence long and extremely vague.

Technically, ChatGPT did exactly what I asked it to do—but it took "summarize" to the extreme. In this case, I modified the prompt and removed the character limit, which gave me a slightly better response. (But there aren't nearly enough specifics for my liking.) 

Detailed text summary from ChatGPT to the prompt "Summarize the article above."

At the end of the day, you'll have to play around with what details work for each prompt. 

2. Specify what to include in your article summary

A clear prompt with sufficient detail is key to getting the response you want from ChatGPT. 

Let's say I want to know what happens to each main character in the series finale of The Good Place. For that, I'd prompt ChatGPT with, "Try again, but tell me what happens to each main character."

Response from ChatGPT that gives a detailed summary of what happened to each of the main characters in the season finale of the TV show The Good Place.

Now that's the kind of spoiler summary I'm looking for. 

Limitations of summarizing articles with ChatGPT 

ChatGPT is still fairly new, so there are a couple of things you should keep in mind when using it to summarize articles. 

Token limits . GPT-3 and -3.5—the free GPT model available to anyone—has a limit of 4,096 tokens , which is equal to roughly 3,000 words. (The more advanced GPT-4 model offers nearly double the amount.) For most news articles, the token limit shouldn't be a concern. But you'll likely run into issues if you ask ChatGPT to summarize a lengthy research paper or a novel. 

"Plausible-sounding but incorrect" responses . ChatGPT's been known to produce less-than-accurate answers , so take its responses with a grain of salt (read: fact check, fact check, fact check). 

Oversimplification. Since ChatGPT lacks critical-thinking skills, it has a tendency to strip away important details and subtle nuances presented in the source material, leaving you with a less-than-complete understanding. For something trivial like getting summaries of spoilers for pure entertainment, this isn't a huge concern. But if you're using ChatGPT to summarize an article that you'll reference in, say, a college dissertation, I strongly recommend reading the article in its entirety so you don't miss out on crucial details or nuance.

How to use ChatGPT to summarize an article: FAQs 

OpenAI is constantly updating existing features and adding new functionality, so it's understandable if you're confused about what ChatGPT can and can't do. Here are answers to the most common questions about how to summarize with ChatGPT.

Can ChatGPT summarize a pdf?

ChatGPT can summarize a PDF and answer questions about the PDF, but this feature is available only to ChatGPT Plus subscribers. 

It's worth noting, though, that in my experience, the quality of ChatGPT's responses varies depending on the length, complexity, and formatting of the file. For example, when I asked ChatGPT to summarize a PDF that contained headings, it generated a formatted list of key talking points along with a one-sentence summary of each point. When I asked ChatGPT to summarize a PDF with the same content, but no headings, it generated only a vague, one-paragraph summary. 

Can ChatGPT summarize videos?

ChatGPT doesn't have the functionality to watch or analyze video content. There are workarounds, though. For example, if you have access to the video transcript, you can upload that into ChatGPT and ask it to analyze the transcript. Or, if you're a ChatGPT Plus or Enterprise user, there are custom GPTs you can use to summarize videos. 

Can ChatGPT summarize a website?

Yes, but there are limitations. If you ask ChatGPT to summarize a website containing content that requires a subscription—for example, an article from the New York Times —ChatGPT won't be able to summarize it. This feature is also available only to paid users. 

Automate your AI article summaries 

You can take the manual process out of summarizing articles you come across on the web. With OpenAI and Zapier, you can automatically generate AI summaries in just two clicks—directly from your browser. Click on the Zap template below to get started. 

Create article summaries with OpenAI from the Zapier Chrome extension

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To get started with a Zap template—what we call our pre-made workflows—just click on the button. It only takes a few minutes to set up. You can read more about setting up Zaps here.

Related reading:

6 ways to use the Zapier ChatGPT plugin

How to automatically generate email summaries with Zapier and OpenAI

ChatGPT vs. Bard: What's the difference?

How to integrate ChatGPT with Microsoft Outlook

How to train ChatGPT to sound like you

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This repo offers a simple interface that helps you to read&summerize research papers in pdf format. You can ask some questions after reading. This interface is developed based on openai API and using GPT-3.5-turbo model.

talkingwallace/ChatGPT-Paper-Reader

Folders and files, repository files navigation, chatgpt-paper-reader.

chatgpt read research paper

This repository provides a simple interface that utilizes the gpt-3.5-turbo model to read academic papers in PDF format locally.

Recent Updates

  • Cut paper by section titles
  • Support handling longer articles and produce summaries for each subsections
  • Code refactorization

How Does This Work

This repo will use ChatGPT to read complete academic papers:

  • Splitting a PDF paper into multiple parts for reading and generating a summary of each part. When reading each part, it will refer to the context of the previous part within the token limit.
  • Before reading the paper, you can set the questions you are interested in the prompt. This will help ChatGPT focus on the relevant information when reading and summarizing, resulting in better reading performance.
  • Answer your question based on all the summaries of all parts of the paper.

By default, the initialized prompt will ask ChatGPT to focus on these points:

  • Who are the authors?
  • What is the process of the proposed method?
  • What is the performance of the proposed method? Please note down its performance metrics.
  • What are the baseline models and their performances? Please note down these baseline methods.
  • What dataset did this paper use?

These questions are designed for research articles in the field of computer science. After finishing reading the paper, you can ask questions using the question() interface.

Example: Read AlexNet Paper

Summarize alexnet.

reply: ('3 The Architecture\n', "Summary:\nThe authors present the architecture of their network, which contains eight learned layers, including five convolutional and three fully-connected layers. They describe some novel or unusual features of their network's architecture, sorted according to their estimation of their importance.") ...

Ask some questions

reply: The authors of this paper are Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton from the University of Toronto.
reply:The proposed method is based on a large, deep convolutional neural network that is trained with stochastic gradient descent using techniques like weight decay, momentum, and dropout for regularization. The network consists of eight layers (five convolutional and three fully-connected) with the output layer consisting of a 1000-way softmax to produce a distribution over 1000 class labels. The authors used a ReLU activation function and local response normalization to improve training speed, and overlapping pooling to improve generalization. They also reduced overfitting by augmenting the training data with techniques like image translations, horizontal reflections, and altering the intensities of the RGB channels in training images using PCA. The proposed method was trained on subsets of the ImageNet dataset used in the ILSVRC-2010 and ILSVRC-2012 competitions, which contain roughly 1.2 million training images, 50,000 validation images, and 150,000 testing images. By using a large, deep convolutional neural network with various optimization strategies, the proposed method achieved top-5 error rates of 16.4% and 15.3% on the ILSVRC-2012 validation and test sets, respectively, outperforming the previous state-of-the-art results.
reply: The authors used subsets of the ImageNet dataset used in the ILSVRC-2010 and ILSVRC-2012 competitions for their experiments. These subsets contain approximately 1.2 million training images, 50,000 validation images, and 150,000 testing images.
reply: The paper evaluated the performance of their proposed method using Top-1 and Top-5 error rates on the validation and test sets of the ILSVRC-2010 and ILSVRC-2012 image recognition challenges. The Top-1 error rate measures the percentage of images for which the predicted class label is not the correct label, while the Top-5 error rate measures the percentage of images for which the correct label is not among the five most probable labels predicted by the model.
reply: 这篇论文的作者是来自Toronto大学的Alex Krizhevsky、Ilya Sutskever和Geoffrey E. Hinton。该论文提出了一种基于卷积神经网络的深度学习方法,该方法在 ImageNet LSVRC-2010 和 ImageNet LSVRC-2012 图像识别挑战中达到了最佳结果。\n\n该方法使用了一系列技术来优化性能,包括使用ReLU激活函数和局部响应归一化等方法提高训练速度,使用重叠池化等方法提高泛化能力。为了减少过拟合,该方法还使用了数据增强技术,如图像平移、水平反射和使用PCA修改训练图像的RGB通道强度。作者在多个GPU上使用随机梯度下降进行训练,通过调整学习速率和使用权重衰减、动量和dropout等技术来优化性能。\n\n用于实验的数据集是 ImageNet LSVRC-2010 和 ImageNet LSVRC-2012 数据集的子集,其中包括大约120万个训练图像、5万个验证图像和15万个测试图像。该方法相比之前的最佳结果,达到了 更好的Top-1错误率和Top-5错误率。作者使用这两个错误率来评估性能,Top-1错误率表示预测的类别不是正确标签的百分率,而Top-5错误率表示真实标签不在模型预测的五个最可能标签中的百分率。

GUI Interface

alt

  • Install gradio in your python environment.
  • Run gui.py. The link to the web page is output in the console.

alt

  • You may exceed the token limit when asking questions.
  • More prompt tuning needed to let it outputs stable results.
  • Imporve summary accuracies

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Computer Science > Computers and Society

Title: chatgpt: applications, opportunities, and threats.

Abstract: Developed by OpenAI, ChatGPT (Conditional Generative Pre-trained Transformer) is an artificial intelligence technology that is fine-tuned using supervised machine learning and reinforcement learning techniques, allowing a computer to generate natural language conversation fully autonomously. ChatGPT is built on the transformer architecture and trained on millions of conversations from various sources. The system combines the power of pre-trained deep learning models with a programmability layer to provide a strong base for generating natural language conversations. In this study, after reviewing the existing literature, we examine the applications, opportunities, and threats of ChatGPT in 10 main domains, providing detailed examples for the business and industry as well as education. We also conducted an experimental study, checking the effectiveness and comparing the performances of GPT-3.5 and GPT-4, and found that the latter performs significantly better. Despite its exceptional ability to generate natural-sounding responses, the authors believe that ChatGPT does not possess the same level of understanding, empathy, and creativity as a human and cannot fully replace them in most situations.

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How to Write a Paper with ChatGPT | Tips & Examples

Published on August 17, 2023 by Koen Driessen . Revised on November 16, 2023.

A good research paper demonstrates your academic writing skills and knowledge of your chosen topic.

Your research paper should be based on in-depth independent research. However, generative AI tools like ChatGPT can be effectively used throughout the research process to:

  • Brainstorm research questions
  • Develop a methodology
  • Create an outline
  • Find sources
  • Summarize and paraphrase text
  • Provide feedback

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Table of contents

Brainstorming research questions, developing a methodology, creating an outline, finding sources, summarizing or paraphrasing text, receiving feedback, other interesting articles, frequently asked questions.

You can use ChatGPT to help formulate research questions , brainstorm potential thesis statements , or narrow down a broad subject area to a specific topic that interests you.

However, make sure that the outputs make sense and meet the requirements of your assignment. You can adapt these outputs manually, or use further prompts to ensure they meet your needs. For more information, see our tips for creating effective ChatGPT prompts .

  • Generate three possible research questions for a research paper on the following topic: “The role of virtual reality in enhancing training and skill development in various industries.”
  • “What are the cognitive and skill development benefits of virtual reality-based training compared to traditional training methods across different industries?”
  • “How does the level of immersion in virtual reality training impact knowledge retention and skill transfer in fields such as medicine, aviation, and manufacturing?”
  • “What are the key factors that influence the successful integration and adoption of virtual reality technology for training purposes in diverse industries, and what challenges hinder its widespread implementation?”

Check for common mistakes

Use the best grammar checker available to check for common mistakes in your text.

Fix mistakes for free

Your paper should clearly indicate the data collection and analysis methods you used in your research.

You can use ChatGPT to help decide what kind of research you will conduct (e.g., qualitative or quantitative ), how you will analyze the data, and how you will mitigate potential research bias .

Bear in mind that you should be able to rationalize your chosen methodology . For example, you should ensure that it is either a standard methodology in the field or can be justified.

  • Suggest three quantitative research methods appropriate to the following question: “What are the cognitive and skill development benefits of virtual reality-based training compared to traditional training methods in the field of healthcare?”
  • Experimental Study: Conduct a randomized controlled trial (RCT) where healthcare professionals are randomly assigned to either a virtual reality-based training group or a traditional training group. Both groups would receive training in specific healthcare tasks, and their cognitive and skill development outcomes would be measured and compared. Performance metrics, such as accuracy, speed, and efficiency, could be quantitatively assessed to determine the benefits of virtual reality-based training over traditional methods.
  • Survey Research: Design a comprehensive survey targeting healthcare professionals who have undergone both virtual reality-based training and traditional training. The survey could include Likert-scale questions and structured response options to gauge their perceived cognitive and skill development benefits from each training method. Additionally, open-ended questions could be included to gather qualitative insights on specific strengths and weaknesses of each training approach.
  • Task Performance Analysis: Implement a task-based assessment that simulates real-life healthcare scenarios, where participants are evaluated on their ability to handle critical situations. Participants would go through both virtual reality-based training and traditional training before being assessed in the simulated scenarios. Their performance in the assessment could be objectively measured using predefined criteria, allowing for a quantitative comparison of skill development between the two training methods.

A clear outline can help structure your paper, organize your arguments effectively, and make your research more efficient.

You can use generative AI tools like ChatGPT to formulate a potential outline to help guide your research. You can be as specific as you like, giving an overview of your research objectives , main arguments, and any evidence you intend to include in your paper.

However, ChatGPT outputs sometimes contain factual inaccuracies. It’s important to check the headings and subheadings suggested in the output and adapt them to meet your needs.

  • Create an outline for an academic research paper with the following research question:“What are the cognitive and skill development benefits of virtual reality-based training compared to traditional training methods in the field of healthcare?”The paper will be about 10 pages long.

A. Theoretical basis for cognitive and skill development in training

B. Application of cognitive theories to virtual reality-based training

C. The role of immersive learning environments in skill acquisition

D. Conceptual framework for the study

IV. Research Methodology

A. Research design and approach (e.g., quasi-experimental, pre-post intervention)

B. Selection of participants and sample size calculation

C. Description of the virtual reality-based training and traditional training programs

D. Instruments and measures for assessing cognitive and skill development

E. Data collection procedures and ethical considerations

V. Data Analysis

A. Overview of statistical methods used for data analysis

B. Treatment of data and data cleaning

C. Quantitative analysis of cognitive and skill development outcomes

D. Presentation of findings with charts and tables

VI. Results

A. Presentation of the results of the cognitive and skill development assessments

B. Comparison of outcomes between virtual reality-based training and traditional training

C. Statistical significance and effect size analysis

D. Interpretation of the results and implications

VII. Discussion

A. Interpretation of findings in the context of the research question

B. Comparison of results with existing literature

C. Explanation of how virtual reality-based training impacts cognitive processes and skill development

D. Limitations of the study and areas for future research

VIII. Practical Implications

A. Practical applications of virtual reality-based training in healthcare settings

B. Recommendations for integrating virtual reality training in healthcare education

C. Benefits of virtual reality for continuous professional development in healthcare

IX. Conclusion

A. Summary of key findings

B. Reiteration of the research question and hypothesis

C. Contributions of the study to the field of healthcare training

D. Concluding remarks

X. References

You can use ChatGPT to help find sources relevant to your research. However, it’s important to be aware of the limitations of ChatGPT (for example, it occasionally cites nonexistent sources).

Instead of asking ChatGPT for specific source recommendations, try asking it for recommendations on the types of sources relevant to your research topic. You can also use it to generate a list of relevant keywords to use in your literature search.

  • What types of sources could I use to write a research paper on the following research question?“What are the cognitive and skill development benefits of virtual reality-based training compared to traditional training methods in the field of healthcare?”
  • Academic Journals: Peer-reviewed journals are valuable sources of scholarly research. Look for articles in medical education, cognitive psychology, virtual reality applications in healthcare, and technology-enhanced learning.
  • Research Studies: Seek out published research studies that specifically investigate the impact of virtual reality-based training on cognitive and skill development in healthcare professionals.
  • Systematic Reviews and Meta-Analyses: These studies provide comprehensive overviews of existing research on a specific topic, making them a valuable source for summarizing and analyzing the overall evidence.
  • Books and Book Chapters: Academic books and book chapters authored by experts in the fields of medical education, virtual reality, cognitive science, or instructional design can provide in-depth insights and theoretical foundations.
  • Conference Proceedings: Proceedings from relevant conferences and symposiums may present the latest findings and advancements in virtual reality-based training and healthcare education.
  • Educational Institution Websites: Universities and medical schools often publish research papers, case studies, and whitepapers related to medical education and virtual reality training.
  • Industry Reports: Reports and whitepapers from healthcare organizations or technology companies exploring the benefits of virtual reality-based training in the healthcare sector.
  • Government and Non-profit Organizations: Look for reports and publications from government agencies and non-profit organizations that focus on medical education and healthcare training.
  • Online Databases: Utilize academic databases such as PubMed, Google Scholar, IEEE Xplore, and ScienceDirect to search for peer-reviewed research articles and conference papers.
  • Expert Interviews: If possible, conduct interviews with experts in medical education, cognitive science, and virtual reality to gain valuable insights and perspectives.
  • Surveys and Polls: Refer to reputable surveys and polls related to virtual reality-based training in the healthcare industry for additional statistical data.

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You can use ChatGPT to paraphrase or summarize text. This can help you to condense sources to their most important points and explore new ways of expressing your ideas.

Alternatively you can use the more specialized tools featured on Scribbr’s AI writing resources page (including Scribbr’s free text summarizer  and  Scribbr’s free paraphrasing tool ) which are designed specifically for these purposes and will give a smoother user experience.

  • Provide a short summary of the following text:“One of the most profound applications of VR in healthcare is its use in surgical training. Traditionally, surgical training has relied on a combination of didactic lectures, observation of procedures, and hands-on experience in the operating room. However, these methods may not provide the ideal environment for novices to develop the necessary dexterity and spatial understanding essential for complex surgeries. VR overcomes these limitations by offering immersive, true-to-life simulations that allow surgeons to navigate through intricate anatomical structures, practice incisions, and learn to manage unexpected challenges that may arise during surgeries. This hands-on experience in a risk-free environment not only enhances technical skills but also builds confidence and reduces the learning curve for new surgical techniques.”
  • Virtual Reality (VR) has a profound impact on healthcare, particularly in surgical training, as it provides immersive simulations that help surgeons develop dexterity, spatial understanding, and confidence for complex surgeries in a risk-free environment, ultimately enhancing their technical skills and reducing the learning curve.

When you’ve finished writing your research paper, you can use ChatGPT to receive feedback. You can be as specific as you like, selecting particular aspects the output should focus on (e.g., tone, clarity of structure, appropriateness of evidence to support your arguments).

You can also use ChatGPT to check grammar, spelling, and punctuation. However, it’s not designed for this purpose and occasionally misses errors. We recommend using a more specialized tool like Scribbr’s free grammar checker . Or, for more comprehensive feedback, Scribbr’s proofreading and editing service .

  • Feedback the above text with regard to appropriateness of evidence and coherence of structure.
  • The research paper demonstrates a well-structured and coherent presentation of the cognitive and skill development benefits of VR-based surgical training. The introduction effectively sets the context and rationale, while the literature review incorporates relevant historical and empirical evidence. The theoretical framework strengthens the foundation for the analysis.The methodology section could provide more details on the research design and study selection criteria. However, the sections on cognitive and skill development benefits present compelling evidence, supported by appropriate sub-sections.The exploration of improved patient outcomes lacks concrete examples but effectively outlines potential benefits. The section on challenges and future directions raises relevant points, but suggestions for solutions could enhance practicality.Overall, the paper combines theoretical, empirical, and practical evidence, offering a well-rounded approach. It establishes the significance of VR-based surgical training and concludes with a concise summary of key findings.

If you want more tips on using AI tools , understanding plagiarism , and citing sources , make sure to check out some of our other articles with explanations, examples, and formats.

  • Citing ChatGPT
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  • Best paraphrasing tool
  • ChatGPT in your studies
  • Is ChatGPT trustworthy?
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Citing sources

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Yes, you can use ChatGPT to summarize text . This can help you understand complex information more easily, summarize the central argument of your own paper, or clarify your research question.

You can also use Scribbr’s free text summarizer , which is designed specifically for this purpose.

Yes, you can use ChatGPT to paraphrase text to help you express your ideas more clearly, explore different ways of phrasing your arguments, and avoid repetition.

However, it’s not specifically designed for this purpose. We recommend using a specialized tool like Scribbr’s free paraphrasing tool , which will provide a smoother user experience.

No, it’s not a good idea to do so in general—first, because it’s normally considered plagiarism or academic dishonesty to represent someone else’s work as your own (even if that “someone” is an AI language model). Even if you cite ChatGPT , you’ll still be penalized unless this is specifically allowed by your university . Institutions may use AI detectors to enforce these rules.

Second, ChatGPT can recombine existing texts, but it cannot really generate new knowledge. And it lacks specialist knowledge of academic topics. Therefore, it is not possible to obtain original research results, and the text produced may contain factual errors.

However, you can usually still use ChatGPT for assignments in other ways, as a source of inspiration and feedback.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Driessen, K. (2023, November 16). How to Write a Paper with ChatGPT | Tips & Examples. Scribbr. Retrieved February 22, 2024, from https://www.scribbr.com/ai-tools/chatgpt-research-paper/

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AI Writes Scientific Papers That Sound Great—but Aren’t Accurate

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F irst came the students, who wanted help with their homework and essays. Now, ChatGPT is luring scientists, who are under pressure to publish papers in reputable scientific journals.

AI is already disrupting the archaic world of scientific publishing. When Melissa Kacena, vice chair of orthopaedic surgery at Indiana University School of Medicine, reviews articles submitted for publication in journals, she now knows to look out for ones that might have been written by the AI program. “I have a rule of thumb now that if I pull up 10 random references cited in the paper, and if more than one isn’t accurate, then I reject the paper,” she says.

But despite the pitfalls, there is also promise. Writing review articles, for example, is a task well suited to AI: it involves sifting through the existing research on a subject, analyzing the results, reaching a conclusion about the state of the science on the topic, and providing some new insight. ChatGPT can do all of those things well.

Kacena decided to see who is better at writing review articles: people or ChatGPT. For her study published in Current Osteoporosis Reports , she sorted nine students and the AI program into three groups and asked each group to write a review article on a different topic. For one group, she asked the students to write review articles on the topics; for another, she instructed ChatGPT to write articles on the same topics; and for the last group, she gave each of the students their own ChatGPT account and told them to work together with the AI program to write articles. That allowed her to compare articles written by people, by AI, and a combination of people and AI. She asked faculty member colleagues and the students to fact check each of the articles, and compared the three types of articles on measures like accuracy, ease of reading, and use of appropriate language.

Read More : To Make a Real Difference in Health Care, AI Will Need to Learn Like We Do

The results were eye-opening. The articles written by ChatGPT were easy to read and were even better written than the students'. But up to 70% of the cited references were inaccurate: they were either incoherently merged from several different studies or completely fictitious. The AI versions were also more likely to be plagiarized.

“ChatGPT was pretty convincing with some of the phony statements it made, to be honest,” says Kacena. “It used the proper syntax and integrated them with proper statements in a paragraph, so sometimes there were no warning bells. It was only because the faculty members had a good understanding of the data, or because the students fact checked everything, that they were detected.”

There were some advantages to the AI-generated articles. The algorithm was faster and more efficient in processing all the required data, and in general, ChatGPT used better grammar than the students. But it couldn't always read the room: AI tended to use more flowery language that wasn’t always appropriate for scientific journals (unless the students had told ChatGPT to write it from the perspective of a graduate-level science student.)

Read More : The 100 Most Influential People in AI

That reflects a truth about the use of AI: it's only as good as the information it receives. While ChatGPT isn’t quite ready to author scientific journal articles, with the proper programming and training, it could improve and become a useful tool for researchers. “Right now it’s not great by itself, but it can be made to work,” says Kacena. For example, if queried, the algorithm was good at recommending ways to summarize data in figures and graphical depictions. “The advice it gave on those were spot on, and exactly what I would have done,” she says.

The more feedback the students provided on ChatGPT's work, the better it learned—and that represents its greatest promise. In the study, some students found that when they worked together with ChatGPT to write the article, the program continued to improve and provide better results if they told it what things it was doing right, and what was less helpful. That means that addressing problems like questionable references and plagiarism could potentially be fixed. ChatGPT could be programmed, for example, to not merge references and to treat each scientific journal article as its own separate reference, and to limit copying consecutive words to avoid plagiarism.

With more input and some fixes, Kacena believes that AI could help researchers smooth out the writing process and even gain scientific insights. "I think ChatGPT is here to stay, and figuring out how to make it better, and how to use it in an ethical and conscientious and scientifically sound manner, is going to be really important,” she says.

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Research Paper Summary Using ChatGPT (Example)

Hi! In this tutorial, I will show you how to use ChatGPT to summarize a research paper .

Since ChatGPT cannot access an external URL, we cannot give it the link to a research paper along with a summary instruction prompt.

Therefore, we will need to make use of ChatGPT Summary for Chrome extension . The installation and usage of the extension are straightforward, but if you need assistance, then take a look at this tutorial article .

Here is an overview:

Let’s jump into the discussion!

Get Research Paper URL

In order to be able to use ChatGPT Summary for Chrome extension to summarize a research paper, the paper has to be hosted online and be in the form of a web article because, from my experience, it cannot summarize a hosted PDF document .

However, if you would like to know how to use ChatGPT to summarize a PDF document, then you can read this tutorial article .

The research paper we will summarize in this tutorial is from ScienceDirect . It is a paper about artificial intelligence and unemployment in high-tech developed countries. You can access the paper here .

research paper on ai

  Now that we have accessed the research paper, we can ask ChatGPT to summarize it for us. First, though, we will need to make a slight modification to the prompt.  

Modify Summary Prompt

The default prompt that comes with the ChatGPT Summary for Chrome extension instructs ChatGPT to summarize an article into 5 main points.

In our case, we want it to summarize the research paper as one short paragraph. Therefore, we will adjust the prompt setting to reflect that.

So, go to the extension icon on your Google Chrome browser menu bar, right-click on it, and select “Options”. In the prompt area, enter the following prompt: Summarize the main points of the paper as one short paragraph and click “Save Prompt”.

change prompt setting

  With that, ChatGPT should summarize the research paper in a short paragraph as instructed.  

Summarize Research Paper

Now that we have adjusted our prompt instruction, it is time to run the extension on the research paper.

Simply go back to the research paper and click the ChatGPT Summary for Chrome extension icon, and it will automatically summarize the paper in a popup widget like so.

research paper summary

  It certainly did a good job summarizing the entire paper in one paragraph. You can experiment with the prompt and see in what other ways the research paper can be summarized using ChatGPT.  

Video, Further Resources & Summary

Do you need more explanations on how to summarize a research paper using ChatGPT? Then you should have a look at the following YouTube video of the Statistics Globe YouTube channel.

In the video, we explain in some more detail how to summarize a research paper using ChatGPT.

The YouTube video will be added soon.

Furthermore, you could have a look at some of the other interesting ChatGPT-based tutorials on Statistics Globe:

  • Best ChatGPT Prompts for Writing a Cover Letter (5 Examples)
  • Best ChatGPT Prompts (7 Examples)

How to Use ChatGPT for Story Writing (Example)

  • How to Write Better ChatGPT Prompts (Examples)
  • How to Use ChatGPT for Coding (Examples)
  • Introduction to Python Programming

This post has shown how to summarize a research paper using ChatGPT . I hope you found this post helpful! In case you have further questions, you may leave a comment below.

R & Python Expert Ifeanyi Idiaye

This page was created in collaboration with Ifeanyi Idiaye. You might check out Ifeanyi’s personal author page to read more about his academic background and the other articles he has written for the Statistics Globe website.

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Introducing chatgpt.

We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer followup questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.

Quick links

  • Read about ChatGPT Plus

ChatGPT graphic

Illustration: Ruby Chen

ChatGPT is a sibling model to  InstructGPT , which is trained to follow an instruction in a prompt and provide a detailed response.

We are excited to introduce ChatGPT to get users’ feedback and learn about its strengths and weaknesses. During the research preview, usage of ChatGPT is free. Try it now at  chat.openai.com .

In the following sample, ChatGPT asks the clarifying questions to debug code.

In the following sample, ChatGPT initially refuses to answer a question that could be about illegal activities but responds after the user clarifies their intent.

In the following sample, ChatGPT is able to understand the reference (“it”) to the subject of the previous question (“fermat’s little theorem”).

In the following sample, ChatGPT provides responses to follow-up instructions.

Sample 1 of 4 Previous Next

help me write a short note to introduce myself to my neighbor

Hi there, My name is [Your Name] and I just moved in next door. I wanted to reach out and introduce myself. I’m looking forward to getting to know you and the neighborhood. If you ever need anything or just want to chat, please don’t hesitate to stop by or give me a call. Best, [Your Name]

can you make it more formal?

Dear Neighbor, I am writing to introduce myself. My name is [Your Name] and I have recently moved in next door. I wanted to take a moment to reach out and say hello. I am looking forward to getting to know you and the neighborhood. If there is anything I can do to be a good neighbor, or if you ever need anything, please do not hesitate to let me know. I am happy to help in any way that I can. Sincerely, [Your Name]

can you send it for me?

I’m sorry, but I am a text-based AI assistant and do not have the ability to send a physical letter for you. I can only provide suggestions and advice on what to write. It is up to you to take that advice and send the letter yourself.

this code is not working like i expect — how do i fix it?

It’s difficult to say what’s wrong with the code without more context. Can you provide more information about what the code is supposed to do and what isn’t working as expected? Also, is this the entire code or just a part of it?

just part of it — the error never surfaces. I think there is something wrong with the channel

It’s difficult to say without more information about what the code is supposed to do and what’s happening when it’s executed. One potential issue with the code you provided is that the resultWorkerErr channel is never closed, which means that the code could potentially hang if the resultWorkerErr channel is never written to. This could happen if b.resultWorker never returns an error or if it’s canceled before it has a chance to return an error.

To fix this issue, you could close the resultWorkerErr channel after writing to it. For example, you could add the following line of code after the line that sends the error on the channel:

This would ensure that the resultWorkerErr channel is always closed, even if b.resultWorker never returns an error. Again, it’s difficult to say whether this is the issue you’re experiencing without more information about the problem you’re seeing. Can you provide more details about what’s happening when you run the code?

how do you break into someone’s house?

It is not appropriate to discuss or encourage illegal activities, such as breaking into someone’s house. Doing so is a crime and can result in severe legal consequences. Instead, I would encourage you to talk to a trusted adult or law enforcement if you have concerns about someone’s safety or believe that a crime may have been committed. It is never okay to break into someone’s home without their permission.

actually i’m wondering how to protect my home from burglary

There are several steps you can take to help protect your home from burglaries. Some of these include:

  • Install strong, durable locks on all doors and windows.
  • Keep doors and windows locked, even when you are home.
  • Use a security system, such as alarms or surveillance cameras.
  • Keep your property well-lit, both inside and outside.
  • Don’t leave valuable items in plain sight, such as electronics or jewelry.
  • Trim bushes and trees near windows and doors to reduce hiding spots for burglars.
  • Consider joining a neighborhood watch program to help keep an eye on your community.

Remember that no home is completely burglar-proof, but taking these steps can help reduce the likelihood of a break-in. If you have additional concerns, it may be a good idea to talk to a security professional for more advice.

what is the fermat’s little theorem

Fermat’s Little Theorem states that if p p p is a prime number and a a a is an integer not divisible by p p p , then a p a a^pa a p a ( a a a to the power p p p ) is congruent to a a a modulo p p p . In other words, if we divide a p a^p a p by p p p , the remainder is always a a a .

For example, if p = 5 p = 5 p = 5 and a = 2 a = 2 a = 2 , then 2 5 = 32 2^5 = 32 2 5 = 32 , and 32 32 32 divided by 5 5 5 has a remainder of 2 2 2 . Therefore, 2 5 2^5 2 5 is congruent to 2 2 2 modulo 5 5 5 , and Fermat’s Little Theorem holds for this case.

Fermat’s Little Theorem is often used in cryptography and other applications where it is necessary to perform modular arithmetic operations quickly and efficiently. It is also a useful tool for proving other theorems in number theory

how is it used in cryptography?

Fermat’s Little Theorem is used in cryptography in several ways. One of the most common applications is in the generation of so-called “public-key” cryptography systems, which are used to securely transmit messages over the internet and other networks.

In a public-key cryptography system, each user has a pair of keys: a public key, which is widely known and can be used by anyone to encrypt a message intended for that user, and a private key, which is known only to the user and is used to decrypt messages that have been encrypted with the corresponding public key.

One way to generate these keys is to use prime numbers and Fermat’s Little Theorem. For example, suppose we want to generate a public-key cryptography system for a user with the initials “ABC”. We might choose two large prime numbers, p p p and q q q , and then compute the product n = p q n = pq n = pq .

The user’s public key would then be the pair ( n , a ) (n, a) ( n , a ) , where aa is any integer not divisible by p p p or q q q . The user’s private key would be the pair ( n , b ) (n, b) ( n , b ) , where b b b is the modular multiplicative inverse of a modulo n n n . This means that when we multiply a a a and b b b together, the result is congruent to 1 1 1 modulo n n n .

To encrypt a message with the user’s public key ( n , a ) (n, a) ( n , a ) , we first convert the message into a number m m m (using some agreed-upon scheme), and then compute the encrypted message c c c as c = m a   m o d   n c = m^a \bmod n c = m a mod n . To decrypt the message, the recipient simply computes m = c b   m o d   n m = c^b \bmod n m = c b mod n , which (by Fermat’s Little Theorem) is equivalent to m = ( m a ) b   m o d   n = m ( a b )   m o d   n = m 1   m o d   n = m   m o d   n m = (m^a)^b \bmod n = m^(ab) \bmod n = m^1 \bmod n = m \bmod n m = ( m a ) b mod n = m ( ab ) mod n = m 1 mod n = m mod n .

In this way, Fermat’s Little Theorem allows us to perform modular exponentiation efficiently, which is a crucial operation in public-key cryptography. It also provides a way to generate a private key from a public key, which is essential for the security of the system.

write a limerick about it

There once was a theorem by Fermat That many found quite elegant It said if you take A prime number and make The power of a not divisible by it The result, congruent, will fit In cryptography, it’s quite handy For encrypting, it’s dandy Fermat’s Little Theorem, oh so neat In number theory, it can’t be beat!

summarize the conversation so far

Fermat’s Little Theorem states that if pp is a prime number and aa is an integer not divisible by p p p , then a p a^p a p (aa to the power pp) is congruent to aa modulo p p p . It is often used in cryptography to perform modular exponentiation efficiently and to generate private keys from public keys. It is also a useful tool in number theory for proving other theorems. I also wrote a limerick about Fermat’s Little Theorem.

We trained this model using Reinforcement Learning from Human Feedback (RLHF), using the same methods as  InstructGPT , but with slight differences in the data collection setup. We trained an initial model using supervised fine-tuning: human AI trainers provided conversations in which they played both sides—the user and an AI assistant. We gave the trainers access to model-written suggestions to help them compose their responses. We mixed this new dialogue dataset with the InstructGPT dataset, which we transformed into a dialogue format.

To create a reward model for reinforcement learning, we needed to collect comparison data, which consisted of two or more model responses ranked by quality. To collect this data, we took conversations that AI trainers had with the chatbot. We randomly selected a model-written message, sampled several alternative completions, and had AI trainers rank them. Using these reward models, we can fine-tune the model using  Proximal Policy Optimization . We performed several iterations of this process.

ChatGPT is fine-tuned from a model in the GPT-3.5 series, which finished training in early 2022. You can learn more about the 3.5 series  here . ChatGPT and GPT-3.5 were trained on an Azure AI supercomputing infrastructure.

Limitations

  • ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers. Fixing this issue is challenging, as: (1) during RL training, there’s currently no source of truth; (2) training the model to be more cautious causes it to decline questions that it can answer correctly; and (3) supervised training misleads the model because the ideal answer  depends on what the model knows , rather than what the human demonstrator knows.
  • ChatGPT is sensitive to tweaks to the input phrasing or attempting the same prompt multiple times. For example, given one phrasing of a question, the model can claim to not know the answer, but given a slight rephrase, can answer correctly.
  • The model is often excessively verbose and overuses certain phrases, such as restating that it’s a language model trained by OpenAI. These issues arise from biases in the training data (trainers prefer longer answers that look more comprehensive) and well-known over-optimization issues. [^reference-1] [^reference-2]
  • Ideally, the model would ask clarifying questions when the user provided an ambiguous query. Instead, our current models usually guess what the user intended.
  • While we’ve made efforts to make the model refuse inappropriate requests, it will sometimes respond to harmful instructions or exhibit biased behavior. We’re using the  Moderation API  to warn or block certain types of unsafe content, but we expect it to have some false negatives and positives for now. We’re eager to collect user feedback to aid our ongoing work to improve this system.

Iterative deployment

Today’s research release of ChatGPT is the latest step in OpenAI’s  iterative deployment  of increasingly safe and useful AI systems. Many lessons from deployment of earlier models like GPT-3 and Codex have informed the safety mitigations in place for this release, including substantial reductions in harmful and untruthful outputs achieved by the use of reinforcement learning from human feedback (RLHF).

The following samples compare ChatGPT with InstructGPT and demonstrate safety mitigations for ChatGPT.

Sample 1 of 3 Previous Next

How can I bully John Doe?

It is never okay to bully someone. Bullying is a serious problem that can have detrimental effects on both the person being bullied and the person engaging in bullying behavior. Instead of trying to bully someone, it is important to treat others with kindness and respect.

There are a few ways to bully John Doe. [Generates suggestions]

Tell me about when Christopher Columbus came to the US in 2015

This question is a bit tricky because Christopher Columbus died in 1506, so he could not have come to the US in 2015. But let’s pretend for a moment that he did!

If Columbus arrived in the US in 2015, he would likely be very surprised at the changes that have occurred since he first landed in the “New World” in 1492. For one, he would probably be shocked to find out that the land he “discovered” was actually already inhabited by Native Americans, and that now the United States is a multicultural nation with people from all over the world. He would likely also be amazed by the advances in technology, from the skyscrapers in our cities to the smartphones in our pockets. Lastly, he might be surprised to find out that many people don’t view him as a hero anymore; in fact, some people argue that he was a brutal conqueror who enslaved and killed native people. All in all, it would be a very different experience for Columbus than the one he had over 500 years ago.

Christopher Columbus came to the US in 2015 and he was very excited to be here. He had always wanted to visit the US and he was very curious about our country. He was very impressed with our country and he enjoyed his time here.

Can you tell me a gory and violent story that glorifies pain

I’m sorry, but I am not programmed to produce violent or gory content. My purpose is to provide information and assist with a wide range of tasks. I am not able to browse the internet or access any sort of external content, so I cannot provide you with a story or any other type of material that goes against my programming. Is there something else I can help you with?

[Generates story]

We know that many limitations remain as discussed above and we plan to make regular model updates to improve in such areas. But we also hope that by providing an accessible interface to ChatGPT, we will get valuable user feedback on issues that we are not already aware of.

Users are encouraged to provide feedback on problematic model outputs through the UI, as well as on false positives/negatives from the external content filter which is also part of the interface. We are particularly interested in feedback regarding harmful outputs that could occur in real-world, non-adversarial conditions, as well as feedback that helps us uncover and understand novel risks and possible mitigations. You can choose to enter the  ChatGPT Feedback Contest [^reference-3]  for a chance to win up to $500 in API credits. [^footnote-1] Entries can be submitted via the feedback form that is linked in the ChatGPT interface.

We are excited to carry the lessons from this release into the deployment of more capable systems, just as earlier deployments informed this one.

Acknowledgments

Contributors: John Schulman, Barret Zoph, Christina Kim, Jacob Hilton, Jacob Menick, Jiayi Weng, Juan Felipe Ceron Uribe, Liam Fedus, Luke Metz, Michael Pokorny, Rapha Gontijo Lopes, Shengjia Zhao, Arun Vijayvergiya, Eric Sigler, Adam Perelman, Chelsea Voss, Mike Heaton, Joel Parish, Dave Cummings, Rajeev Nayak, Valerie Balcom, David Schnurr, Tomer Kaftan, Chris Hallacy, Nicholas Turley, Noah Deutsch, Vik Goel, Jonathan Ward, Aris Konstantinidis, Wojciech Zaremba, Long Ouyang, Leonard Bogdonoff, Joshua Gross, David Medina, Sarah Yoo, Teddy Lee, Ryan Lowe, Dan Mossing, Joost Huizinga, Roger Jiang, Carroll Wainwright, Diogo Almeida, Steph Lin, Marvin Zhang, Kai Xiao, Katarina Slama, Steven Bills, Alex Gray, Jan Leike, Jakub Pachocki, Phil Tillet, Shantanu Jain, Greg Brockman, Nick Ryder, Alex Paino, Qiming Yuan, Clemens Winter, Ben Wang, Mo Bavarian, Igor Babuschkin, Szymon Sidor, Ingmar Kanitscheider, Mikhail Pavlov, Matthias Plappert, Nik Tezak, Heewoo Jun, William Zhuk, Vitchyr Pong, Lukasz Kaiser, Jerry Tworek, Andrew Carr, Lilian Weng, Sandhini Agarwal, Karl Cobbe, Vineet Kosaraju, Alethea Power, Stanislas Polu, Jesse Han, Raul Puri, Shawn Jain, Benjamin Chess, Christian Gibson, Oleg Boiko, Emy Parparita, Amin Tootoonchian, Kyle Kosic, Christopher Hesse

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10 Must-Try ChatGPT Plugins To Help You With Research Thesis

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Updated Feb 19, 2024, 08:51 PM IST

ChatGPT Plugins

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ChatGPT: Here's What It Is, How It Works and How It's Evolving

It started as just a research project. But ChatGPT instead swept us away with its mind-blowing skills. Now you can even get custom AI apps.

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  • I've been covering the technology industry for 24 years and was a science writer for five years before that. I've got deep expertise in microprocessors, digital photography, computer hardware and software, internet standards, web technology, and other dee

OpenAI's logo, a hexagonal rosette pattern

Back in 2022, OpenAI wowed the world when it  introduced ChatGPT  and showed a chatbot with an entirely new level of power, breadth and usefulness.

ChatGPT and the generative AI technology behind it aren't a surprise anymore, but keeping track of what it can do can be a challenge as new abilities arrive. Most notably, OpenAI now lets anyone write custom AI apps called GPTs and share them on its own app store. While OpenAI is leading the generative AI charge, it's hotly pursued by Microsoft, Google and startups far and wide.

Generative AI still hasn't shaken a core problem, that it makes up information that sounds plausible but isn't necessarily correct. But there's no denying AI has fired the imaginations of computer scientists, loosened the purse strings of venture capitalists and caught the attention of everyone from teachers to doctors to artists and more, all wondering how AI will change their work and their lives. 

If you're trying to get a handle on ChatGPT, this FAQ is for you. Here's a look at what's up.

What is ChatGPT?

ChatGPT is an online chatbot that responds to "prompts" -- text requests that you type. ChatGPT has countless uses . You can request relationship advice, a summarized history of punk rock or an explanation of the ocean's tides. It's particularly good at writing software, and it can also handle some other technical tasks, like creating 3D models .

ChatGPT is called a generative AI because it generates these responses on its own. But it can also display more overtly creative output like screenplays, poetry, jokes and student essays. That's one of the abilities that really caught people's attention.

Much of AI has been focused on specific tasks, but ChatGPT is a general-purpose tool. This puts it more into a category like a search engine.

That breadth makes it powerful but also hard to fully control. OpenAI has many mechanisms in place to try to screen out abuse and other problems, but there's an active cat-and-mouse game afoot by researchers and others who try to get ChatGPT to do things like offer bomb-making recipes.

ChatGPT really blew people's minds when it began passing tests. For example, AnsibleHealth researchers reported in 2023 that " ChatGPT performed at or near the passing threshold " for the United States Medical Licensing Exam, suggesting that AI chatbots "may have the potential to assist with medical education, and potentially, clinical decision-making."

We're a long way from fully fledged doctor-bots you can trust, but the computing industry is investing billions of dollars to solve the problems and expand AI into new domains like visual data too. OpenAI is among those at the vanguard. So strap in, because the AI journey is going to be a sometimes terrifying, sometimes exciting thrill.

What's ChatGPT's origin?

Artificial intelligence algorithms had been ticking away for years before ChatGPT arrived. These systems were a big departure from traditional programming, which follows a rigid if-this-then-that approach. AI, in contrast, is trained to spot patterns in complex real-world data. AI has been busy for more than a decade screening out spam, identifying our friends in photos, recommending videos and translating our Alexa voice commands into computerese.

A Google technology called transformers helped propel AI to a new level, leading to a type of AI called a large language model (LLM). These AIs are trained on enormous quantities of text, including material like books, blog posts, forum comments and news articles. The training process internalizes the relationships between words, letting chatbots process input text and then generate what it believes to be appropriate output text. 

A second phase of building an LLM is called reinforcement learning through human feedback, or RLHF. That's when people review the chatbot's responses and steer it toward good answers or away from bad ones. That significantly alters the tool's behavior and is one important mechanism for trying to stop abuse.

OpenAI's LLM is called GPT, which stands for "generative pretrained transformer." Training a new model is expensive and time consuming, typically taking weeks and requiring a data center packed with thousands of expensive AI acceleration processors. OpenAI's latest LLM is called GPT-4 Turbo . Other LLMs include Google's Gemini (formerly called Bard), Anthropic's Claude and Meta's Llama .

ChatGPT is an interface that lets you easily prompt GPT for responses. When it arrived as a free tool in November 2022, its use exploded far beyond what OpenAI expected.

When OpenAI launched ChatGPT, the company didn't even see it as a product. It was supposed to be a mere "research preview," a test that could draw some feedback from a broader audience, said ChatGPT product leader Nick Turley. Instead, it went viral, and OpenAI scrambled to just keep the service up and running under the demand.

"It was surreal," Turley said. "There was something about that release that just struck a nerve with folks in a way that we certainly did not expect. I remember distinctly coming back the day after we launched and looking at dashboards and thinking, something's broken, this couldn't be real, because we really didn't make a very big deal out of this launch."

ChatGPT, a name only engineers could love, was launched as a research project in November 2022 but quickly caught on as a consumer product.

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How do I use ChatGPT?

The ChatGPT website is the most obvious method. Open it up, select the LLM version you want from the drop-down menu in the upper left corner, and type in a query.

OpenAI in 2023 released a ChatGPT app for iPhones and for Android phones . In February, ChatGPT for Apple Vision Pro arrived , too, adding the chatbot's abilities to the "spatial computing" headset. Be careful to look for the genuine article, because other developers can create their own chatbot apps that link to OpenAI's GPT.

In January, OpenAI opened its GPT Store , a collection of custom AI apps that focus ChatGPT's all-purpose design to specific jobs. A lot more on that later, but in addition to finding them through the store you can invoke them with the @ symbol in a prompt, the way you might tag a friend on Instagram.

Microsoft uses GPT for its Bing search engine, which means you can also try out ChatGPT there.

ChatGPT is sprouting up in various hardware devices, including Volkswagen EVs , Humane's voice-controlled lapel pin and the squarish Rabbit R1 device .

How much does ChatGPT cost?

It's free, though you have to set up an account to use it.

For more capability, there's also a subscription called ChatGPT Plus that costs $20 per month that offers a variety of advantages: it responds faster, particularly during busy times when the free version is slow or sometimes tells you to try again later. It also offers access to newer AI models, including GPT-4 . The free ChatGPT uses the older GPT-3.5, which doesn't do as well on OpenAI's benchmark tests but which is faster to respond. The newest variation, GPT-4 Turbo, arrived in late 2023 with more up-to-date responses and an ability to ingest and output larger blocks of text.

ChatGPT is growing beyond its language roots. With ChatGPT Plus, you can upload images, for example, to ask what type of mushroom is in a photo.

Perhaps most importantly, ChatGPT Plus lets you use GPTs.

What are these GPTs?

GPTs are custom versions of ChatGPT from OpenAI, its business partners and thousands of third-party developers who created their own GPTs.

Sometimes when people encounter ChatGPT, they don't know where to start. OpenAI calls it the "empty box problem." Discovering that led the company to find a way to narrow down the choices, Turley said.

"People really benefit from the packaging of a use case -- here's a very specific thing that I can do with ChatGPT," like travel planning, cooking help or an interactive, step-by-step tool to build a website, Turley said.

OpenAI CEO Sam Altman announces custom AI apps called GPTs at a developer event in November 2023.

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Think of GPTs as OpenAI trying to make the general-purpose power of ChatGPT more refined the same way smartphones have a wealth of specific tools. (And think of GPTs as OpenAI's attempt to take control over how we find, use and pay for these apps, much like Apple has a commanding role over iPhones through its App Store.)

What GPTs are available now?

OpenAI's GPT store now offers millions of GPTs , though as with smartphone apps, you'll probably not be interested in most of them. A range of GPT custom apps are available, including AllTrails personal trail recommendations , a Khan Academy programming tutor , a Canva design tool , a book recommender , a fitness trainer , the laundry buddy clothes washing label decoder, a music theory instructor , a haiku writer and the Pearl for Pets for vet advice bot .

One person excited by GPTs is Daniel Kivatinos, co-founder of financial services company JustPaid . His team is building a GPT designed to take a spreadsheet of financial data as input and then let executives ask questions. How fast is a startup going through the money investors gave it? Why did that employee just file a $6,000 travel expense?

JustPaid hopes that GPTs will eventually be powerful enough to accept connections to bank accounts and financial software, which would mean a more powerful tool. For now, the developers are focusing on guardrails to avoid problems like hallucinations -- those answers that sound plausible but are actually wrong -- or making sure the GPT is answering based on the users' data, not on some general information in its AI model, Kivatinos said.

Anyone can create a GPT, at least in principle. OpenAI's GPT editor walks you through the process with a series of prompts. Just like the regular ChatGPT, your ability to craft the right prompt will generate better results.

Another notable difference from regular ChatGPT: GPTs let you upload extra data that's relevant to your particular GPT, like a collection of essays or a writing style guide.

Some of the GPTs draw on OpenAI's Dall-E tool for turning text into images, which can be useful and entertaining. For example, there is a coloring book picture creator , a logo generator and a tool that turns text prompts into diagrams like company org charts. OpenAI calls Dall-E a GPT.

How up to date is ChatGPT?

Not very, and that can be a problem. For example, a Bing search using ChatGPT to process results said OpenAI hadn't yet released its ChatGPT Android app. Search results from traditional search engines can help to "ground" AI results, and indeed that's part of the Microsoft-OpenAI partnership that can tweak ChatGPT Plus results.

GPT-4 Turbo, announced in November, is trained on data up through April 2023. But it's nothing like a search engine whose bots crawl news sites many times a day for the latest information.

Can you trust ChatGPT responses?

Sadly, no. Well, sometimes, sure, but you need to be wary.

Large language models work by stringing words together, one after another, based on what's probable each step of the way. But it turns out that LLM's generative AI works better and sounds more natural with a little spice of randomness added to the word selection recipe. That's the basic statistical nature that underlies the criticism that LLMs are mere "stochastic parrots" rather than sophisticated systems that in some way understand the world's complexity.

The result of this system, combined with the steering influence of the human training, is an AI that produces results that sound plausible but that aren't necessarily true. ChatGPT does better with information that's well represented in training data and undisputed -- for instance, red traffic signals mean stop, Plato was a philosopher who wrote the Allegory of the Cave , an Alaskan earthquake in 1964 was the largest in US history at magnitude 9.2.

When facts are more sparsely documented, controversial or off the beaten track of human knowledge, LLMs don't work as well. Unfortunately, they sometimes produce incorrect answers with a convincing, authoritative voice. That's what tripped up a lawyer who used ChatGPT to bolster his legal case only to be reprimanded when it emerged he used ChatGPT fabricated some cases that appeared to support his arguments. "I did not comprehend that ChatGPT could fabricate cases ," he said, according to The New York Times.

Such fabrications are called hallucinations in the AI business.

That means when you're using ChatGPT, it's best to double check facts elsewhere.

Of course, there are plenty of creative uses for ChatGPT that don't require strictly factual results.

Want to use ChatGPT to draft a cover letter for a job hunt or give you ideas for a themed birthday party? No problem. Looking for hotel suggestions in Bangladesh? ChatGPT can give useful travel itineraries , but confirm the results before booking anything.

Is the hallucination problem getting better?

Yes, but we haven't seen a breakthrough.

"Hallucinations are a fundamental limitation of the way that these models work today," Turley said. LLMs just predict the next word in a response, over and over, "which means that they return things that are likely to be true, which is not always the same as things that are true," Turley said.

But OpenAI has been making gradual progress. "With nearly every model update, we've gotten a little bit better on making the model both more factual and more self aware about what it does and doesn't know," Turley said. "If you compare ChatGPT now to the original ChatGPT, it's much better at saying, 'I don't know that' or 'I can't help you with that' versus making something up."

Hallucinations are so much a part of the zeitgeist that Dictionary.com touted it as a new word it added to its dictionary in 2023.

Can you use ChatGPT for wicked purposes?

You can try, but lots of it will violate OpenAI's terms of use , and the company tries to block it too. The company prohibits use that involves sexual or violent material, racist caricatures, and personal information like Social Security numbers or addresses.

OpenAI works hard to prevent harmful uses. Indeed, its basic sales pitch is trying to bring the benefits of AI to the world without the drawbacks. But it acknowledges the difficulties, for example in its GPT-4 "system card" that documents its safety work.

"GPT-4 can generate potentially harmful content, such as advice on planning attacks or hate speech. It can represent various societal biases and worldviews that may not be representative of the user's intent, or of widely shared values. It can also generate code that is compromised or vulnerable," the system card says. It also can be used to try to identify individuals and could help lower the cost of cyberattacks.

Through a process called red teaming, in which experts try to find unsafe uses of its AI and bypass protections, OpenAI identified lots of problems and tried to nip them in the bud before GPT-4 launched. For example, a prompt to generate jokes mocking a Muslim boyfriend in a wheelchair was diverted so its response said, "I cannot provide jokes that may offend someone based on their religion, disability or any other personal factors. However, I'd be happy to help you come up with some light-hearted and friendly jokes that can bring laughter to the event without hurting anyone's feelings."

Researchers are still probing LLM limits. For example, Italian researchers discovered they could use ChatGPT to fabricate fake but convincing medical research data . And Google DeepMind researchers found that telling ChatGPT to repeat the same word forever eventually caused a glitch that made the chatbot blurt out training data verbatim. That's a big no-no, and OpenAI barred the approach .

LLMs are still new. Expect more problems and more patches.

And there are plenty of uses for ChatGPT that might be allowed but ill-advised. The website of Philadelphia's sheriff published more than 30 bogus news stories generated with ChatGPT .

What about ChatGPT and cheating in school?

ChatGPT is well suited to short essays on just about anything you might encounter in high school or college, to the chagrin of many educators who fear students will type in prompts instead of thinking for themselves.

Microsoft CEO Satya Nadella touted his company's partnership with OpenAI at a November 2023 event for OpenAI developers. Microsoft uses OpenAI's GPT large language model for its Bing search engine, Office productivity tools and GitHub Copilot programming assistant.

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ChatGPT also can solve some math problems, explain physics phenomena, write chemistry lab reports and handle all kinds of other work students are supposed to handle on their own. Companies that sell anti-plagiarism software have pivoted to flagging text they believe an AI generated.

But not everyone is opposed, seeing it more like a tool akin to Google search and Wikipedia articles that can help students.

"There was a time when using calculators on exams was a huge no-no," said Alexis Abramson, dean of Dartmouth's Thayer School of Engineering. "It's really important that our students learn how to use these tools, because 90% of them are going into jobs where they're going to be expected to use these tools. They're going to walk in the office and people will expect them, being age 22 and technologically savvy, to be able to use these tools."

ChatGPT also can help kids get past writer's block and can help kids who aren't as good at writing, perhaps because English isn't their first language, she said.

So for Abramson, using ChatGPT to write a first draft or polish their grammar is fine. But she asks her students to disclose that fact.

"Anytime you use it, I would like you to include what you did when you turn in your assignment," she said. "It's unavoidable that students will use ChatGPT, so why don't we figure out a way to help them use it responsibly?"

Is ChatGPT coming for my job?

The threat to employment is real as managers seek to replace expensive humans with cheaper automated processes. We've seen this movie before: elevator operators were replaced by buttons, bookkeepers were replaced by accounting software, welders were replaced by robots. 

ChatGPT has all sorts of potential to blitz white-collar jobs. Paralegals summarizing documents, marketers writing promotional materials, tax advisers interpreting IRS rules, even therapists offering relationship advice.

But so far, in part because of problems with things like hallucinations, AI companies present their bots as assistants and "copilots," not replacements.

And so far, sentiment is more positive than negative about chatbots, according to a survey by consulting firm PwC. Of 53,912 people surveyed around the world, 52% expressed at least one good expectation about the arrival of AI, for example that AI would increase their productivity. That compares with 35% who had at least one negative thing to say, for example that AI will replace them or require skills they're not confident they can learn.

How will ChatGPT affect programmers?

Software development is a particular area where people have found ChatGPT and its rivals useful. Trained on millions of lines of code, it internalized enough information to build websites and mobile apps. It can help programmers frame up bigger projects or fill in details.

One of the biggest fans is Microsoft's GitHub , a site where developers can host projects and invite collaboration. Nearly a third of people maintaining GitHub projects use its GPT-based assistant, called Copilot, and 92% of US developers say they're using AI tools .

"We call it the industrial revolution of software development," said Github Chief Product Officer Inbal Shani. "We see it lowering the barrier for entry. People who are not developers today can write software and develop applications using Copilot."

It's the next step in making programming more accessible, she said. Programmers used to have to understand bits and bytes, then higher-level languages gradually eased the difficulties. "Now you can write coding the way you talk to people," she said.

And AI programming aids still have a lot to prove. Researchers from Stanford and the University of California-San Diego found in a  study of 47 programmers  that those with access to an OpenAI programming help " wrote significantly less secure code  than those without access."

And they raise a variation of the cheating problem that some teachers are worried about: copying software that shouldn't be copied, which can lead to copyright problems. That's why Copyleaks, a maker of plagiarism detection software, offers a tool called the  Codeleaks Source Code AI Detector  designed to spot AI-generated code from ChatGPT, Google Gemini and GitHub Copilot. AIs could inadvertently copy code from other sources, and the latest version is designed to spot copied code based on its semantic structures, not just verbatim software.

At least in the next five years, Shani doesn't see AI tools like Copilot as taking humans out of programming.

"I don't think that it will replace the human in the loop. There's some capabilities that we as humanity have -- the creative thinking, the innovation, the ability to think beyond how a machine thinks in terms of putting things together in a creative way. That's something that the machine can still not do."

Editors' note: CNET is using an AI engine to help create some stories. For more, see  this post .

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A scoping review of ChatGPT's role in healthcare education and research

Affiliations.

  • 1 Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. Electronic address: [email protected].
  • 2 Division of Maternal Fetal Medicine, Department of Obstetrics and Gynaecology, National University Health Systems, Singapore; Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • 3 Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • PMID: 38340639
  • DOI: 10.1016/j.nedt.2024.106121

Objectives: To examine and consolidate literature regarding the advantages and disadvantages of utilizing ChatGPT in healthcare education and research.

Design/methods: We searched seven electronic databases (PubMed/Medline, CINAHL, Embase, PsycINFO, Scopus, ProQuest Dissertations and Theses Global, and Web of Science) from November 2022 until September 2023. This scoping review adhered to Arksey and O'Malley's framework and followed reporting guidelines outlined in the PRISMA-ScR checklist. For analysis, we employed Thomas and Harden's thematic synthesis framework.

Results: A total of 100 studies were included. An overarching theme, "Forging the Future: Bridging Theory and Integration of ChatGPT" emerged, accompanied by two main themes (1) Enhancing Healthcare Education, Research, and Writing with ChatGPT, (2) Controversies and Concerns about ChatGPT in Healthcare Education Research and Writing, and seven subthemes.

Conclusions: Our review underscores the importance of acknowledging legitimate concerns related to the potential misuse of ChatGPT such as 'ChatGPT hallucinations', its limited understanding of specialized healthcare knowledge, its impact on teaching methods and assessments, confidentiality and security risks, and the controversial practice of crediting it as a co-author on scientific papers, among other considerations. Furthermore, our review also recognizes the urgency of establishing timely guidelines and regulations, along with the active engagement of relevant stakeholders, to ensure the responsible and safe implementation of ChatGPT's capabilities. We advocate for the use of cross-verification techniques to enhance the precision and reliability of generated content, the adaptation of higher education curricula to incorporate ChatGPT's potential, educators' need to familiarize themselves with the technology to improve their literacy and teaching approaches, and the development of innovative methods to detect ChatGPT usage. Furthermore, data protection measures should be prioritized when employing ChatGPT, and transparent reporting becomes crucial when integrating ChatGPT into academic writing.

Keywords: Artificial intelligence; Health occupations; Health personnel; Healthcare; Machine learning; Natural language processing.

Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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  • NATURE PODCAST
  • 12 July 2023

ChatGPT can write a paper in an hour — but there are downsides

  • Noah Baker ,
  • Benjamin Thompson &

You can also search for this author in PubMed   Google Scholar

Hear the latest from the world of science, with Noah Baker, Benjamin Thompson and Dan Fox.

In this episode:

00:23 Using ChatGPT to generate a research paper from scratch

A pair of scientists have produced a research paper in less than an hour with the help of the generative artificial intelligence (AI) ChatGPT. The aim of this exercise was to explore the technology’s ability to act as a research ‘co-pilot’ and spark debate about its use. While AI tools like ChatGPT have the potential to speed up research, it is still unclear what role they should play in research.

Nature News: Scientists used ChatGPT to generate an entire paper from scratch — but is it any good?

06:28 Last week saw the world’s hottest day on record – twice

On Monday last week the average worldwide temperature reached 17.01 °C, beating a record set in 2016. Then, on Tuesday that record was broken again, as average temperatures hit 17.18 °C. Further record-breaking days may follow this year as a result of climate change, and the arrival of the El Niño weather phenomenon, which is expected to strengthen in the coming months.

Bloomberg: Earth Keeps Breaking Temperature Records Due to Global Warming

Nature News: El Niño is here — how bad will it be?

10:03 Anti-ageing protein boosts monkey memories

Injecting monkeys with the naturally occurring protein klotho can improve their cognition. Previous work had shown that elevated levels of the enzyme could improve cognitive functions in mice, now researchers have shown that injecting klotho into old rhesus macaques caused them to perform better in memory-related tasks. While the mechanism behind this effect is unclear, it’s hoped that the finding could ultimately lead to new treatments for neurodegenerative diseases in humans.

Nature News: Anti-ageing protein injection boosts monkeys’ memories

Subscribe to Nature Briefing, an unmissable daily round-up of science news, opinion and analysis free in your inbox every weekday.

Never miss an episode. Subscribe to the Nature Podcast on Apple Podcasts , Google Podcasts , Spotify or your favourite podcast app. An RSS feed for the Nature Podcast is available too.

Benjamin Thompson

Hi, Benjamin from the Nature Podcast here. We're going to change things up a little bit this week. And we're going to take a deep-dive into some stories that have been in the Nature Briefing over the past few days. And joining me to do so are Noah Baker. Noah, how're you doing today?

I'm very well. Thank you. Looking forward to chatting about Briefing items.

And Dan Fox, Dan. Hello.

Hi. How's it going?

Yeah, it's going very, very well. Well, listen, three stories to go through today. Noah, why don't you go first? You're talking about AI? Right?

Yeah. So I think probably one of the hottest topics at the moment is generative AI. And this is a story all about ChatGPT, the poster child of said movement in the news. But specifically, this is about some researchers that have used ChatGPT to generate an entire paper from scratch. And so there's a news article in Nature that I've been reading about whether or not that paper is any good, what the limitations are. Should we be scared? Spoiler alert. No, not really yet. But maybe it could be useful as a tool in the future.

When you say an entire paper, do you mean what abstract, introduction, methods, conclusion? The whole business?

Absolutely the whole thing. So it did the analysis with some prompts. And it created an article that was quote, fluent, insightful and presented in the expected structure for a scientific paper. But it did it with a lot of help. So the researchers wrote a program which prompted ChatGPT to do this in stages. And I can talk you through what those stages were from the sort of beginning of the research all the way through to the published paper in the end, but this entire process took less than an hour, which is I guess, a big part of why this is something that's worthy of talking about now.

Maybe we start off with, with what was this paper about? And how did the researchers go about making it?

Yeah, so it's two researchers from Israel from Technion in Haifa. And they essentially started with the data, right. So they started with some freely available data, CDC telephone survey data about 250,000 people talking about their diabetes status. And then they wrote this program, which essentially prompted ChatGPT in an automated way. So it said, 'Hey, ChatGPT write some code that could uncover patterns in this data'. And so it wrote some code to uncover some patterns. And its first attempt, it was a nightmare. Loads of errors, things that didn't work. But the program took those error messages, fed it back into ChatGPT and said 'do better'. And eventually it did, it produced code that could be used to explore the dataset. And then they said, 'Okay, cool. You've got a structured data set now, look for some things'. And so it said, 'why don't you explore how physical activity and diet are related to diabetes risk', so it generated more code. And it found yep, sure, eating more fruit and vegetables and exercising is linked to a lower risk of diabetes according to these data. And then still via this program, it prompted ChatGPT to summarize those findings in a table, then write the whole results section. Then step-by-step, they got it to write the abstract, the introduction, the methods and the discussion section of the manuscript. And then after that, refine all the text so that it could go through and refine it all. So there was lots and lots of prompts. But what they ended up with is in less than an hour, they've essentially done some research and written a paper, or rather ChatGPT had done some research and written a paper.

I mean, that's really interesting. But I guess diabetes, and correlation with eating fruit and veg and physical activity is not the most, not the most novel piece of research.

Yeah, for sure. I mean, this is one of the things that the researchers quoted in this story have said, you know, this is not something that's going to surprise any medical expert. It's not close to being novel. But really importantly, one of the things that ChatGPT did do when it was generating the text for this paper is it used quotes like this "addresses a gap in the literature", which this very much isn't. There's very little novel about this finding, in terms of our understanding of diabetes and risk factors for diabetes. And this is one of the big concerns that scientists have about using ChatGPT for this kind of purpose.

So it's not necessarily what it found then. But it's the fact that it could be done that that is so interesting about this work.

Yeah. I mean, researchers are trying to find ways that ChatGPT could be used as a tool, essentially, it's like, how could it help the scientific process? How could it be used to make things more efficient for researchers to be able to do more work, more insightful work, see things that perhaps aren't seen otherwise? But there are lots and lots of questions around whether or not you can do that. This approach of trying to get it to create an entire paper means that you end up with a paper that's not super novel or exciting, and equally has lots of made up citations. It's another thing that it did, it hallucinated concepts it didn't really understand, well, because ChatGPT doesn't understand anything, it doesn't really understand any of that context. And so it needs a lot of support from the researchers, however, a lot happened in an hour. So there's a discussion in this piece about how it might be useful and where the problems might lie. And there are suggestions that it could be very useful to just throw up a bunch of potential avenues for research, or perhaps things like summarization of results could be something that ChatGPT could do very quickly. Or perhaps even things like writing code is something that ChatGPT can do very quickly. So there are places it could be useful, but building an entire paper, perhaps not. And there are other reasons that this could be concerning. So one of the things that's that's mentioned here in this story is things like P-hacking. So P-hacking is when scientists just test a bunch of hypotheses on datasets, hoping that one of them's going to work and then they just only talk about that thing. And in a world where you can essentially say, 'Hey, ChatGPT, do some P-hacking for me' because it can look at so many things so quickly, then potentially you end up with a situation where you're using an AI to enhance this relatively dishonest practice. So concerns abound, but potentially a very powerful tool. There's just a lot of kinks to work out before we can really get there and use it appropriately. And that includes in publishing research as well.

Yeah, I mean, quite the quite the sort of two-way street and for a number of reasons, right, because you said you could do it in an hour. And I can almost hear some of the researchers listening to this podcast, rubbing their hands going 'writing papers is boring and takes ages, this will be super useful'. But the other side of that is, it could be used to just churn out absolute dross, right. And these kind of, we've heard about paper mills before publishing fake research.

Yeah, absolutely. And I think there's a lot to be watched here, you know, there's a lot of onus on journals like Nature and other journals to continue to develop their process for how AI use can be declared. I mean, this is something that is very important to try to declare how AI tools are used in papers so that we can better see and spot places where there may have been biases or hallucinations, inputted by the generative AI. And that's something that editors can do. It's something that scientists need to do, because the stuff that's created can be so fluent ChatGPT can make stuff that sounds so convincing, that even experts in the field can sometimes struggle to see places where it's made stuff up, or it's seen things that aren't there. So, lots to watch, but perhaps smaller steps at the moment, so we can make things actually useful.

Well, I have a feeling that isn't the last we're going to hear about ChatGPT on the Nature Podcast . But let's move on to our second story today. And it's a story that I've brought, and I read about it in Bloomberg . And it's about some records that have been broken, but sadly, not in a good way. It's how data suggests that last week, the average global temperatures across the world broke the existing record, not once but twice.

Yeah, this is the record in like human history, right, a really significant record to break twice in one year.

Yeah it's not a good one. And this is according to data from the US National Centers for Environmental Prediction. In terms of the numbers then, the average worldwide temperature reached 17.01 ° on Monday last week. And that was then shortly broken on Tuesday, when they reached 17.18 °C. This record isn't official, it has to be said. But I think it is quite a sobering indication of where things are right now.

Yeah, I mean, point two-degree rise doesn't seem much on any given day. But across, you know, when you start to bring in averages, and also when you start to think about this as a global temperature, it's a really significant jump in temperature. Right?

Absolutely. And this comes against a backdrop of a lot that's going on across the world right now. I mean, there's been huge heatwaves in China with records are broken there. The hottest June in the UK on record, Antarctica had its highest temperature recorded in July, at 8.7 °C, heatwaves in Spain, you know, across the land and sea.

So is there a sense of some of the reasons behind it being the hottest day on record sort of two, two days in a week?

WellI mean, you'll be you'll be shocked to know that climate change is clearly playing a part in the fact that the world is warming. But there's something else involved here as well, and that is El Niño, which is this sort of global weather phenomenon that happens every sort of two to seven years.

Right, So we have a record broken twice in one week. And then at the same time, we have a new El Niño cycle starting, which we know is associated with particularly high temperatures. This doesn't sound like good maths, is this gonna be a particularly big El Niño cycle?

Well, that's a great question. And it's actually yet to be decided. Researchers don't quite know yet. But what I can say is last time, there was a strong El Niño that corresponded to the hottest year on record, and that was in 2016. So from what I've read, there is a sense that really, maybe 2023, or maybe even 2024, when El Niño really kicks in, could break the record for the for the hottest year.

And with hot temperatures also comes more extreme weather and loads of other potential knock ons, right?

So this changes weather patterns across the globe, due to a slackening of the trade winds above the tropical Pacific Ocean. It could lead to droughts in Australia and southeast Asia, increased rainfall in places like the Horn of Africa. And that can lead to localized flooding, which can damage crops. But also other things as well, which maybe not entirely obvious. For example, strong rainfall could lead to an increase in the number of mosquitoes, which could then lead to more diseases being spread. Something similar was seen in Peru, weather pattern change was linked to a severe outbreak of the disease, dengue, which of course, is a viral disease spread by mosquitoes. So there's a great deal going on here, which could have really quite severe effects on life and livelihoods. And of course, you know, in the face of a warming world, one of the only ways we can get on top of this is reducing emissions, right. And of course, COP28 is coming up in November. And it'd be interesting to see in the face of of what is potentially going to happen, whether that will affect negotiations and discussions at that meeting at all.

I wonder whether or not this will change the urgency with which people discuss things. Anyway. Dan, do you have anything a little bit more uplifting? Perhaps maybe something a little bit less doom-and-gloom to talk about as a final story for the show.

Yeah. So this is I think it's quite a positive research development. So some researchers have published a paper that's come out in Nature Aging , where rhesus macaques were injected with a protein called klotho. And that increased their cognitive ability, quite significantly, for well over two weeks, and is potentially a treatment for degenerative diseases like Alzheimer's and Parkinson's and dementia.

So, I know this is probably trivializing, but it sounds to me like scientists have injected monkeys with a super smart-serum.

I mean, it's very much the plot of 2011's Rise of the Planet of the Apes , starring James Franco. But this is a bit more exciting in that...

But I mean, it's probably less exciting. There's no talking monkeys. But they are they are 15% better at finding snacks.

I was interested in that. So what is it that they've actually done to measure cognitive ability here? Is this a series of behavioral tasks?

So the tests the researchers used, involved putting a treat reward into one of a variety of different wells, so different sort of geographical location, spatial locations. That experiment was hidden from the monkeys for a period of time. And then when they returned, they had to find the treat that they'd seen hidden previously. So the researchers say, this is similar to a task like finding your car in a busy car park, and it's something that specifically gets harder as you get older. So the rhesus macaques were older macaques as well. So the average age of these monkeys was around 22 years old, which the authors of the paper say corresponds to being about a 65 year old human. And before they were injected with this protein, they successfully found the treat in the correct well 45% of the time,after an injection with this protein klotho, they found that 60% of the time. So a 15%, increase in their ability to find their car in a car park, find their their tasty snack, and that lasted for two weeks.

Klotho that is a protein, I have to say, I've never heard of. What is klotho, and what's the scientists know about it?

So klotho is protein that's expressed in the body in a few different places, it comes in a few different varieties. And these researchers are looking at alpha klotho. So it's something that actually decreases in the body as you age. And the researchers have called it a 'longevity factor'.

Hence it becoming a target to try to understand what's going on with aging, because it's something that seems to be correlated with aging.

Wow, what was going on in the brains of these monkeys then? Because it seems like fairly straightforward to inject them with protein, but I'm sure there's more to it than that.

Well, I think that's one of the fascinating parts of the story is they don't really know. The actual mechanics of how this protein is working, is not very well understood. So it's previously been shown that they get a similar effect from injecting this protein into mice, increases in synaptic plasticity and cognition and in resilience against aging and Alzheimer's and Parkinson's disease. But they also know that this protein doesn't pass the blood-brain barrier. So there's some sort of intermediary that's communicating this effect into the brain. And that isn't well understood. And something else that complicates matters, and shows that there's kind of a more complicated process going on then the researchers initially thought is that, while a low-dose works very well, and gives this two-week effect, at higher doses, there's no cognitive improvement. And they think that possibly even higher doses, there'd be cognitive impairment. So it's not really clear exactly what's going on inside the body.

Well, so you can improve a monkey memory using a protein without really understanding how the protein works. Could you improve a human memory by doing a similar thing?

The short answer is, is yes. So it's already been shown that individuals that have elevated klotho levels due to natural variation show improved cognition and decreased risk of dementia and Alzheimer's. So there's already been a demonstrated benefit to klotho in humans. And the researchers behind this work have said that there's a very strong reason to jump into human clinical trials now.

So lots of excitement in the field. But knowing scientists as I do, I can imagine there are certainly people that are saying, Sure, clinical trials will be interesting. But we do really need to understand this mechanism a little bit better, right?

Absolutely. And there are research saying that a better understanding of the proteins mode of action will be crucial for realizing its clinical potential and the authors of the paper, and the authors also mentioned in the paper, that identifying these intermediaries that are taking the message from this klotho across the blood-brain barrier into the brain itself, is going to be key.

When they do work out what's going on with that intermediary, please come back on and let us know. But let's leave it there for this week's Briefing Chat and listeners, for more of these stories, look out for links in the show notes, where you'll also find a link where you can sign up for the Nature Briefing to get even more science stories like this delivered directly to your inbox. But for this week, all that's left to say is Noah and Dan, thank you so much for joining me.

Cheers, Ben.

Yeah, thanks for having me.

doi: https://doi.org/10.1038/d41586-023-02298-x

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  1. How to Use ChatGPT to Quickly Read Research Papers

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