write a research paper with ai

Your Writing Assistant for Research

Unlock Your Research Potential with Jenni AI

Are you an academic researcher seeking assistance in your quest to create remarkable research and scientific papers? Jenni AI is here to empower you, not by doing the work for you, but by enhancing your research process and efficiency. Explore how Jenni AI can elevate your academic writing experience and accelerate your journey toward academic excellence.

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Join our academic community and elevate your research journey alongside fellow scholars with Jenni AI.

Effortlessly Ignite Your Research Ideas

Unlock your potential with these standout features

Boost Productivity

Save time and effort with AI assistance, allowing you to focus on critical aspects of your research. Craft well-structured, scholarly papers with ease, backed by AI-driven recommendations and real-time feedback.

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Overcome Writer's Block

Get inspiration and generate ideas to break through the barriers of writer's block. Jenni AI generates research prompts tailored to your subject, sparking your creativity and guiding your research.

Unlock Your Full Writing Potential

Jenni AI is designed to boost your academic writing capabilities, not as a shortcut, but as a tool to help you overcome writer's block and enhance your research papers' quality.

 Ensure Accuracy

Properly format citations and references, ensuring your work meets academic standards. Jenni AI offers accurate and hassle-free citation assistance, including APA, MLA, and Chicago styles.

Our Commitment: Academic Honesty

Jenni AI is committed to upholding academic integrity. Our tool is designed to assist, not replace, your effort in research and writing. We strongly discourage any unethical use. We're dedicated to helping you excel in a responsible and ethical manner.

How it Works

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Prompt Generation

Input your research topic, and Jenni AI generates comprehensive prompts to kickstart your paper.

Research Assistance

Find credible sources, articles, and relevant data with ease through our powerful AI-driven research assistant.

Writing Support

Draft and refine your paper with real-time suggestions for structure, content, and clarity.

Citation & References

Let Jenni AI handle your citations and references in multiple styles, saving you valuable time.

What Our Users Say

Discover how Jenni AI has made a difference in the lives of academics just like you

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Frequently asked questions

How much does jenni ai cost, how can jenni ai assist me in writing complex academic papers, can jenni ai handle different types of academic papers, such as essays, research papers, and dissertationss jenni ai maintain the originality of my work, how does artificial intelligence enhance my academic writing with jenni ai.

Can Jenni AI help me structure and write a comprehensive literature review?

Will using Jenni AI improve my overall writing skills?

Can Jenni AI assist with crafting a thesis statement?

What sets Jenni AI apart as an AI-powered writing tool?

Can I trust Jenni AI to help me maintain academic integrity in my work?

Choosing the Right Academic Writing Companion

Get ready to make an informed decision and uncover the key reasons why Jenni AI is your ultimate tool for academic excellence.

Feature Featire

COMPETITORS

Enhanced Writing Style

Jenni AI excels in refining your writing style and enhancing sentence structure to meet academic standards with precision.

Competitors may offer basic grammar checking but often fall short in fine-tuning the nuances of writing style.

Academic Writing Process

Jenni AI streamlines the academic writing process, offering real-time assistance in content generation and thorough proofreading.

Competitors may not provide the same level of support, leaving users to navigate the intricacies of academic writing on their own.

Scientific Writing

Jenni AI is tailored for scientific writing, ensuring the clarity and precision needed in research articles and reports.

Competitors may offer generic writing tools that lack the specialized features required for scientific writing.

Original Content and Academic Integrity

Jenni AI's AI algorithms focus on producing original content while preventing plagiarism, ensuring academic integrity.

Competitors may not provide robust plagiarism checks, potentially compromising academic integrity.

Valuable Tool for Technical Writing

Jenni AI extends its versatility to technical writing, aiding in the creation of clear and concise technical documents.

Some competitors may not be as well-suited for technical writing projects.

User-Friendly Interface

Jenni AI offers an intuitive and user-friendly interface, making it easy for both novice and experienced writers to utilize its features effectively.

Some competitors may have steeper learning curves or complex interfaces, which can be time-consuming and frustrating for users.

Seamless Citation Management

Jenni AI simplifies the citation management process, offering suggestions and templates for various citation styles.

Competitors may not provide the same level of support for correct and consistent citations.

Ready to Revolutionize Your Research Writing?

Sign up for a free Jenni AI account today. Unlock your research potential and experience the difference for yourself. Your journey to academic excellence starts here.

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

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

Make no mistake, AI is here to stay!

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

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

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

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

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

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

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

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

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

Here they are, below:

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

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

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

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

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

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

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

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

AI-powered research tools and AI for academic research

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

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

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

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

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

AI for reading peer-reviewed papers easily

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

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

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

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

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

AI for scientific writing and research papers

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

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

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

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

AI academic editing tools

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

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

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

AI tools for grant writing

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

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

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

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

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

Best free AI research tools

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

The best free ones at time of writing are:

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

Wrapping up

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

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

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

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

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

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

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

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

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

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

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

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AI Research Paper Generator

Transform your research journey with groundbreaking ai technology, effortlessly crafting academic papers that meet professional standards..

Streamlining Your Academic Writing Process Using EssayGPT

EssayGPT's AI research paper generator simplifies the process of crafting well-structured, comprehensive research papers. Here is how to do it in simple steps:

• 1. Get started by entering the central theme of your research in the 'Essay Topic' box.
• 2. Add up to five specific keywords related to your research topic to create relevant and focused content.
• 3. Enter your desired format including APA, MLA, or Harvard for accurate citation and formatting.
• 4. Use the 'Outline Suggestions' and 'Essay Title' boxes to tailor the structure and title to your specific needs.
• 5. Pick your target audience, tone of voice, and language. Then, hit the 'Generate' button to create your paper.

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Choosing EssayGPT's AI Research Paper Generator: A Cut Above the Rest

When it comes to crafting a research paper, the choice of tools can be a game-changer. With cutting-edge features, EssayGPT's AI research paper generator stands out as a superior choice for researchers seeking an efficient, versatile, and high-quality AI research paper writer.

This AI research paper generator from EssayGPT distinguishes itself from other AI writers for numerous compelling reasons such as:

Advanced AI Capabilities: At the heart of EssayGPT's AI research paper generator lies the integration of both GPT-3.5 and GPT-4 technologies. This dual AI power ensures not only advanced capabilities in generating research content but also guarantees versatility and depth in analysis, making it an unparalleled AI paper writer.

Full Customizability: Unlike standard research paper writers, EssayGPT's AI research paper generator provides complete control over the creation process. Whether it's adjusting the style, format, or specific content requirements, EssayGPT's AI research paper generator caters to all your unique academic needs.

Professional Citations and Reference Format: Catering to diverse academic standards, EssayGPT's AI paper generator offers a variety of professional paper reference formats. From APA to MLA or custom formats, the tool ensures your research paper meets the highest academic criteria.

Multi-Language Support: Breaking language barriers, EssayGPT's research paper writer extends its support to over 30 languages. This feature not only broadens the tool's accessibility but also makes it an invaluable asset for international research communities.

Advanced Context-Aware Technology: Understanding the importance of context in academic writing, EssayGPT's AI research paper generator employs advanced context-aware technology. This ensures that each paper generated is not only relevant but also resonates with the intended research topic, making it more than just an ordinary AI paper generator.

How Can You Benefit From EssayGPT's AI Research Paper Generator?

Embrace the future of research with EssayGPT's AI research paper generator. This tool is not just an advanced AI paper writer; it's a revolution in academic writing. Designed to cater to a diverse range of research needs, it offers an unparalleled blend of efficiency, customization, and quality, ensuring your research stands out.

Let's explore how it can significantly benefit users in the academic and professional fields:

Innovative Idea Cultivation: The AI research paper generator serves as a springboard for your research ideas. It helps conceptualize diverse topics, offering unique perspectives and thought-provoking angles, essential for groundbreaking research papers.

Time-Saving and Cost-Effective Solution: Reduce the hours spent on research and writing significantly. This free tool streamlines the writing process, allowing more focus on analysis and less on structuring, making efficient use of your valuable time and resources.

Simplifying the Writing Journey: Experience a transformed writing process with our AI paper writer. From outlining to drafting, the tool organizes and structures your thoughts, turning complex ideas into well-articulated research papers with ease.

Educational Enhancement: Beyond just generating papers, the AI research paper generator is a learning tool. It exposes users to varied writing styles and structures, enhancing their understanding of academic writing norms and encouraging skill development in research methodology.

EssayGPT AI Research Paper Generator’s Innovations in AI Paper Writing

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1. How does the EssayGPT AI research paper generator ensure data accuracy in the generated papers?

The EssayGPT AI research paper generator utilizes an advanced AI algorithm to fetch relevant and credible information. It employs sophisticated contextual understanding and keyword analysis to maintain accuracy. However, this tool is designed to augment rather than replace comprehensive manual research.

2. How does the EssayGPT AI research paper generator address plagiarism concerns?

The tool employs machine learning algorithms to synthesize information, ensuring each output is unique and original. Additionally, EssayGPT recommends users utilize its plagiarism checker, for thorough plagiarism verification.

3. Can the EssayGPT AI research paper generator handle complex academic disciplines?

Yes, the AI research paper generator is equipped with algorithms capable of handling a wide range of subjects, including advanced and specialized academic disciplines. It understands the complexity of various subjects and structures the research paper accordingly. Users are always advised to review and edit the generated content for precision.

4. What should I do if I find issues with the paper generated by EssayGPT's tool?

If you encounter any issues with the generated paper, you can always modify your inputs and regenerate them for better results. For specific concerns or improvement suggestions, you can always contact our support .

Get High-quality Paper with AI Research Paper Generator

Elevate your academic journey and let our AI research paper generator from EssayGPT turn your ideas into polished, scholarly works. Begin your transformative writing adventure now.

Research Paper Writer

Ai-powered research paper writing tool.

• Academic Research: Write a research paper for your coursework, thesis, or dissertation.
• Professional Research: Create a well-structured report for your professional work, including market research, policy papers, or white papers.
• Personal Research: Draft a detailed essay on a topic of personal interest.
• Content Creation: Develop a long-form blog post or article based on in-depth research.

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The 11 best AI tools for academic writing

By leveraging the power of the right AI tool, you can significantly improve the clarity, efficiency, and overall quality of your academic writing. In this guide, we reviewed and ranked 11 popular AI tools for academic writing , along with our top 3 choices, so that you can pick the best one.

What are the best AI tools for academic writing?

With the rise of AI tools, academic writing is undergoing a remarkable transformation. The emergence of new AI-powered tools has revolutionized the way researchers, scholars, and students approach their writing tasks.

Having to use multiple tools for different purposes can be frustrating. Therefore, comprehensive testing was conducted on AI tools to assess their all-encompassing capabilities.

Furthermore, the optional functions were compared to their respective prices to ensure a fair pricing structure. AI support for academic writing should be affordable and not strain your budget.

Here are Master Academia’s top picks for the best AI tools for academic writing in 2023:

Best Overall for Academic Writing ($6.67/month)

Trinka takes into account the specific research subjects, ensuring that the writing style, word choice, and tone align with disciplinary standards and scientific conventions.

Key Features:

You can use the basic version of Trinka for free, which includes access to all features but with a monthly word limit of 5000 words. The pricing for Trinka’s premium plan starts at $6.67 per month with annual billing, which is extremely affordable.

Genei streamlines the academic writing process by utilizing AI-generated summaries and note-taking shortcuts, extracting information from academic articles.

For those heavily reliant on literature reviews in their academic writing, Genei proves to be a gamechanger.

Genei offers two pricing structures, one for professionals and another for academics.

3. Quil lBot

With QuillBot ‘s all-in-one Co-Writer, you can access paraphrasing, summarizing, citation creation, and essay writing tools in a single location.

In simple terms, QuillBot’s AI will collaborate with you to generate effective rephrasing. You have a lot of control as you can compare outputs from all seven available modes to choose the most suitable paraphrase.

With the premium plan, you gain access to full functionality, including unlimited word paraphrasing, summarizing up to 6000 words, faster processing, advanced grammar features, tone detection, and more. The premium plan is priced at $19.95 per month or $8.33 per month when paid annually.

4. Writefull

With additional AI widgets like the Abstract Generator, Academizer, Paraphraser, and Title Generator, it provides inspiration and assistance for academic writers.

Writefull can be used with limited functionality for free. Its Premium Plan offers unlimited use of all features at a cost of $15.37 per month.

5. Grammarly

Grammarly stands out among other AI tools by having a widespread and popular institutional license, which universities readily embrace.

Grammarly’s popularity in the academic community can be attributed to its support for citation style formatting and robust plagiarism detection, making it a valuable tool for academic writing.

The business account may not be of interest to students or researchers. However, universities can opt for Grammarly for Education, which provides licenses for free premium plans to students and staff.

6. Wordtune

The tool itself proclaims that it has gained the trust of students and researchers at renowned universities.

7. Paperpal

Paperpal, developed by Researcher.life, is a specialized AI tool designed for researchers and academic writers, leveraging the expertise gained from editing numerous manuscripts by professional editors.

Available as Paperpal for Word, Web, and Manuscript, this comprehensive tool also checks for structural and technical inconsistencies in your writing.

8. Sourcely

By analyzing text and identifying key themes, Sourcely searches through a vast data set to locate relevant and reliable sources, providing academic writers with the information needed to support their work.

Sourcely offers great affordability with a price of $5.99 per month or $36.99 per year. While it may have fewer features compared to other academic writing tools, its lower price point still makes it a valuable and useful tool for academic writing.

Rytr is a text-generating AI tool. Depending on the purpose, academics can find it useful for selecting from multiple languages and tones of voice, as well as rewording and shortening text.

Alternatively, the Unlimited plan is available at $29 per month or $290 per year. These different pricing tiers cater to the diverse needs of users, ensuring they can find the plan that best suits their requirements.

10. Writesonic

Upon generating a paragraph, Writesonic provides three different versions for you to choose from. It allows you to select the best option or make edits and revisions using the various variations.

11. TextCortex

TextCortex is an AI tool which can condense long texts into concise summaries, capturing the essential points.

Summary and Top Picks

The landscape of AI writing tools is continuously evolving, witnessing the introduction of new tools regularly. However, not all these tools are equally suitable for academic writing, as their effectiveness depends on your specific goals and requirements.

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Using AI for research: A beginner’s guide

Table of Contents

From the invention of the first wheel for moving around faster to Galileo observing the cosmos using a telescope, there has been no shortage of instances where scientists have used technology to do their work more efficiently. And isn’t that the whole point? Since human faculties can be limiting.

Using AI for research is no different, particularly in current times where the research landscape is evolving at an unprecedented rate. New scientific domains are sprouting frequently, millions of papers are being published every year , and there are vast amounts of data needing to be synthesized.

This is where artificial intelligence can assist, augment, and even revolutionize the way we discover, conduct, and write scientific research. Generative AI has proven itself to be more than a simple buzzword to the point where it can provide real useful value to a researcher at any level.

How can you use AI for research?

AI has proven itself to be handy in many professional circumstances. In academic research , you can easily fit it into several stages of your workflow. Here are some of the ways you can use it:

Finding and reviewing relevant papers

If you go about conducting a manual literature review, you’re talking about countless days of dedicated effort in search and reading. On the other hand, AI can significantly reduce the time and effort it takes to conduct a literature review.

There are AI search engines in plenty that comb through vast databases of research papers, identify relevant papers, and even summarize key findings. This can help you speed up paper analysis, find trends or gaps in the literature, and discover a research question faster.

Most of these AI research assistants help you discover new research articles based on a more accurate semantic search. Even if you don’t have the right keyword, you will still be able to find the correct papers.

Comprehending academic papers

AI can make academic papers easier to read and understand by simplifying jargon and complex topics in research papers. They can also summarise long papers into shorter reads so that you save quite some time while going through heaps of scientific articles.

Some AI assistants let you interact with papers, meaning you can essentially have a conversation with the PDF you’re reading. You can enter prompts like a simple question to get an answer or even ask to create a presentation. The AI tool will read the paper and give the output.

Academic AI tools are also alleviating language barriers by allowing users to do the above task in their native languages.

Data collection and analysis

AI can automate data collection processes by quickly gathering information by mining large databases. Even more impressive is when AI starts analyzing this huge data. For humans, it would be unfathomable to go through a mountain of data, uncovering patterns, trends, and correlations. However, for AI tools, it’s a rather easy process with less room for error.

Whether it’s data entry or data analysis, manually working with data can be an uphill task. Through AI, you will be able to arrive at more accurate insights faster, which sets a high-quality foundation for your research.

Better academic writing

Language models can assist in better writing regardless of your comprehension skill.

They can help with accurate citations, along with providing grammar and style suggestions as you are writing your paper or essay. This means you can now automate proofreading and creating citations.

AI also solves the problem of stiff scientific writing. Tools like paraphrasers and co-writers give you a great opportunity to instantly improve your writing skills and convey your thoughts in the way you actually wish.

Seamless team collaborations

AI can significantly enhance group projects where collaboration and communication are of focus. Through project management research tools, you can automate tedious tasks, manage documents better, and facilitate better communication by creating common workspaces online.

If you’re working with people from different linguistic backgrounds, AI can help you translate in real-time while you’re on calls.

Instant plagiarism checks

Maintaining academic integrity is a non-negotiable while submitting papers. AI tools can help detect plagiarism or the presence of AI in your writing. These tools scan your work, compare it to an extensive database of academic and online content, and flag potential instances of plagiarism.

Similarly, AI detectors recognize the pattern that AI writing follows and proceed to highlight any instances of such writing in your prose.

Best AI tools for research workflows

Combine the importance of AI in modern-day research life with this huge wave of generative AI and ChatGPT in the past couple of years, it should come as no surprise that there is a host of extremely helpful AI tools for research.

Here are 5 best AI tools for researchers which can be integrated to your workflow:

SciSpace is an AI platform specifically made for researchers that eases research discovery, reading, and writing. It sits on top of a repository of 270 million+ papers and offers a spectrum of AI tools, including a literature review tool to find relevant information about scientific papers and an AI research assistant called SciSpace Copilot to answer questions about any PDF document. There is also a Copilot Chrome browser extension that can help you understand academic articles on any website.

Litmaps is a handy discovery tool that assists researchers in navigating through scientific literature. It generates interactive literature maps consisting of articles related to a specific journal article or research topic. These maps enable researchers to find appropriate papers, connect the pattern between them, and exchange their knowledge about a particular field of study. The tool is both free and paid

EndNote is a reference managing tool that assists you in sorting your bibliographies and references while writing essays, reports, and journal articles. It allows you to create a personal database of references and files, as well as insert references into a Word document and automatically format them in your preferred citation style.

One of the more widely known free productivity software, Notion lets you jot down notes, arrange thoughts, and handle tasks and projects efficiently. During research, Notion can be an excellent tool when you’re collaborating with teams as your team members can comment on the documents, create dynamic content like tables, graphs, etc., and use its AI assistant to complete their tasks.

Otter.ai is a boon while you’re in meetings or recording audio while you work. The AI tool automatically transcribes everything you’re saying and generates live captions during meetings. You can also connect Otter.ai with popular meeting apps like Zoom or Google Meet.

Best practices while using AI for academic research

While AI is predominantly a boon for researchers, all things have their pros and cons. AI is still a technology in its infancy, as experts call it, and it should be treated as such. So before you become completely dependent on it, here are a few things you should keep in mind while using an AI-powered research tool:

Ensure data quality and bias

Before you start to analyze data using AI, take a moment to consider the quality of your input. Because if you feed low-quality data to a machine, you can't expect a high-quality output. That just isn’t how it works.

AI cannot think for itself in the same way humans do. At best, it can learn from everything it has been fed and predict an output. So, make sure your data is premium, representative, and, most importantly, unbiased. Biased data can lead to skewed results and questionable conclusions.

Adhere to academic ethics

To reiterate again, academic researchers are bound by academic integrity. Plagiarism, AI-assisted writing, and privacy regulations are all of the highest priority while publishing a paper.

Thus, it’s always better to ensure your research complies with ethical standards and you use necessary plagiarism and AI detection tools before submitting your paper. How you write a paper is a reflection of who you are as a professional.

Check for hallucinations

While AI may seem perfect at all times, it has its moments that make you question the validity of the entire technology.

Sometimes, AI systems can generate results that seem plausible but are entirely incorrect or generate complete gibberish. There are also times when an AI might give you the correct answer but fake its sources. This is popularly known as a hallucination.

It’s quite obvious how it can be detrimental to your academic research, thus it’s always better to fact-check AI-generated output. Some AI assistants have real citations in their answers now, which helps build trust.

Maintain human oversight

While AI can automate and streamline many tasks, it can't replace human judgment, context, and expertise. And given how AI can, at times, hallucinate or give false output, it’s always better to have your human judgment review everything.

To leave you with

The academic world has undergone a profound change in the last few years thanks to AI. For some, it’s an invaluable resource from streamlining literature reviews to supercharging data analysis and academic writing. For others, it’s a grey area and presents some real concerns relating to academic integrity and watering down of content.

But the fact remains that AI, in most cases does help researchers around the world become more efficient, thus producing good-quality work in less time. As language models develop more and more, the use of AI for research will become even more prominent.

Frequently Asked Questions

AI tools can be used in research for finding relevant papers, reviewing and comprehending complex papers, data collection and analysis, better academic writing, and plagiarism detection.

Some of the best AI tools for researchers include SciSpace, Litmaps, Endnote, Notion, and Otter.ai.

Yes, you can use AI tools to write a research paper. From streamlining literature reviews to supercharging data analysis and academic writing, AI tools can make research more efficient. However, human intervention is vital to provide factual information to the readers.

AI can be used to identify relevant papers, summarize key findings, automate data collection, improve academic writing, and also detect plagiarism.

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Top AI Tools for Academic Research

Founder, Junia AI

Introduction

Academic research , once a tedious process involving hours spent in libraries and manual data collection, is now increasingly digitized. Technological advancements have made this critical aspect of knowledge generation more efficient and accessible.

One visionary who foresaw this transformation is Bill Gates . Known for his insightful predictions, Gates anticipated that AI-driven software would revolutionize education and academia within a span of 5-10 years. And true to his words, we are witnessing a surge in the use of AI writing tools for academic research.

These AI tools are not just augmenting traditional research methods but are reshaping them altogether. They offer a myriad of benefits like accelerating the pace of research, enhancing accuracy, and democratizing access to academic resources.

In this article, we have compiled a list of the top AI writing tools for academic research. These tools employ natural language processing algorithms to assist researchers in various aspects of the research process, including:

• Generating ideas and outlining papers
• Finding relevant sources
• Proofreading and editing

Best AI Tools For Research: Our Top Picks

thout reading entire text and establishes relationships between concepts across documents. | | 5 | Scite.ai | Analyzes citation patterns in scholarly articles to assess impact/credibility of papers. Categorizes citations as supporting/mentioning/disputing original paper's claims/findings. | | 6 | Research Rabbit | Web app for scientific literature exploration/understanding. Creates organized collections of relevant papers using advanced algorithms analyzing content/metadata (keywords/abstracts/citation networks). | | 7 | Google Scholar | Extensive online repository of scholarly literature across disciplines. Uses AI algorithms to rank documents by relevance and tracks citations to measure impact. | | 8 | Trinka | Improves academic papers' quality by providing feedback on sentence structure, vocabulary usage, overall coherence. |

1. Junia AI

Junia AI is a leading AI writing tool for academic research, and its citation generator feature is one of its standout offerings. With Junia AI, citing research sources becomes a breeze, saving you time and effort. Let's take a closer look at what makes Junia AI the go-to citation tool for researchers and academicians.

How Junia AI Works

Junia AI utilizes advanced algorithms to simplify the citation process. It has access to a vast database of sources, which allows it to generate accurate citations in various styles such as APA, MLA, and Chicago. Here's how it works:

• Input Source Details: You provide the necessary information about your source, such as author name, publication title, year of publication, etc.
• Select Citation Style: You choose the desired citation style from the available options.
• Generate Citations: Junia AI applies its algorithms to create citations based on the provided details and selected style.

Key Benefits of Using Junia AI

Using Junia AI for your citation needs offers several advantages that can enhance your research process:

1. Time Efficiency

Manually citing sources and formatting reference lists can be time-consuming, especially when dealing with multiple styles. With Junia AI, you can save valuable time by letting the tool handle these tasks for you.

2. Accuracy

Correctly citing your sources is crucial in academic writing as it adds credibility to your work and prevents plagiarism issues. Junia AI's advanced algorithms ensure that your citations are precise and consistent with the chosen style.

3. Ease of Use

Despite its sophisticated features, Junia AI remains user-friendly. Its intuitive interface makes it easy to enter source details, and its ability to generate citations instantly is a boon for researchers working under tight deadlines.

4. Versatility

Whether you're citing a book, a scholarly journal, a website, or any other type of source, Junia AI has got you covered. It supports a wide range of source formats, making it a versatile tool for all your citation requirements.

While Junia AI offers significant benefits for academic writing, it's worth noting that there are other AI-driven tools available to assist you throughout your research journey.

ChatGPT , developed by OpenAI , is an essential tool for academic research. This language model is specifically designed for generating text, making it a valuable assistant for scholars and researchers.

The Power of Incremental Prompting

The key feature of ChatGPT that resonates with academia is its incremental prompting feature. Incremental prompting allows researchers to create detailed outlines for their journal articles or research papers. With this feature, you can provide the model with a series of related prompts one by one, and it will respond accordingly. This step-by-step approach leads to more coherent and detailed responses.

This capability not only simplifies the writing process but also makes it more structured and organized. It's like having an intelligent assistant that helps you arrange your thoughts and ideas into well-defined sections or chapters of the research document.

Versatility in Document Handling

One of the strengths of ChatGPT lies in its ability to work with different types of documents. It can browse the web, interact with files (including PDFs and other formats), making it convenient for users to access various sources during their research work.

This ability is particularly useful when dealing with large PDF files or complex documents where finding relevant information can be challenging. With ChatGPT, you can simply upload your file, ask specific questions about its content, and get precise answers instead of having to read through the entire document.

Case Study: Stanford University

Let's look at an example from Stanford University where ChatGPT was tested by students and professors . They used this AI tool as part of their academic writing process - from generating ideas to creating outlines for journal articles.

• In one instance, a PhD student working on a paper about AI ethics used ChatGPT to generate an outline for his document. He started with a broad prompt on AI ethics which yielded a general response from the model. He then gradually added more specific prompts, leading the model to generate a detailed and organized outline of the paper.
• In another case, a professor at Stanford used ChatGPT for preparing his lectures. He would prompt the model with a topic he planned to teach and based on the generated responses, he would create an outline for his lecture.

These real-life examples demonstrate the effectiveness of ChatGPT in academic writing. It's not just about easing the writing process but also enhancing it by providing a new way to structure your thoughts, ideas, and findings. As Bill Gates predicted, AI-driven software like ChatGPT is indeed revolutionizing education and academia.

From these examples and many more, it is clear that using an AI tool like ChatGPT can significantly improve the academic writing process. By providing structure to your work, generating ideas, and making information retrieval easier, such tools are proving to be game-changers in academic research.

3. Consensus

Consensus is a specialized search engine designed for academics, leveraging advanced Artificial Intelligence to provide accurate and concise summaries of peer-reviewed articles.

How Consensus Works

The power of Consensus lies in its AI algorithms, which analyze the content of papers to extract key information. This makes it more than just a regular search engine - it's a tool that can distill complex academic papers into easy-to-understand summaries.

Why Choose Consensus?

When it comes to finding relevant sources for your research, Consensus offers several advantages over traditional search engines:

Features of Consensus

• Summarized Evidence : Consensus provides summarized evidence from peer-reviewed literature, allowing you to quickly grasp the main points of a paper without reading the entire document.
• AI-Powered Search Engine : Unlike keyword-based search engines, Consensus understands the context and relevance of your query, delivering more precise results.
• User-Friendly Interface : With its simple yet efficient interface, Consensus makes it easy for you to navigate the platform and find what you need.

Benefits of Using Consensus

Using Consensus during the literature review stage of your academic research projects can bring several benefits:

• Efficient Information Retrieval : By providing concise summaries of peer-reviewed articles, Consensus helps you save time during the literature review process.
• Access to Quality Sources : As Consensus focuses on peer-reviewed literature, using it ensures that you're accessing reliable and academically sound sources.
• Time-Saving : Thanks to its AI-powered search engine, Consensus delivers relevant results quickly, allowing you to work more efficiently.
• Improved Understanding : The summarized evidence provided by Consensus can enhance your understanding of the topic at hand, making your research more comprehensive.
• Ease of Use : With its user-friendly interface and straightforward functionality, Consensus is a tool that seamlessly integrates into your academic writing workflow.

Consensus serves as an example of how AI can transform the way academic research is conducted. As we embrace the digital age, tools like Consensus are becoming essential for researchers in various fields. By harnessing the power of AI, Consensus paves the way for more efficient and effective academic research, allowing you to focus on what truly matters - creating impactful knowledge.

4. Elicit.org

Elicit.org is an AI-powered tool designed to streamline the research process by assisting in conducting comprehensive literature reviews and extracting relevant data from various sources. It is one of the top AI writing tools for academic research that has been embraced by researchers worldwide.

How Elicit.org Works

The power of Elicit lies in its sophisticated algorithms that analyze the content of documents. These algorithms are capable of identifying key concepts, relationships, and findings within a sea of information. This feature allows users to gain valuable insights for their own research projects in a fraction of the time it would take manually.

Key Features of Elicit.org

Identifying key concepts.

Elicit's AI is programmed to identify and highlight key concepts within a text. This gives you an immediate grasp of the main ideas within a document without having to read it in its entirety.

Establishing Relationships

Another significant feature of Elicit.org is its ability to establish relationships between different documents or concepts. This helps to build a comprehensive understanding of the subject matter.

Extracting Findings

Finally, it can extract critical findings from research papers, providing you with specific data points that may be relevant to your research.

The practical applications of these features are numerous. For instance, if you were conducting a literature review on climate change, Elicit.org could:

• Analyze hundreds of papers
• Identify the key concepts such as 'global warming', 'carbon emissions', 'deforestation', etc.
• Establish relationships between these concepts across different papers
• Extract critical data points like specific carbon emission figures.

Try Elicit.org for Your Research

Elicit.org has truly revolutionized the way researchers approach literature review and data extraction, making it a crucial AI tool for academic research. By integrating Elicit.org into your research workflow, you can leverage its AI capabilities to make your research process more efficient and effective.

5. Scite.ai

Scite.ai , a unique platform that stands out in its approach to enhancing the credibility of research.

Beyond Traditional Citation Tools

Scite.ai is not just a citation tool; it uses artificial intelligence to analyze citation patterns in scholarly articles meticulously. This insightful analysis offers users contextual information about how particular studies have been cited by other researchers. It's like having an intelligent assistant who can tell you not just who is citing your work, but also how and why they are citing it.

How Does Scite.ai Enhance Research Validation?

The primary focus of Scite.ai is on research validation. This is where the tool truly shines. In simple terms, Scite.ai helps scholars assess the impact and credibility of published papers more effectively. Its underlying AI technology sifts through the multitude of citations associated with any article, cutting through the noise to provide meaningful insights. It uses these insights to determine whether a paper has been positively or negatively received, based on the context within which it has been cited in subsequent works.

But how does this work?

Scite.ai takes each citation and breaks it down into three categories:

• Supporting : The citing work provides evidence in favor of the assertions made in the original paper.
• Mentioning : The citing work refers to the original paper but does not explicitly support or dispute its content.
• Disputing : The citing work challenges or contradicts the findings or claims made in the original paper.

This categorization gives a clear snapshot of how other researchers view your study, which can be invaluable when assessing its impact and validity.

Benefits of Using Scite.ai for Academic Writing

Incorporating Scite.ai into your academic writing process comes with several potential benefits:

• Strengthening Arguments : Knowing how others perceive your references can help you build stronger arguments by choosing sources that have been widely accepted and supported.
• Supporting Claims : Scite.ai gives you an edge by letting you back up your claims with references that have been positively cited in other works.
• Enhancing Credibility : A paper that includes well-regarded sources increases its credibility in the academic community, potentially leading to more citations and higher impact.

Understanding the Context of Citations

Scite.ai's approach to assessing the impact of papers does not stop at categorization. It also provides a 'citation statement', which is a brief excerpt from the citing text. This allows users to understand the context and rationale of the citation without having to read through the entire citing article.

For example, if a researcher is writing about climate change and selects a paper as a reference, Scite.ai not only shows how many times the paper has been cited but also provides an overview of whether these citations are supporting, mentioning or disputing it. This information paints a more in-depth and detailed picture of how the chosen paper has been received by the scientific community.

The Power of Scite.ai for Scholars

In essence, Scite.ai is a powerful ally for any scholar. It provides unique insights into citation patterns, enabling users to make informed decisions about which sources to use and how to present their arguments effectively. The ability to validate research, bolster arguments, and enhance credibility makes Scite.ai an indispensable tool in today's digital age where academic integrity is paramount.

6. Research Rabbit

Research Rabbit is an innovative AI tool designed to assist with exploring and understanding scientific literature. It's a web application that helps researchers navigate through scientific literature, enabling them to create organized collections of pertinent papers.

Utilizing advanced algorithms, Research Rabbit analyzes both content and metadata of articles. The analysis allows the application to suggest related works, providing researchers with new perspectives and connections they might have overlooked.

How Does Research Rabbit Work?

Research Rabbit employs AI algorithms to scrutinize the content and metadata of articles. This process includes evaluating keywords, abstracts, author affiliations, citation networks, and even figures and tables within the paper. This comprehensive approach provides a deeper understanding of the article's context and relevance.

The system then recommends other relevant articles based on its analysis. This feature aids researchers in uncovering new links between studies and gaining interdisciplinary insights.

Benefits of Using Research Rabbit

The use of Research Rabbit can bring multiple benefits to both novice and experienced researchers:

• Keeping Up With Latest Developments : The rapid pace at which new research papers are published makes it challenging for researchers to stay updated. Research Rabbit addresses this issue by providing recommendations based on recent publications related to their chosen topics.
• Identifying Research Gaps : By reviewing related papers suggested by Research Rabbit, researchers can identify gaps in current knowledge and thereby find opportunities for novel research.
• Improving Efficiency : Instead of manually searching for relevant studies, researchers can rely on Research Rabbit's AI-powered suggestions, saving valuable time.
• Enhancing Understanding : By presenting different perspectives on a topic through related works, Research Rabbit fosters a more comprehensive understanding of the subject matter.

To illustrate this process, consider a researcher studying climate change's impact on agriculture. After inputting their research papers into Research Rabbit, the application might suggest articles about innovative farming practices in response to climate change or economic studies on how climate change affects agricultural markets. These suggestions can lead the researcher to consider new angles for their work, promoting a more nuanced and complete analysis.

Research Rabbit represents a significant advancement in AI writing tools for academic research. Its ability to analyze literature and suggest related works enables researchers to delve deeper into their topics, discover new perspectives, and stay abreast of the latest developments in their field. By harnessing this technology, researchers can enhance the depth and breadth of their studies while improving their productivity.

7. Google Scholar

Google Scholar , a well-known platform for academic research, is an extensive online collection of scholarly literature across various fields. It has become an essential tool in the academic world because of its vast collection of research articles, conference papers, theses, books, and patents from professional societies, online repositories, universities, and other scholarly organizations.

Google Scholar uses advanced AI algorithms to rank documents based on their relevance, considering factors such as the full text of each document, where it was published, who authored it, and how frequently and recently it has been cited in other literature. As a result, researchers can access a wide range of scholarly content that might not be available through other search engines.

Finding Relevant Sources with Google Scholar

When doing academic research, the challenge often lies not in finding information but in finding relevant information. By using Google Scholar 's advanced search features effectively, you can overcome this challenge.

General Search

Simply enter your keywords into the search bar for a list of relevant resources.

Advanced Search

Click on the menu icon on the top left of the page and select "Advanced Search" for more specific queries. You can:

• Search for exact phrases
• Exclude certain words
• Search within specific publications or authors

Author Verification

If you're searching for articles from a particular author, make sure that they have verified their Google Scholar profile to avoid confusion with authors having similar names.

Tracking Citations: Measure Your Impact

One of the unique features of Google Scholar is its citation tracking capability. This feature allows researchers to measure the impact and influence of their work within the academic community.

This link under each result shows how many times an article has been cited by other papers indexed on Google Scholar . It's a helpful indicator of an article's influence or importance in a field.

Google Scholar Citations

This feature lets authors track citations to their articles. You can check who is citing your publications, graph citations over time, and compute several citation metrics.

Tips and Strategies: Maximizing Google Scholar's Effectiveness

The value derived from Google Scholar largely depends on how effectively you use its features. Here are some strategies to enhance your academic writing endeavors:

• Refine Your Search : Use boolean operators like AND, OR, NOT, "", and - to narrow or broaden your search.
• Personalized Updates : Set up alerts for new content that matches your specified criteria (such as author or keyword). This helps you stay updated with the latest research in your field of interest.
• Export Citations : Google Scholar allows you to export citations in various formats (like BibTeX, EndNote, RefMan, or RefWorks) which can be directly imported into your reference management software.

Google Scholar is considered one of the most powerful academic search engines available. Its comprehensive database coupled with advanced AI algorithms makes it an invaluable tool for academic research. By understanding its features and learning how to leverage them effectively, you can streamline your academic writing process and produce well-researched scholarly work.

Trinka is an advanced writing assistant powered by AI that aims to improve the quality of academic papers. It provides researchers with valuable feedback and suggestions to refine their writing style and eliminate grammatical errors.

How Does Trinka Help Improve Your Writing?

Trinka uses advanced algorithms to analyze your text thoroughly, focusing on three main areas:

1. Sentence Structure

Trinka examines each sentence in your paper for clarity, coherence, and conciseness. It suggests revisions to make your writing easier to understand.

2. Vocabulary Usage

The tool identifies complex or inappropriate words in your writing and suggests simpler alternatives.

3. Overall Coherence

Trinka evaluates the logical flow of ideas and arguments throughout your paper, highlighting areas that may need further explanation or reorganization.

By addressing these aspects, Trinka helps you create a well-written academic paper with a strong foundation.

"Trinka is more than just a grammar-checking tool. It is a smart companion that understands the nuances of academic writing and can assist you in producing high-quality papers.

The Power of AI Writing Tools for Academic Research

With the rapid advancements in technology, an important shift has taken place in the academic research arena. The emergence of AI writing tools for academic research has become a game-changer, improving both efficiency and quality in research efforts. These tools offer a wide range of capabilities that can help at every stage of the academic writing process.

Adapting to Technological Advancements

The world of academia is changing quickly. Researchers now need to keep up not only with developments in their own fields but also with broader technological trends that could affect their work. This includes embracing advancements like AI, which can greatly enhance research endeavors.

One example of this is Scite.ai . This platform uses AI to analyze citation patterns in scholarly articles, giving users contextual information about how a particular study has been cited by other researchers. This approach to research validation can help scholars better understand the impact and reliability of published papers. By using such tools, researchers can strengthen their arguments and support claims with trustworthy references, thereby improving the credibility of their work.

Experimenting with AI Tools

Innovation is key in academic research. That's why it's crucial for researchers to constantly explore and experiment with new methods and technologies that can enhance their work. This includes trying out various AI writing tools mentioned in this article.

For instance, you might want to consider using Research Rabbit for exploring scientific literature and creating organized collections of relevant papers. Its algorithms analyze the content and metadata of articles to suggest related works, enabling you to discover new connections and interdisciplinary perspectives. Such tools not only streamline your literature review process but also inspire new research directions.

The Future is Here

These AI writing tools are not just about keeping up with technological advancements; they are about embracing the future of academic research. As researchers, it's important for us to adapt and evolve alongside these changes, integrating technology into our workflows to improve efficiency and enhance the quality of our work.

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A free, AI-powered research tool for scientific literature

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New & Improved API for Developers

Introducing semantic reader in beta.

Stay Connected With Semantic Scholar Sign Up What Is Semantic Scholar? Semantic Scholar is a free, AI-powered research tool for scientific literature, based at Ai2.

Enhance your research with AI built for trust

Ask our AI or search the literature to transform the way you discover, review, and connect scientific research.

Trusted by leading Universities, Publishers, and Corporations.

What makes Scite different from other tools?

Scite is an award-winning platform built on the world's largest citation statement database. We analyzed 1.2 billion citations from 200 million sources to create Smart Citations, which provide context and classify citations as supporting or contrasting evidence. This database also powers our AI chatbot, Assistant, and our literature search engine.

Extracted citations in a report page

Never waste time looking for and evaluating research again.

Our innovative index of Smart Citations powers new features built to make research intuitive and trustworthy for anyone engaging with research.

Find information by searching across a mix of metadata (like titles & abstracts) as well as Citation Statements we indexed from the full-text of research articles.

Build and manage collections of articles of interest -- from a manual list, systematic review, or a search -- and get aggregate insights, notifications, and more.

Evaluate how references from your manuscript were used by you or your co-authors to ensure you properly cite high quality references.

Explore pre-built journal dashboards to find their publications, top authors, compare yearly scite Index rankings in subject areas, and more.

Large Language Model (LLM) Experience for Researchers

Assistant by scite gives you the power of large language models backed by our unique database of Smart Citations to minimize the risk of hallucinations and improve the quality of information and real references.

Use it to get ideas for search strategies, build reference lists for a new topic you're exploring, get help writing marketing and blog posts, and more.

Assistant is built with observability in mind to help you make more informed decisions about AI generated content.

Here are a few examples to try:

"How many rats live in NYC?"

"How does the structure of a protein affect its function?"

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Trusted by researchers and organizations around the world

Over 969,000 students, researchers, and industry experts use scite

See what they're saying

scite is an incredibly clever tool. The feature that classifies papers on whether they find supporting or contrasting evidence for a particular publication saves so much time. It has become indispensable to me when writing papers and finding related work to cite and read.

Emir Efendić, Ph.D

Maastricht University

As a PhD student, I'm so glad that this exists for my literature searches and papers. Being able to assess what is disputed or affirmed in the literature is how the scientific process is supposed to work, and scite helps me do this more efficiently.

Kathleen C McCormick, Ph.D Student

scite is such an awesome tool! It’s never been easier to place a scientific paper in the context of the wider literature.

Mark Mikkelsen, Ph.D

The Johns Hopkins University School of Medicine

This is a really cool tool. I just tried it out on a paper we wrote on flu/pneumococcal seasonality... really interesting to see the results were affirmed by other studies. I had no idea.

David N. Fisman, Ph.D

University of Toronto

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Using AI tools

AI Writing Tools | Definition, Uses & Implications

AI writing tools are artificial intelligence (AI) software applications like ChatGPT that help to automate or assist the writing process. These tools use machine learning algorithms to generate human-sounding text in response to users’ text-based prompts.

Other AI tools, such as grammar checkers , paraphrasers and summarizers serve more specific functions, like identifying grammar and spelling mistakes or rephrasing text.

Table of contents

How do ai writing tools work, what can ai writing tools be used for, implications of ai writing tools, other interesting articles, frequently asked questions about ai writing tools.

AI writing tools (chatbots, grammar checkers, etc.) use natural language processing (NLP) algorithms, machine learning , and large language models (LLMs) to generate or improve written text. These tools are trained to identify patterns in vast amounts of data. The tools then use these patterns to analyze human inputs (or prompts) and generate natural-sounding outputs (similar to how predictive text works).

Different AI tools may be programmed in different ways. For example, ChatGPT, the popular chatbot developed by OpenAI and released in November 2022, uses generative pre-trained transformers (GPTs) and was trained using reinforcement learning from human feedback (RLHF) , meaning that the tool was given feedback from humans to help guide it towards the most helpful responses.

AI writing tools have a number of helpful applications. Some of these applications are discussed below.

Interactive learning and feedback

Generative AI tools can be helpful resources for conversational learning. By inputting questions, users can engage in interactive learning at any time.

You can also prompt these tools to provide feedback on your work to improve the clarity or consistency of your writing. However, it’s important not to upload sensitive information, as user inputs are generally saved by the tool for the purposes of training future models.

Below is an example of how ChatGPT can be used for interactive learning.

Example: Using ChatGPT for interactive learning

• Tell me three facts about Carthaginian culture
• Carthaginians were known for their maritime trade and commerce, and their navy was one of the strongest in the ancient Mediterranean world. They established colonies and trading posts throughout the Mediterranean, including in Sicily, Sardinia, and North Africa.
• Carthaginians had a polytheistic religion, and their chief deity was Baal Hammon, the god of fertility, agriculture, and the sky. They also worshiped a number of other gods and goddesses, including Tanit, the goddess of love, fertility, and war.
• Carthaginians were skilled metalworkers and produced a variety of metal goods, including weapons, armor, jewelry, and household objects. They were particularly famous for their bronze work, which was highly prized in the ancient world. Carthaginian bronze was so valued that it was used by the Romans to make their famous statues and other works of art.
• Tell me three more facts about the Carthaginian navy
• The Carthaginian navy was one of the most advanced and powerful navies of the ancient world. It was instrumental in establishing Carthage as a dominant power in the Mediterranean region.
• The Carthaginians were known for their skill in shipbuilding and developed a variety of ship types for different purposes, including warships, transport ships, and cargo ships. One of their most famous ship types was the quinquereme, a large warship with five rows of oars.
• The Carthaginian navy was led by a commander called the “admiral.” The admiral was responsible for overseeing the fleet and making strategic decisions about naval warfare. One of the most famous Carthaginian admirals was Hannibal Barca, who led the Carthaginian fleet during the First Punic War against Rome.

Generating research questions and outlines

AI writing tools can be used to generate potential research questions or research paper outlines . You can then refine the tool’s responses by further prompting it or directly editing the output yourself to ensure the result makes sense and fits your requirements.

Below is an example of how ChatGPT can be used to generate potential reseach questions and research method ideas.

Example: Using ChatGPT to generate research questions and methods

• Develop three possible research questions on the following topic: “The influence of technology on second language acquisition.”
• What is the impact of technology-assisted language learning (TALL) on the acquisition of a second language?
• How do different types of technology, such as mobile applications, virtual reality, and online platforms, affect second language acquisition outcomes?
• How do individual learner characteristics, such as age, proficiency level, and motivation, interact with the use of technology in second language acquisition?
• Suggest three quantitative research methods appropriate to the second question.
• Experimental research: This research method involves manipulating an independent variable (in this case, the type of technology used) to observe its effect on a dependent variable (second language acquisition outcomes). Participants would be randomly assigned to different groups using different types of technology to learn a second language, and then their language acquisition outcomes would be measured and compared.
• Survey research: This research method involves using questionnaires to gather data from a large group of participants. In this case, a survey could be designed to gather information on participants’ use of different types of technology to learn a second language, as well as their language acquisition outcomes. This would allow for a large-scale investigation of how different types of technology are being used, and what their impact might be.
• Correlational research: This research method involves examining the relationship between two or more variables. In this case, a correlational study could be conducted to investigate whether there is a relationship between the type of technology used and language acquisition outcomes. Data could be collected from participants using different types of technology to learn a second language, and then the correlation between the type of technology and language acquisition outcomes could be calculated.

Paraphrasing text

AI tools like ChatGPT and Scribbr’s free paraphrasing tool can help you paraphrase text to express your ideas more clearly, avoid repetition, and maintain a consistent tone throughout your writing.

They can also help you incorporate scholarly sources in your writing in a more concise and fluent way, without the need for direct quotations. However, it’s important to correctly cite all sources to avoid accidental plagiarism.

Summarizing text

AI writing tools can help condense a text to its most important and relevant ideas. This can help you understand complex information more easily. You can also use summarizer tools on your own work to summarize your central argument, clarify your research question, and form conclusions.

You can do this using generative AI tools or more specialized tools like Scribbr’s free text-summarizer .

Proofreading text

AI writing tools can be used to identify spelling, grammar, and punctuation mistakes and suggest corrections. These tools can help to improve the clarity of your writing and avoid common mistakes .

While AI tools like ChatGPT offer useful suggestions, they can also potentially miss some mistakes or even introduce new grammatical errors into your writing.

We advise using Scribbr’s proofreading and editing service  or a tool like Scribbr’s free grammar checker , which is designed specifically for this purpose.

Translating text

AI translation tools like Google Translate can be used to translate text from a source language into various target languages. While the quality of these tools tend to vary depending on the languages used, they’re constantly developing and are increasingly accurate.

While there are many benefits to using AI writing tools, some commentators have emphasized the limitations of AI tools and the potential disadvantages of using them. These drawbacks are discussed below.

Impact on learning

One of the potential pitfalls of using AI writing tools is the effect they might have on a student’s learning and skill set. Using AI tools to generate a paper, thesis , or dissertation , for example, may impact a student’s research, critical thinking, and writing skills.

However, other commentators argue that AI tools can be used to promote critical thinking (e.g., by having a student evaluate a tool’s output and refine it).

Consistency and accuracy

Generative AI tools (such as ChatGPT) are not always trustworthy and sometimes produce results that are inaccurate or factually incorrect. Although these tools are programmed to answer questions, they can’t judge the accuracy of the information they provide and may generate incorrect answers or contradict themselves.

It’s important to verify AI-generated information against a credible source .

Grammatical mistakes

While generative AI tools can produce written text, they don’t actually understand what they’re saying and sometimes produce grammar, spelling, and punctuation mistakes.

You can combine the use of generative AI tools with Scribbr’s grammar checker , which is designed to catch these mistakes.

Ethics and plagiarism

As AI writing tools are trained on large sets of data, they may produce content that is similar to existing content (which they usually cannot cite correctly), which can be considered plagiarism.

Furthermore, passing off AI-generated text as your own work is usually considered a form of plagiarism and is likely to be prohibited by your university. This offense may be recognized by your university’s plagiarism checker or AI detector .

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
• Best grammar checker
• Best paraphrasing tool
• ChatGPT in your studies
• Is ChatGPT trustworthy?
• Types of plagiarism
• Self-plagiarism
• Avoiding plagiarism
• Academic integrity
• Best plagiarism checker

Citing sources

• Citation styles
• In-text citation
• Citation examples
• Annotated bibliography

AI writing tools can be used to perform a variety of tasks.

Generative AI writing tools (like ChatGPT ) generate text based on human inputs and can be used for interactive learning, to provide feedback, or to generate research questions or outlines.

These tools can also be used to paraphrase or summarize text or to identify grammar and punctuation mistakes. Y ou can also use Scribbr’s free paraphrasing tool , summarizing tool , and grammar checker , which are designed specifically for these purposes.

Using AI writing tools (like ChatGPT ) to write your essay is usually considered plagiarism and may result in penalization, unless it is allowed by your university . Text generated by AI tools is based on existing texts and therefore cannot provide unique insights. Furthermore, these outputs sometimes contain factual inaccuracies or grammar mistakes.

However, AI writing tools can be used effectively as a source of feedback and inspiration for your writing (e.g., to generate research questions ). Other AI tools, like grammar checkers, can help identify and eliminate grammar and punctuation mistakes to enhance your writing.

You can access ChatGPT by signing up for a free account:

• Follow this link to the ChatGPT website.
• Click on “Sign up” and fill in the necessary details (or use your Google account). It’s free to sign up and use the tool.
• Type a prompt into the chat box to get started!

A ChatGPT app is also available for iOS, and an Android app is planned for the future. The app works similarly to the website, and you log in with the same account for both.

Yes, ChatGPT is currently available for free. You have to sign up for a free account to use the tool, and you should be aware that your data may be collected to train future versions of the model.

To sign up and use the tool for free, go to this page and click “Sign up.” You can do so with your email or with a Google account.

A premium version of the tool called ChatGPT Plus is available as a monthly subscription. It currently costs $20 and gets you access to features like GPT-4 (a more advanced version of the language model). But it’s optional: you can use the tool completely free if you’re not interested in the extra features.

ChatGPT was publicly released on November 30, 2022. At the time of its release, it was described as a “research preview,” but it is still available now, and no plans have been announced so far to take it offline or charge for access.

ChatGPT continues to receive updates adding more features and fixing bugs. The most recent update at the time of writing was on May 24, 2023.

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

Table of contents

Meredith Sell

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

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

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

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

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

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

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

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

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

How to Properly Write a Research Paper Using AI

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

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

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

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

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

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

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

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

Instead, follow your curiosity.

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

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

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

For example:

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

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

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

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

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

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

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

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

Use a research question to develop your thesis

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

Why were the Irish so dependent on potatoes?

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

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

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

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

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

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

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

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

Does the source cover information relevant to my research question?

Yes: Keep to read later.

No: Discard and move on to the next source.

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

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

5. Make note of the most interesting facts you find

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

Why should you do this?

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

6. Organize your research

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

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

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

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

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

7. Write with your research document open

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

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

Keeping your research document open and in clear view.

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

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

8. Steal the TK trick from journalists

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

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

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

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

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

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

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

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

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

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

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

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

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

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How AI can help you write your research paper

Putting together a research paper can be a daunting task, often involving hours of research, managing information, and crafting a well-structured document. However, the advent of AI-powered tools makes the process more manageable than ever before. Even better than some research tips, explore how AI-powered tools can change the way you build research papers, making the entire process smoother, more precise, and less time-consuming.

Use AI for research

One of the most laborious aspects of writing a research paper is gathering information and conducting thorough research; AI-powered tools can help streamline this process significantly.

Use Copilot in Edge to find relevant research papers, articles, and academic sources with ease. By simply inputting your paper parameters, research topic, or keywords, you can quickly access a vast database of academic resources, saving you hours of scouring the internet. Copilot can also swiftly provide definitions, explanations, and relevant context for unfamiliar terms or passages on the page, eliminating the need to switch between tabs or search engines. Moreover, Copilot can summarize extensive web content and suggest related articles or papers to deepen your understanding. By integrating Copilot into your research workflow, you can enhance productivity and ensure access to up-to-date and pertinent information. 

Organize your paper with AI

Once you've collected the necessary information, you need to organize and structure your research paper effectively. Copilot, accessible right in the sidebar, can help build a clear, well-structured outline for your paper based specifically on your topic and web sources. By inputting key points and subtopics, Copilot can generate a structured outline to serve as a roadmap for your argument. This ensures your research paper is logically organized, making it easier for readers to comprehend.

Come across a concept or fact on the web that you want to use? Something spark an idea you want to get down and revisit? Use the Compose  in the Microsoft Edge sidebar to write up a summary of the idea, or where it fits into your larger argument. Ask for a citation while you’re at it—more on that a little later.

As a bonus, Microsoft Edge’s AI-powered tools check for grammar and spelling errors and provide suggestions to improve the clarity of your writing. If you like writing chunks of your paper as you research, this is ideal. They can help refine your writing style and ensure your ideas are effectively communicated.

Finding sources using AI

Looking for primary or academic sources? Ask Copilot in Edge. With a topic, keywords, and questions, the AI-powered tool can help hunt down possible sources fast. Copilot can provide links and even summaries of the sources. To be sure the sources are credible, always review them for yourself, of course, and make the best decision about what is relevant and persuasive for your paper.

Citing sources using AI

Citing sources and managing references is a crucial aspect of research paper writing—and one of the most dreaded. Fortunately, AI-powered citation and reference management tools can simplify the tedious citation process. As you track sources and collect information across the web, the AI-powered Microsoft Edge sidebar can help generate citations for your sources. Simply ask for Copilot to cite a source using a specific style—typically APA, MLA, or Chicago—and it will find the best citation generator for your paper. The sidebar tools can also serve as a sort of extra set of eyes, checking your footnotes and bibliography for errors or inconsistencies.

Ethical use of AI-powered tools in school

The ethics of using AI for research papers raise important questions about transparency, integrity, and the role of human creativity and critical thinking in academia. While AI-powered tools undeniably offer efficiency and assistance in the research process, it's crucial for researchers to maintain transparency. Proper citation and acknowledgment of AI-generated content or assistance is essential to uphold academic integrity and avoid plagiarism.

Ultimately, the responsible use of AI in research should complement human ingenuity rather than replace it, emphasizing collaboration between technology and researchers to advance knowledge ethically and morally.

Embark on you next research paper with AI’s help

AI-powered tools  like those built into Microsoft Edge have the ability to revolutionize the process of developing research papers. From automating research to helping with organization, citation management, even language translation, these tools offer a variety of benefits to researchers.

When you embark on your next research paper, consider integrating AI-powered tools into your workflow to save time, enhance accuracy, and improve the overall quality of your work. Copilot in Edge is an easy and convenient AI portal for researchers and writers. Try Microsoft Edge  today to tap into the power of AI and improve your research papers today.

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Organizing Your Social Sciences Research Paper

Generative ai and writing.

• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• USC Libraries Tutorials and Other Guides
• Bibliography

Research Writing and Generative AI Large Language Models

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

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

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

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

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

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

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

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

Ethical Considerations

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

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

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

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

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

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

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

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How to Write a Research Proposal: (with Examples & Templates)

Table of Contents

Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.  

Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.  

This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.  

What is a Research Proposal ?  

A research proposal¹ ,²  can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.   

With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.  

Purpose of Research Proposals  

A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.  

Research proposals can be written for several reasons:³  

• To describe the importance of research in the specific topic  
• Address any potential challenges you may encounter  
• Showcase knowledge in the field and your ability to conduct a study  
• Apply for a role at a research institute  
• Convince a research supervisor or university that your research can satisfy the requirements of a degree program  
• Highlight the importance of your research to organizations that may sponsor your project  
• Identify implications of your project and how it can benefit the audience  

What Goes in a Research Proposal?    

Research proposals should aim to answer the three basic questions—what, why, and how.  

The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.  

The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.  

The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.   

Research Proposal Example  

Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.  

Structure of a Research Proposal  

If you want to know how to make a research proposal impactful, include the following components:¹  

1. Introduction  

This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.  

2. Literature review  

This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.  

3. Objectives  

Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.  

4. Research design and methodology  

Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.  

5. Ethical considerations  

This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.  

6. Budget/funding  

Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.  

7. Appendices  

This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.  

8. Citations  

Important Tips for Writing a Research Proposal  

Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5  

The Planning Stage  

• Manage your time efficiently. Plan to have the draft version ready at least two weeks before your deadline and the final version at least two to three days before the deadline.
• What is the primary objective of your research?  
• Will your research address any existing gap?  
• What is the impact of your proposed research?  
• Do people outside your field find your research applicable in other areas?  
• If your research is unsuccessful, would there still be other useful research outcomes?  

  The Writing Stage  

• Create an outline with main section headings that are typically used.  
• Focus only on writing and getting your points across without worrying about the format of the research proposal , grammar, punctuation, etc. These can be fixed during the subsequent passes. Add details to each section heading you created in the beginning.   
• Ensure your sentences are concise and use plain language. A research proposal usually contains about 2,000 to 4,000 words or four to seven pages.  
• Don’t use too many technical terms and abbreviations assuming that the readers would know them. Define the abbreviations and technical terms.  
• Ensure that the entire content is readable. Avoid using long paragraphs because they affect the continuity in reading. Break them into shorter paragraphs and introduce some white space for readability.  
• Focus on only the major research issues and cite sources accordingly. Don’t include generic information or their sources in the literature review.  
• Proofread your final document to ensure there are no grammatical errors so readers can enjoy a seamless, uninterrupted read.  
• Use academic, scholarly language because it brings formality into a document.  
• Ensure that your title is created using the keywords in the document and is neither too long and specific nor too short and general.  
• Cite all sources appropriately to avoid plagiarism.  
• Make sure that you follow guidelines, if provided. This includes rules as simple as using a specific font or a hyphen or en dash between numerical ranges.  
• Ensure that you’ve answered all questions requested by the evaluating authority.  

Key Takeaways   

Here’s a summary of the main points about research proposals discussed in the previous sections:  

• A research proposal is a document that outlines the details of a proposed study and is created by researchers to submit to evaluators who could be research institutions, universities, faculty, etc.  
• Research proposals are usually about 2,000-4,000 words long, but this depends on the evaluating authority’s guidelines.  
• A good research proposal ensures that you’ve done your background research and assessed the feasibility of the research.  
• Research proposals have the following main sections—introduction, literature review, objectives, methodology, ethical considerations, and budget.  

Frequently Asked Questions  

Q1. How is a research proposal evaluated?  

A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6  

• Significance —Does the research address any important subject or issue, which may or may not be specific to the evaluator or university?  
• Content and design —Is the proposed methodology appropriate to answer the research question? Are the objectives clear and well aligned with the proposed methodology?  
• Sample size and selection —Is the target population or cohort size clearly mentioned? Is the sampling process used to select participants randomized, appropriate, and free of bias?  
• Timing —Are the proposed data collection dates mentioned clearly? Is the project feasible given the specified resources and timeline?  
• Data management and dissemination —Who will have access to the data? What is the plan for data analysis?  

Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?  

A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.  

Q3. How long should a research proposal be?  

A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.  

Q4. What are the common mistakes to avoid in a research proposal ?  

A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7  

• No clear objectives: Objectives should be clear, specific, and measurable for the easy understanding among readers.  
• Incomplete or unconvincing background research: Background research usually includes a review of the current scenario of the particular industry and also a review of the previous literature on the subject. This helps readers understand your reasons for undertaking this research because you identified gaps in the existing research.  
• Overlooking project feasibility: The project scope and estimates should be realistic considering the resources and time available.   
• Neglecting the impact and significance of the study: In a research proposal , readers and evaluators look for the implications or significance of your research and how it contributes to the existing research. This information should always be included.  
• Unstructured format of a research proposal : A well-structured document gives confidence to evaluators that you have read the guidelines carefully and are well organized in your approach, consequently affirming that you will be able to undertake the research as mentioned in your proposal.  
• Ineffective writing style: The language used should be formal and grammatically correct. If required, editors could be consulted, including AI-based tools such as Paperpal , to refine the research proposal structure and language.  

Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.  

This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.  

References  

• Sudheesh K, Duggappa DR, Nethra SS. How to write a research proposal? Indian J Anaesth. 2016;60(9):631-634. Accessed July 15, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037942/  
• Writing research proposals. Harvard College Office of Undergraduate Research and Fellowships. Harvard University. Accessed July 14, 2024. https://uraf.harvard.edu/apply-opportunities/app-components/essays/research-proposals  
• What is a research proposal? Plus how to write one. Indeed website. Accessed July 17, 2024. https://www.indeed.com/career-advice/career-development/research-proposal  
• Research proposal template. University of Rochester Medical Center. Accessed July 16, 2024. https://www.urmc.rochester.edu/MediaLibraries/URMCMedia/pediatrics/research/documents/Research-proposal-Template.pdf  
• Tips for successful proposal writing. Johns Hopkins University. Accessed July 17, 2024. https://research.jhu.edu/wp-content/uploads/2018/09/Tips-for-Successful-Proposal-Writing.pdf  
• Formal review of research proposals. Cornell University. Accessed July 18, 2024. https://irp.dpb.cornell.edu/surveys/survey-assessment-review-group/research-proposals  
• 7 Mistakes you must avoid in your research proposal. Aveksana (via LinkedIn). Accessed July 17, 2024. https://www.linkedin.com/pulse/7-mistakes-you-must-avoid-your-research-proposal-aveksana-cmtwf/  

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Get accurate academic translations, rewriting support, grammar checks, vocabulary suggestions, and generative AI assistance that delivers human precision at machine speed. Try for free or upgrade to Paperpal Prime starting at US$19 a month to access premium features, including consistency, plagiarism, and 30+ submission readiness checks to help you succeed.  

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Related Reads:

How to write a phd research proposal.

• What are the Benefits of Generative AI for Academic Writing?
• How to Avoid Plagiarism When Using Generative AI Tools
• What is Hedging in Academic Writing?  

How to Write Your Research Paper in APA Format

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The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

At Sakana AI, we have pioneered the use of nature-inspired methods to advance cutting-edge foundation models. Earlier this year, we developed methods to automatically merge the knowledge of multiple LLMs . In more recent work, we harnessed LLMs to discover new objective functions for tuning other LLMs. Throughout these projects, we have been continuously surprised by the creative capabilities of current frontier models. This led us to dream even bigger: Can we use foundation models to automate the entire process of research itself?

Introduction

One of the grand challenges of artificial intelligence is developing agents capable of conducting scientific research and discovering new knowledge. While frontier models have already been used to aid human scientists, e.g. for brainstorming ideas or writing code, they still require extensive manual supervision or are heavily constrained to a specific task.

Today, we’re excited to introduce The AI Scientist , the first comprehensive system for fully automatic scientific discovery, enabling Foundation Models such as Large Language Models (LLMs) to perform research independently. In collaboration with the Foerster Lab for AI Research at the University of Oxford and Jeff Clune and Cong Lu at the University of British Columbia, we’re excited to release our new paper, The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery .

In our report:

• We propose and run a fully AI-driven system for automated scientific discovery, applied to machine learning research.
• The AI Scientist automates the entire research lifecycle, from generating novel research ideas, writing any necessary code, and executing experiments, to summarizing experimental results, visualizing them, and presenting its findings in a full scientific manuscript.
• We also introduce an automated peer review process to evaluate generated papers, write feedback, and further improve results. It is capable of evaluating generated papers with near-human accuracy.
• The automated scientific discovery process is repeated to iteratively develop ideas in an open-ended fashion and add them to a growing archive of knowledge, thus imitating the human scientific community.
• In this first demonstration, The AI Scientist conducts research in diverse subfields within machine learning research, discovering novel contributions in popular areas, such as diffusion models , transformers , and grokking .

The AI Scientist is designed to be compute efficient. Each idea is implemented and developed into a full paper at a cost of approximately $15 per paper. While there are still occasional flaws in the papers produced by this first version (discussed below and in the report), this cost and the promise the system shows so far illustrate the potential of The AI Scientist to democratize research and significantly accelerate scientific progress.

We believe this work signifies the beginning of a new era in scientific discovery: bringing the transformative benefits of AI agents to the entire research process, including that of AI itself. The AI Scientist takes us closer to a world where endless affordable creativity and innovation can be unleashed on the world’s most challenging problems.

For decades following each major AI advance, it has been common for AI researchers to joke amongst themselves that “now all we need to do is figure out how to make the AI write the papers for us!” Our work demonstrates this idea has gone from a fantastical joke so unrealistic everyone thought it was funny to something that is currently possible.

The remainder of this post provides a more detailed summary of The AI Scientist. Read on for:

• An Overview of how The AI Scientist works.
• More Examples of generated papers and innovations discovered by The AI Scientist.
• Known Limitations and Challenges faced by the current version of The AI Scientist.
• Interesting and unexpected things The AI Scientist sometimes does in order to increase its chance of success, such as modifying and launching its own execution script! We discuss the AI safety implications in our paper.
• A Discussion about ethical and broader future implications of The AI Scientist.

For more details and many more example papers, please see our full scientific report . We are also releasing open source code and full experimental results on our GitHub repository.

Overview of The AI Scientist

The AI Scientist is a fully automated pipeline for end-to-end paper generation, enabled by recent advances in foundation models. Given a broad research direction starting from a simple initial codebase, such as an available open-source code base of prior research on GitHub, The AI Scientist can perform idea generation, literature search, experiment planning, experiment iterations, figure generation, manuscript writing, and reviewing to produce insightful papers. Furthermore, The AI Scientist can run in an open-ended loop, using its previous ideas and feedback to improve the next generation of ideas, thus emulating the human scientific community.

Conceptual illustration of The AI Scientist . The AI Scientist first brainstorms a set of ideas and then evaluates their novelty. Next, it edits a codebase powered by recent advances in automated code generation to implement the novel algorithms. The Scientist then runs experiments to gather results consisting of both numerical data and visual summaries. It crafts a scientific report, explaining and contextualizing the results. Finally, the AI Scientist generates an automated peer review based on top-tier machine learning conference standards. This review helps refine the current project and informs future generations of open-ended ideation.

The AI Scientist has 4 main processes, described next.

Idea Generation . Given a starting template, The AI Scientist first “brainstorms” a diverse set of novel research directions. We provide The AI Scientist with a starting code “template” of an existing topic we wish to have The AI Scientist further explore. The AI Scientist is then free to explore any possible research direction. The template also includes a LaTeX folder that contains style files and section headers, for paper writing. We allow it to search Semantic Scholar to make sure its idea is novel.

Experimental Iteration . Given an idea and a template, the second phase of The AI Scientist first executes the proposed experiments and then obtains and produces plots to visualize its results. It makes a note describing what each plot contains, enabling the saved figures and experimental notes to provide all the information required to write up the paper.

Paper Write-up . Finally, The AI Scientist produces a concise and informative write-up of its progress in the style of a standard machine learning conference proceeding in LaTeX. It uses Semantic Scholar to autonomously find relevant papers to cite.

Automated Paper Reviewing . A key aspect of this work is the development of an automated LLM-powered reviewer, capable of evaluating generated papers with near-human accuracy. The generated reviews can be used to either improve the project or as feedback to future generations for open-ended ideation. This enables a continuous feedback loop, allowing The AI Scientist to iteratively improve its research output.

When combined with the most capable LLMs, The AI Scientist is capable of producing papers judged by our automated reviewer as “Weak Accept” at a top machine learning conference.

Example Papers Generated by The AI Scientist

Here, we highlight some of the machine learning papers The AI Scientist has generated, demonstrating its capacity to discover novel contributions in areas like diffusion modeling, language modeling, and grokking. In our full report, we do a deeper dive into the generated papers and provide more analysis on their strengths and weaknesses.

Diffusion Modeling

Language modeling, limitations and challenges.

In its current form, The AI Scientist has several shortcomings. We expect all of these will improve, likely dramatically, in future versions with the inclusion of multi-modal models and as the underlying foundation models The AI Scientist uses continue to radically improve in capability and affordability.

• The AI Scientist currently doesn’t have any vision capabilities, so it is unable to fix visual issues with the paper or read plots. For example, the generated plots are sometimes unreadable, tables sometimes exceed the width of the page, and the page layout is often suboptimal. Adding multi-modal foundation models can fix this.
• The AI Scientist can incorrectly implement its ideas or make unfair comparisons to baselines, leading to misleading results.
• The AI Scientist occasionally makes critical errors when writing and evaluating results. For example, it struggles to compare the magnitude of two numbers, which is a known pathology with LLMs. To partially address this, we make sure all experimental results are reproducible, storing all files that are executed.

In our report, we dive deeper into The AI Scientists’s current limitations and challenges ahead.

The AI Scientist Bloopers

We have noticed that The AI Scientist occasionally tries to increase its chance of success, such as modifying and launching its own execution script! We discuss the AI safety implications in our paper.

For example, in one run, it edited the code to perform a system call to run itself. This led to the script endlessly calling itself. In another case, its experiments took too long to complete, hitting our timeout limit. Instead of making its code run faster, it simply tried to modify its own code to extend the timeout period. Here are some examples of such code modifications it made:

These issues can be mitigated by sandboxing the operating environment of The AI Scientist. In our full report, we discuss the issue of safe code execution and sandboxing in depth.

Future Implications of The AI Scientist

As with many new technologies, The AI Scientist opens up a Pandora’s box of new issues. While the full report has a more lengthy discussion, here we highlight a few key issues:

Ethical Considerations . While The AI Scientist may be a useful tool for researchers, there is significant potential for misuse. The ability to automatically create and submit papers to venues may significantly increase reviewer workload and strain the academic process, obstructing scientific quality control. Similar concerns around generative AI appear in other applications, such as the impact of image generation.

Furthermore, the Automated Reviewer, if deployed online by reviewers, may significantly lower review quality and impose undesirable biases on papers. Because of this, we believe that papers and reviews that are substantially AI-generated must be marked as such for full transparency.

As with most previous technological advances, The AI Scientist has the potential to be used in unethical ways. For instance, it has the potential to be deployed to conduct unethical research. It could also lead to unintended harm if The AI Scientist conducts unsafe research. For example, if it were encouraged to find novel, interesting biological materials and given access to “cloud labs” where robots perform wet lab biology experiments, it could (without its overseer’s intent) create new, dangerous viruses or poisons that harm people before we realize what has happened. Even in computers, if tasked to create new, interesting, functional software, it could create dangerous computer viruses. The AI Scientist current capabilities, which will only improve, reinforces that the machine learning community needs to immediately prioritize learning how to align such systems to explore in a manner that is safe and consistent with our values.

Open Models . In this project, we used various proprietary frontier LLMs, such as GPT-4o and Sonnet, but we also explored using open models like DeepSeek and Llama-3. Currently, proprietary models such as Sonnet produce the highest quality papers. However, there is no fundamental reason to expect a single model like Sonnet to maintain its lead.

We anticipate that all frontier LLMs, including open models, will continue to improve. The competition among LLMs has led to their commoditization and increased capabilities. Therefore, our work aims to be model-agnostic regarding the foundation model provider. We found that open models offer significant benefits, such as lower costs, guaranteed availability, greater transparency, and flexibility. In the future, we aim to use our proposed discovery process to produce self-improving AI research in a closed-loop system using open models.

The Role of a Scientist. . Ultimately, we envision a fully AI-driven scientific ecosystem including not only LLM-driven researchers but also reviewers, area chairs and entire conferences. However, we do not believe that the role of a human scientist will be diminished. If anything, the role of a scientist will change and adapt to new technology, and move up the food chain.

The introduction of The AI Scientist marks a significant step towards realizing the full potential of AI in scientific research. By automating the discovery process and incorporating an AI-driven review system, we open the door to endless possibilities for innovation and problem-solving in the most challenging areas of science and technology.

But while the current iteration of The AI Scientist demonstrates a strong ability to innovate on top of well-established ideas, such as Diffusion Modeling or Transformers, it is still an open question whether such systems can ultimately propose genuinely paradigm-shifting ideas. Will future versions of The AI Scientist be capable of proposing ideas as impactful as Diffusion Modeling, or come up with the next Transformer architecture? Will machines ultimately be able to invent concepts as fundamental as the artificial neural network, or information theory?

We believe The AI Scientist will make a great companion to human scientists, but only time will tell to the extent to which the nature of our human creativity and our moments of serendipitous innovation can be replicated by an open-ended discovery process conducted by artificial agents.

Want to make the AI that improves AI? Please see our Careers page for more information.

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'AI Scientist' model designed to conduct scientific research autonomously

by Bob Yirka , Tech Xplore

A team of AI researchers at Sakana AI, in Japan, working with colleagues from the University of Oxford and the University of British Columbia, has developed an AI system that can conduct scientific research autonomously.

The group has posted a paper to the arXiv preprint server describing their system, which they call " The AI Scientist ". They have also posted an overview of their system on Sakana's corporate website.

Scientific research is generally a long and involved process. It tends to start with a simple idea, such as, "Is there a way to stop the buildup of plaque on human teeth?" Scientists then research other studies to determine what research has been done on the topic.

After that, they draw up a plan of action, followed by a needs assessment and a cost analysis. If all goes well, a project is initiated and people and material needs are assigned. That is followed by the actual research and the subsequent writing of a research paper to detail the process used and findings. After that, if merited, the paper is published and use is made of the reported discoveries.

This general process can be long, difficult and often expensive, mostly because of manpower costs. In this new effort, the research team eliminated the manpower costs by automating the whole process, from the generation of ideas to delivery of the written paper .

The AI system uses LLMs to mimic the scientific research process and has already been tested by prompting it to carry out tasks related to AI research, which means it is already conducting research with the goal of finding ways to improve its own abilities. The researchers claim their system is currently conducting real science, and as part of such efforts, it is producing acceptance-level papers.

If these claims are validated, this development is likely to have a major impact on the research community. If AI systems begin conducting the kind of research now done by people, millions of jobs could be lost, universities could see enrollments drop and research funding could be dramatically reduced.

On the other hand, such research could lead to major breakthroughs in areas like cancer research , drug development , climate mitigation strategies or perhaps finding a true understanding of such mysteries as gravity, dark matter or why life exists on Earth and seemingly nowhere else.

Github: github.com/SakanaAI/AI-Scientist

Sakana.ai: sakana.ai/ai-scientist/

© 2024 Science X Network

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Sakana AI’s ‘AI Scientist’ conducts research autonomously, challenging scientific norms

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Sakana AI , in collaboration with scientists from the University of Oxford and the University of British Columbia, has developed an artificial intelligence system that can conduct end-to-end scientific research autonomously. This breakthrough, named “ The AI Scientist ,” promises to completely transform the process of scientific discovery.

The AI Scientist automates the entire research lifecycle, from generating novel ideas to writing full scientific manuscripts. “We propose and run a fully AI-driven system for automated scientific discovery, applied to machine learning research,” the team reports in their newly released paper .

Introducing The AI Scientist: The world’s first AI system for automating scientific research and open-ended discovery! https://t.co/8wVqIXVpZJ From ideation, writing code, running experiments and summarizing results, to writing entire papers and conducting peer-review, The AI… pic.twitter.com/SJuat9a2Uw — Sakana AI (@SakanaAILabs) August 13, 2024

This innovative system uses large language models (LLMs) to mimic the scientific process. It can generate research ideas, design and execute experiments, analyze results, and even perform peer review of its own papers. The researchers claim that The AI Scientist can produce a complete research paper for approximately $15 in computing costs.

The dawn of AI-driven discovery: A new era in scientific research

In their study, published on the preprint server arXiv , the researchers detail how The AI Scientist was tested on tasks in machine learning research, including developing new techniques for diffusion models, transformer-based language models, and analyzing learning dynamics. According to the team, the system produced papers that “exceed the acceptance threshold at a top machine learning conference as judged by our automated reviewer.”

This development represents a significant leap in AI capabilities, moving beyond narrow task-specific applications to a more general scientific problem-solving approach. The AI Scientist’s ability to navigate the entire research process autonomously suggests a level of reasoning and creativity previously thought to be the exclusive domain of human researchers.

The implications of such a system are profound and multifaceted. On one hand, it could dramatically accelerate the pace of scientific discovery by allowing continuous, round-the-clock research without human limitations. This could lead to rapid advancements in fields like drug discovery, materials science, and climate change mitigation.

? Stoked to share The AI-Scientist ?‍? – our end-to-end approach for conducting research with LLMs including ideation, coding, experiment execution, paper write-up & reviewing. Blog ?: https://t.co/kBwAgvXDjZ Paper ?: https://t.co/XvkwWfQhyi Code ?: https://t.co/hXlXjxFAD9 … https://t.co/bPB37b9RUY pic.twitter.com/mHn6ShzaiA — Robert Lange (@RobertTLange) August 13, 2024

Balancing act: Human intuition vs. AI efficiency in the lab

However, the automation of scientific research raises critical questions about the future role of human scientists. While AI may excel at processing vast amounts of data and identifying patterns, human intuition, creativity, and ethical judgment remain crucial in steering scientific inquiry towards meaningful and beneficial outcomes. The challenge will be in finding the right balance between AI-driven efficiency and human-guided purpose in scientific research.

Moreover, the system’s ability to conduct research at such a low cost could have significant economic implications for academic institutions and the broader scientific community. This could potentially lead to a restructuring of how research is funded and conducted, with implications for employment in the scientific sector.

The researchers themselves acknowledge the potential risks associated with such powerful AI systems. They explain in their paper, saying, “The AI Scientist current capabilities, which will only improve, reinforces that the machine learning community needs to immediately prioritize learning how to align such systems to explore in a manner that is safe and consistent with our values.”

Ethical considerations: Navigating the uncharted waters of AI-led science

This admission from the researchers underscores the importance of developing robust ethical frameworks and safeguards alongside technological advancements. As AI systems become more capable of independent scientific inquiry, ensuring they operate in ways that benefit humanity and align with our values becomes increasingly critical.

The open-sourcing of The AI Scientist’s code allows for broader scrutiny and development by the scientific community, which could help address some of these concerns. It also enables researchers to build upon this technology, potentially leading to even more advanced AI-driven scientific discovery systems in the future.

As the scientific community grapples with the implications of this technology, it’s clear that the process of scientific discovery is on the cusp of a profound transformation.

The challenge now lies in harnessing the power of AI-driven research while preserving the irreplaceable elements of human scientific inquiry — creativity, intuition, and ethical consideration — that have driven progress for centuries.

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How to cite ChatGPT

Use discount code STYLEBLOG15 for 15% off APA Style print products with free shipping in the United States.

We, the APA Style team, are not robots. We can all pass a CAPTCHA test , and we know our roles in a Turing test . And, like so many nonrobot human beings this year, we’ve spent a fair amount of time reading, learning, and thinking about issues related to large language models, artificial intelligence (AI), AI-generated text, and specifically ChatGPT . We’ve also been gathering opinions and feedback about the use and citation of ChatGPT. Thank you to everyone who has contributed and shared ideas, opinions, research, and feedback.

In this post, I discuss situations where students and researchers use ChatGPT to create text and to facilitate their research, not to write the full text of their paper or manuscript. We know instructors have differing opinions about how or even whether students should use ChatGPT, and we’ll be continuing to collect feedback about instructor and student questions. As always, defer to instructor guidelines when writing student papers. For more about guidelines and policies about student and author use of ChatGPT, see the last section of this post.

Quoting or reproducing the text created by ChatGPT in your paper

If you’ve used ChatGPT or other AI tools in your research, describe how you used the tool in your Method section or in a comparable section of your paper. For literature reviews or other types of essays or response or reaction papers, you might describe how you used the tool in your introduction. In your text, provide the prompt you used and then any portion of the relevant text that was generated in response.

Unfortunately, the results of a ChatGPT “chat” are not retrievable by other readers, and although nonretrievable data or quotations in APA Style papers are usually cited as personal communications , with ChatGPT-generated text there is no person communicating. Quoting ChatGPT’s text from a chat session is therefore more like sharing an algorithm’s output; thus, credit the author of the algorithm with a reference list entry and the corresponding in-text citation.

When prompted with “Is the left brain right brain divide real or a metaphor?” the ChatGPT-generated text indicated that although the two brain hemispheres are somewhat specialized, “the notation that people can be characterized as ‘left-brained’ or ‘right-brained’ is considered to be an oversimplification and a popular myth” (OpenAI, 2023).

OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat

You may also put the full text of long responses from ChatGPT in an appendix of your paper or in online supplemental materials, so readers have access to the exact text that was generated. It is particularly important to document the exact text created because ChatGPT will generate a unique response in each chat session, even if given the same prompt. If you create appendices or supplemental materials, remember that each should be called out at least once in the body of your APA Style paper.

When given a follow-up prompt of “What is a more accurate representation?” the ChatGPT-generated text indicated that “different brain regions work together to support various cognitive processes” and “the functional specialization of different regions can change in response to experience and environmental factors” (OpenAI, 2023; see Appendix A for the full transcript).

Creating a reference to ChatGPT or other AI models and software

The in-text citations and references above are adapted from the reference template for software in Section 10.10 of the Publication Manual (American Psychological Association, 2020, Chapter 10). Although here we focus on ChatGPT, because these guidelines are based on the software template, they can be adapted to note the use of other large language models (e.g., Bard), algorithms, and similar software.

The reference and in-text citations for ChatGPT are formatted as follows:

• Parenthetical citation: (OpenAI, 2023)
• Narrative citation: OpenAI (2023)

Let’s break that reference down and look at the four elements (author, date, title, and source):

Author: The author of the model is OpenAI.

Date: The date is the year of the version you used. Following the template in Section 10.10, you need to include only the year, not the exact date. The version number provides the specific date information a reader might need.

Title: The name of the model is “ChatGPT,” so that serves as the title and is italicized in your reference, as shown in the template. Although OpenAI labels unique iterations (i.e., ChatGPT-3, ChatGPT-4), they are using “ChatGPT” as the general name of the model, with updates identified with version numbers.

The version number is included after the title in parentheses. The format for the version number in ChatGPT references includes the date because that is how OpenAI is labeling the versions. Different large language models or software might use different version numbering; use the version number in the format the author or publisher provides, which may be a numbering system (e.g., Version 2.0) or other methods.

Bracketed text is used in references for additional descriptions when they are needed to help a reader understand what’s being cited. References for a number of common sources, such as journal articles and books, do not include bracketed descriptions, but things outside of the typical peer-reviewed system often do. In the case of a reference for ChatGPT, provide the descriptor “Large language model” in square brackets. OpenAI describes ChatGPT-4 as a “large multimodal model,” so that description may be provided instead if you are using ChatGPT-4. Later versions and software or models from other companies may need different descriptions, based on how the publishers describe the model. The goal of the bracketed text is to briefly describe the kind of model to your reader.

Source: When the publisher name and the author name are the same, do not repeat the publisher name in the source element of the reference, and move directly to the URL. This is the case for ChatGPT. The URL for ChatGPT is https://chat.openai.com/chat . For other models or products for which you may create a reference, use the URL that links as directly as possible to the source (i.e., the page where you can access the model, not the publisher’s homepage).

Other questions about citing ChatGPT

You may have noticed the confidence with which ChatGPT described the ideas of brain lateralization and how the brain operates, without citing any sources. I asked for a list of sources to support those claims and ChatGPT provided five references—four of which I was able to find online. The fifth does not seem to be a real article; the digital object identifier given for that reference belongs to a different article, and I was not able to find any article with the authors, date, title, and source details that ChatGPT provided. Authors using ChatGPT or similar AI tools for research should consider making this scrutiny of the primary sources a standard process. If the sources are real, accurate, and relevant, it may be better to read those original sources to learn from that research and paraphrase or quote from those articles, as applicable, than to use the model’s interpretation of them.

We’ve also received a number of other questions about ChatGPT. Should students be allowed to use it? What guidelines should instructors create for students using AI? Does using AI-generated text constitute plagiarism? Should authors who use ChatGPT credit ChatGPT or OpenAI in their byline? What are the copyright implications ?

On these questions, researchers, editors, instructors, and others are actively debating and creating parameters and guidelines. Many of you have sent us feedback, and we encourage you to continue to do so in the comments below. We will also study the policies and procedures being established by instructors, publishers, and academic institutions, with a goal of creating guidelines that reflect the many real-world applications of AI-generated text.

For questions about manuscript byline credit, plagiarism, and related ChatGPT and AI topics, the APA Style team is seeking the recommendations of APA Journals editors. APA Style guidelines based on those recommendations will be posted on this blog and on the APA Style site later this year.

Update: APA Journals has published policies on the use of generative AI in scholarly materials .

We, the APA Style team humans, appreciate your patience as we navigate these unique challenges and new ways of thinking about how authors, researchers, and students learn, write, and work with new technologies.

American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). https://doi.org/10.1037/0000165-000

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• 14 August 2024

Has your paper been used to train an AI model? Almost certainly

• Elizabeth Gibney

You can also search for this author in PubMed   Google Scholar

Academic publisher Wiley has sold access to its research papers to firms developing large language models. Credit: Timon Schneider/Alamy

Academic publishers are selling access to research papers to technology firms to train artificial-intelligence (AI) models. Some researchers have reacted with dismay at such deals happening without the consultation of authors. The trend is raising questions about the use of published and sometimes copyrighted work to train the exploding number of AI chatbots in development.

Experts say that, if a research paper hasn’t yet been used to train a large language model (LLM), it probably will be soon. Researchers are exploring technical ways for authors to spot if their content being used.

AI models fed AI-generated data quickly spew nonsense

Last month, it emerged that the UK academic publisher Taylor & Francis, had signed a US$10-million deal with Microsoft, allowing the US technology company to access the publisher’s data to improve its AI systems. And in June, an investor update showed that US publisher Wiley had earned $23 million from allowing an unnamed company to train generative-AI models on its content.

Anything that is available to read online — whether in an open-access repository or not — is “pretty likely” to have been fed into an LLM already, says Lucy Lu Wang, an AI researcher at the University of Washington in Seattle. “And if a paper has already been used as training data in a model, there’s no way to remove that paper after the model has been trained,” she adds.

Massive data sets

LLMs train on huge volumes of data, frequently scraped from the Internet. They derive patterns between the often billions of snippets of language in the training data, known as tokens, that allow them to generate text with uncanny fluency.

Generative-AI models rely on absorbing patterns from these swathes of data to output text, images or computer code. Academic papers are valuable for LLM builders owing to their length and “high information density”, says Stefan Baack, who analyses AI training data sets at the Mozilla Foundation, a global non-profit organization in San Francisco, California that aims to keep the Internet open for all to access.

How does ChatGPT ‘think’? Psychology and neuroscience crack open AI large language models

Training models on a large body of scientific information also give them a much better ability to reason about scientific topics, says Wang, who co-created S2ORC, a data set based on 81.1 million academic papers. The data set was originally developed for text mining — applying analytical techniques to find patterns in data — but has since been used to train LLMs.

The trend of buying high-quality data sets is growing. This year, the Financial Times has offered its content to ChatGPT developer OpenAI in a lucrative deal, as has the online forum Reddit, to Google. And given that scientific publishers probably view the alternative as their work being scraped without an agreement, “I think there will be more of these deals to come,” says Wang.

Information secrets

Some AI developers, such as the Large-scale Artificial Intelligence Network, intentionally keep their data sets open, but many firms developing generative-AI models have kept much of their training data secret, says Baack. “We have no idea what is in there,” he says. Open-source repositories such as arXiv and the scholarly database PubMed of abstracts are thought to be “very popular” sources, he says, although paywalled journal articles probably have their free-to-read abstracts scraped by big technology firms. “They are always on the hunt for that kind of stuff,” he adds.

Proving that an LLM has used any individual paper is difficult, says Yves-Alexandre de Montjoye, a computer scientist at Imperial College London. One way is to prompt the model with an unusual sentence from a text and see whether the output matches the next words in the original. If it does, that is good evidence that the paper is in the training set. But if it doesn’t, that doesn’t mean that the paper wasn’t used — not least because developers can code the LLM to filter responses to ensure they don’t match training data too closely. “It takes a lot for this to work,” he says.

Robo-writers: the rise and risks of language-generating AI

Another method to check whether data are in a training set is known as membership inference attack. This relies on the idea that a model will be more confident about its output when it is seeing something that it has seen before. De Montjoye’s team has developed a version of this, called a copyright trap, for LLMs.

To set the trap, the team generates sentences that look plausible but are nonsense, and hides them in a body of work, for example as white text on a white background or in a field that’s displayed as zero width on a webpage. If an LLM is more ‘surprised’ — a measure known as its perplexity — by an unused control sentence than it is by the one hidden in the text, “that is statistical evidence that the traps were seen before”, he says.

Copyright questions

Even if it were possible to prove that an LLM has been trained on a certain text, it is not clear what happens next. Publishers maintain that, if developers use copyrighted text in training and have not sought a licence, that counts as infringement. But a counter legal argument says that LLMs do not copy anything — they harvest information content from training data, which gets broken up, and use their learning to generate new text.

AI is complicating plagiarism. How should scientists respond?

Litigation might help to resolve this. In an ongoing US copyright case that could be precedent-setting, The New York Times is suing Microsoft and ChatGPT’s developer OpenAI in San Francisco, California. The newspaper accuses the firms of using its journalistic content to train their models without permission.

Many academics are happy to have their work included in LLM training data — especially if the models make them more accurate. “I personally don’t mind if I have a chatbot who writes in the style of me,” says Baack. But he acknowledges that his job is not threatened by LLM outputs in the way that those of other professions, such as artists and writers, are.

Individual scientific authors currently have little power if the publisher of their paper decides to sell access to their copyrighted works. For publicly available articles, there is no established means to apportion credit or know whether a text has been used.

Some researchers, including de Montjoye, are frustrated. “We want LLMs, but we still want something that is fair, and I think we’ve not invented what this looks like yet,” he says.

doi: https://doi.org/10.1038/d41586-024-02599-9

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Weather and climate predicted accurately — without using a supercomputer

News & Views 13 AUG 24

Physics solves a training problem for artificial neural networks

News & Views 07 AUG 24

Estonians gave their DNA to science — now they’re learning their genetic secrets

News 26 JUN 24

Not all ‘open source’ AI models are actually open: here’s a ranking

News 19 JUN 24

A guide to the Nature Index

Nature Index 05 JUN 24

Global Recruitment for Center Directors and Principal Investigators, GIBH

We aim to foster cutting-edge scientific and technological advancements in the field of molecular tissue biology at the single-cell level.

Guangzhou, Guangdong, China

Guangzhou Institutes of Biomedicine and Health(GIBH), Chinese Academy of Sciences

Postdoctoral Fellow in Epigenetics/RNA Biology in the Lab of Yvonne Fondufe-Mittendorf

Van Andel Institute’s (VAI) Professor Yvonne Fondufe-Mittendorf, Ph.D. is hiring a Postdoctoral Fellow to join the lab and carry out an independent...

Grand Rapids, Michigan

Van Andel Institute

Faculty Positions in Center of Bioelectronic Medicine, School of Life Sciences, Westlake University

SLS invites applications for multiple tenure-track/tenured faculty positions at all academic ranks.

Hangzhou, Zhejiang, China

School of Life Sciences, Westlake University

Faculty Positions, Aging and Neurodegeneration, Westlake Laboratory of Life Sciences and Biomedicine

Applicants with expertise in aging and neurodegeneration and related areas are particularly encouraged to apply.

Westlake Laboratory of Life Sciences and Biomedicine (WLLSB)

Faculty Positions in Chemical Biology, Westlake University

We are seeking outstanding scientists to lead vigorous independent research programs focusing on all aspects of chemical biology including...

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