steps to critique research article

How to Write an Article Critique Step-by-Step

Table of contents

• 1 What is an Article Critique Writing?
• 2 How to Critique an Article: The Main Steps
• 3 Article Critique Outline
• 4 Article Critique Formatting
• 5 How to Write a Journal Article Critique
• 6 How to Write a Research Article Critique
• 7 Research Methods in Article Critique Writing
• 8 Tips for writing an Article Critique

Do you know how to critique an article? If not, don’t worry – this guide will walk you through the writing process step-by-step. First, we’ll discuss what a research article critique is and its importance. Then, we’ll outline the key points to consider when critiquing a scientific article. Finally, we’ll provide a step-by-step guide on how to write an article critique including introduction, body and summary. Read more to get the main idea of crafting a critique paper.

What is an Article Critique Writing?

An article critique is a formal analysis and evaluation of a piece of writing. It is often written in response to a particular text but can also be a response to a book, a movie, or any other form of writing. There are many different types of review articles . Before writing an article critique, you should have an idea about each of them.

To start writing a good critique, you must first read the article thoroughly and examine and make sure you understand the article’s purpose. Then, you should outline the article’s key points and discuss how well they are presented. Next, you should offer your comments and opinions on the article, discussing whether you agree or disagree with the author’s points and subject. Finally, concluding your critique with a brief summary of your thoughts on the article would be best. Ensure that the general audience understands your perspective on the piece.

How to Critique an Article: The Main Steps

If you are wondering “what is included in an article critique,” the answer is:

An article critique typically includes the following:

• A brief summary of the article .
• A critical evaluation of the article’s strengths and weaknesses.
• A conclusion.

When critiquing an article, it is essential to critically read the piece and consider the author’s purpose and research strategies that the author chose. Next, provide a brief summary of the text, highlighting the author’s main points and ideas. Critique an article using formal language and relevant literature in the body paragraphs. Finally, describe the thesis statement, main idea, and author’s interpretations in your language using specific examples from the article. It is also vital to discuss the statistical methods used and whether they are appropriate for the research question. Make notes of the points you think need to be discussed, and also do a literature review from where the author ground their research. Offer your perspective on the article and whether it is well-written. Finally, provide background information on the topic if necessary.

When you are reading an article, it is vital to take notes and critique the text to understand it fully and to be able to use the information in it. Here are the main steps for critiquing an article:

• Read the piece thoroughly, taking notes as you go. Ensure you understand the main points and the author’s argument.
• Take a look at the author’s perspective. Is it powerful? Does it back up the author’s point of view?
• Carefully examine the article’s tone. Is it biased? Are you being persuaded by the author in any way?
• Look at the structure. Is it well organized? Does it make sense?
• Consider the writing style. Is it clear? Is it well-written?
• Evaluate the sources the author uses. Are they credible?
• Think about your own opinion. With what do you concur or disagree? Why?

Article Critique Outline

When assigned an article critique, your instructor asks you to read and analyze it and provide feedback. A specific format is typically followed when writing an article critique.

An article critique usually has three sections: an introduction, a body, and a conclusion.

• The introduction of your article critique should have a summary and key points.
• The critique’s main body should thoroughly evaluate the piece, highlighting its strengths and weaknesses, and state your ideas and opinions with supporting evidence.
• The conclusion should restate your research and describe your opinion.

You should provide your analysis rather than simply agreeing or disagreeing with the author. When writing an article review , it is essential to be objective and critical. Describe your perspective on the subject and create an article review summary. Be sure to use proper grammar, spelling, and punctuation, write it in the third person, and cite your sources.

Article Critique Formatting

When writing an article critique, you should follow a few formatting guidelines. The importance of using a proper format is to make your review clear and easy to read.

Make sure to use double spacing throughout your critique. It will make it easy to understand and read for your instructor.

Indent each new paragraph. It will help to separate your critique into different sections visually.

Use headings to organize your critique. Your introduction, body, and conclusion should stand out. It will make it easy for your instructor to follow your thoughts.

Use standard fonts, such as Times New Roman or Arial. It will make your critique easy to read.

Use 12-point font size. It will ensure that your critique is easy to read.

How to Write a Journal Article Critique

When critiquing a journal article, there are a few key points to keep in mind:

• Good critiques should be objective, meaning that the author’s ideas and arguments should be evaluated without personal bias.
• Critiques should be critical, meaning that all aspects of the article should be examined, including the author’s introduction, main ideas, and discussion.
• Critiques should be informative, providing the reader with a clear understanding of the article’s strengths and weaknesses.

When critiquing a research article, evaluating the author’s argument and the evidence they present is important. The author should state their thesis or the main point in the introductory paragraph. You should explain the article’s main ideas and evaluate the evidence critically. In the discussion section, the author should explain the implications of their findings and suggest future research.

It is also essential to keep a critical eye when reading scientific articles. In order to be credible, the scientific article must be based on evidence and previous literature. The author’s argument should be well-supported by data and logical reasoning.

How to Write a Research Article Critique

When you are assigned a research article, the first thing you need to do is read the piece carefully. Make sure you understand the subject matter and the author’s chosen approach. Next, you need to assess the importance of the author’s work. What are the key findings, and how do they contribute to the field of research?

Finally, you need to provide a critical point-by-point analysis of the article. This should include discussing the research questions, the main findings, and the overall impression of the scientific piece. In conclusion, you should state whether the text is good or bad. Read more to get an idea about curating a research article critique. But if you are not confident, you can ask “ write my papers ” and hire a professional to craft a critique paper for you. Explore your options online and get high-quality work quickly.

However, test yourself and use the following tips to write a research article critique that is clear, concise, and properly formatted.

• Take notes while you read the text in its entirety. Right down each point you agree and disagree with.
• Write a thesis statement that concisely and clearly outlines the main points.
• Write a paragraph that introduces the article and provides context for the critique.
• Write a paragraph for each of the following points, summarizing the main points and providing your own analysis:
• The purpose of the study
• The research question or questions
• The methods used
• The outcomes
• The conclusions were drawn by the author(s)
• Mention the strengths and weaknesses of the piece in a separate paragraph.
• Write a conclusion that summarizes your thoughts about the article.
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Research Methods in Article Critique Writing

When writing an article critique, it is important to use research methods to support your arguments. There are a variety of research methods that you can use, and each has its strengths and weaknesses. In this text, we will discuss four of the most common research methods used in article critique writing: quantitative research, qualitative research, systematic reviews, and meta-analysis.

Quantitative research is a research method that uses numbers and statistics to analyze data. This type of research is used to test hypotheses or measure a treatment’s effects. Quantitative research is normally considered more reliable than qualitative research because it considers a large amount of information. But, it might be difficult to find enough data to complete it properly.

Qualitative research is a research method that uses words and interviews to analyze data. This type of research is used to understand people’s thoughts and feelings. Qualitative research is usually more reliable than quantitative research because it is less likely to be biased. Though it is more expensive and tedious.

Systematic reviews are a type of research that uses a set of rules to search for and analyze studies on a particular topic. Some think that systematic reviews are more reliable than other research methods because they use a rigorous process to find and analyze studies. However, they can be pricy and long to carry out.

Meta-analysis is a type of research that combines several studies’ results to understand a treatment’s overall effect better. Meta-analysis is generally considered one of the most reliable type of research because it uses data from several approved studies. Conversely, it involves a long and costly process.

Are you still struggling to understand the critique of an article concept? You can contact an online review writing service to get help from skilled writers. You can get custom, and unique article reviews easily.

Tips for writing an Article Critique

It’s crucial to keep in mind that you’re not just sharing your opinion of the content when you write an article critique. Instead, you are providing a critical analysis, looking at its strengths and weaknesses. In order to write a compelling critique, you should follow these tips: Take note carefully of the essential elements as you read it.

• Make sure that you understand the thesis statement.
• Write down your thoughts, including strengths and weaknesses.
• Use evidence from to support your points.
• Create a clear and concise critique, making sure to avoid giving your opinion.

It is important to be clear and concise when creating an article critique. You should avoid giving your opinion and instead focus on providing a critical analysis. You should also use evidence from the article to support your points.

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How to Write an Article Critique

Tips for Writing a Psychology Critique Paper

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

Cultura RM / Gu Cultura / Getty Images

• Steps for Writing a Critique

Evaluating the Article

• How to Write It
• Helpful Tips

An article critique involves critically analyzing a written work to assess its strengths and flaws. If you need to write an article critique, you will need to describe the article, analyze its contents, interpret its meaning, and make an overall assessment of the importance of the work.

Critique papers require students to conduct a critical analysis of another piece of writing, often a book, journal article, or essay . No matter your major, you will probably be expected to write a critique paper at some point.

For psychology students, critiquing a professional paper is a great way to learn more about psychology articles, writing, and the research process itself. Students will analyze how researchers conduct experiments, interpret results, and discuss the impact of the results.

At a Glance

An article critique involves making a critical assessment of a single work. This is often an article, but it might also be a book or other written source. It summarizes the contents of the article and then evaluates both the strengths and weaknesses of the piece. Knowing how to write an article critique can help you learn how to evaluate sources with a discerning eye.

Steps for Writing an Effective Article Critique

While these tips are designed to help students write a psychology critique paper, many of the same principles apply to writing article critiques in other subject areas.

Your first step should always be a thorough read-through of the material you will be analyzing and critiquing. It needs to be more than just a casual skim read. It should be in-depth with an eye toward key elements.

To write an article critique, you should:

• Read the article , noting your first impressions, questions, thoughts, and observations
• Describe the contents of the article in your own words, focusing on the main themes or ideas
• Interpret the meaning of the article and its overall importance
• Critically evaluate the contents of the article, including any strong points as well as potential weaknesses

The following guidelines can help you assess the article you are reading and make better sense of the material.

Read the Introduction Section of the Article

Start by reading the introduction . Think about how this part of the article sets up the main body and how it helps you get a background on the topic.

• Is the hypothesis clearly stated?
• Is the necessary background information and previous research described in the introduction?

In addition to answering these basic questions, note other information provided in the introduction and any questions you have.

Read the Methods Section of the Article

Is the study procedure clearly outlined in the methods section ? Can you determine which variables the researchers are measuring?

Remember to jot down questions and thoughts that come to mind as you are reading. Once you have finished reading the paper, you can then refer back to your initial questions and see which ones remain unanswered.

Read the Results Section of the Article

Are all tables and graphs clearly labeled in the results section ? Do researchers provide enough statistical information? Did the researchers collect all of the data needed to measure the variables in question?

Make a note of any questions or information that does not seem to make sense. You can refer back to these questions later as you are writing your final critique.

Read the Discussion Section of the Article

Experts suggest that it is helpful to take notes while reading through sections of the paper you are evaluating. Ask yourself key questions:

• How do the researchers interpret the results of the study?
• Did the results support their hypothesis?
• Do the conclusions drawn by the researchers seem reasonable?

The discussion section offers students an excellent opportunity to take a position. If you agree with the researcher's conclusions, explain why. If you feel the researchers are incorrect or off-base, point out problems with the conclusions and suggest alternative explanations.

Another alternative is to point out questions the researchers failed to answer in the discussion section.

Begin Writing Your Own Critique of the Paper

Once you have read the article, compile your notes and develop an outline that you can follow as you write your psychology critique paper. Here's a guide that will walk you through how to structure your critique paper.

Introduction

Begin your paper by describing the journal article and authors you are critiquing. Provide the main hypothesis (or thesis) of the paper. Explain why you think the information is relevant.

Thesis Statement

The final part of your introduction should include your thesis statement. Your thesis statement is the main idea of your critique. Your thesis should briefly sum up the main points of your critique.

Article Summary

Provide a brief summary of the article. Outline the main points, results, and discussion.

When describing the study or paper, experts suggest that you include a summary of the questions being addressed, study participants, interventions, comparisons, outcomes, and study design.

Don't get bogged down by your summary. This section should highlight the main points of the article you are critiquing. Don't feel obligated to summarize each little detail of the main paper. Focus on giving the reader an overall idea of the article's content.

Your Analysis

In this section, you will provide your critique of the article. Describe any problems you had with the author's premise, methods, or conclusions. You might focus your critique on problems with the author's argument, presentation, information, and alternatives that have been overlooked.

When evaluating a study, summarize the main findings—including the strength of evidence for each main outcome—and consider their relevance to key demographic groups.  

Organize your paper carefully. Be careful not to jump around from one argument to the next. Arguing one point at a time ensures that your paper flows well and is easy to read.

Your critique paper should end with an overview of the article's argument, your conclusions, and your reactions.

More Tips When Writing an Article Critique

• As you are editing your paper, utilize a style guide published by the American Psychological Association, such as the official Publication Manual of the American Psychological Association .
• Reading scientific articles can be challenging at first. Remember that this is a skill that takes time to learn but that your skills will become stronger the more that you read.
• Take a rough draft of your paper to your school's writing lab for additional feedback and use your university library's resources.

What This Means For You

Being able to write a solid article critique is a useful academic skill. While it can be challenging, start by breaking down the sections of the paper, noting your initial thoughts and questions. Then structure your own critique so that you present a summary followed by your evaluation. In your critique, include the strengths and the weaknesses of the article.

Archibald D, Martimianakis MA. Writing, reading, and critiquing reviews .  Can Med Educ J . 2021;12(3):1-7. doi:10.36834/cmej.72945

Pautasso M. Ten simple rules for writing a literature review . PLoS Comput Biol . 2013;9(7):e1003149. doi:10.1371/journal.pcbi.1003149

Gülpınar Ö, Güçlü AG. How to write a review article?   Turk J Urol . 2013;39(Suppl 1):44–48. doi:10.5152/tud.2013.054

Erol A. Basics of writing review articles .  Noro Psikiyatr Ars . 2022;59(1):1-2. doi:10.29399/npa.28093

American Psychological Association.  Publication Manual of the American Psychological Association  (7th ed.). Washington DC: The American Psychological Association; 2019.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

How to Critique an Article: Mastering the Article Evaluation Process

Did you know that approximately 4.6 billion pieces of content are produced every day? From news articles and blog posts to scholarly papers and social media updates, the digital landscape is flooded with information at an unprecedented rate. In this age of information overload, honing the skill of articles critique has never been more crucial. Whether you're seeking to bolster your academic prowess, stay well-informed, or improve your writing, mastering the art of article critique is a powerful tool to navigate the vast sea of information and discern the pearls of wisdom.

How to Critique an Article: Short Description

In this article, we will equip you with valuable tips and techniques to become an insightful evaluator of written content. We present a real-life article critique example to guide your learning process and help you develop your unique critique style. Additionally, we explore the key differences between critiquing scientific articles and journals. Whether you're a student, researcher, or avid reader, this guide will empower you to navigate the vast ocean of information with confidence and discernment. Still, have questions? Don't worry! We've got you covered with a helpful FAQ section to address any lingering doubts. Get ready to unleash your analytical prowess and uncover the true potential of every article that comes your way!

What Is an Article Critique: Understanding The Power of Evaluation

An article critique is a valuable skill that involves carefully analyzing and evaluating a written piece, such as a journal article, blog post, or news article. It goes beyond mere summarization and delves into the deeper layers of the content, examining its strengths, weaknesses, and overall effectiveness. Think of it as an engaging conversation with the author, where you provide constructive feedback and insights.

For instance, let's consider a scenario where you're critiquing a research paper on climate change. Instead of simply summarizing the findings, you would scrutinize the methodology, data interpretation, and potential biases, offering thoughtful observations to enrich the discussion. Through the process of writing an article critique, you develop a critical eye, honing your ability to appreciate well-crafted work while also identifying areas for improvement.

In the following sections, our ' write my paper ' experts will uncover valuable tips on and key points on how to write a stellar critique, so let's explore more!

Unveiling the Key Aims of Writing an Article Critique

Writing an article critique serves several essential purposes that go beyond a simple review or summary. When engaging in the art of critique, as when you learn how to write a review article , you embark on a journey of in-depth analysis, sharpening your critical thinking skills and contributing to the academic and intellectual discourse. Primarily, an article critique allows you to:

• Evaluate the Content : By critiquing an article, you delve into its content, structure, and arguments, assessing its credibility and relevance.
• Strengthen Your Critical Thinking : This practice hones your ability to identify strengths and weaknesses in written works, fostering a deeper understanding of complex topics and critical evaluation skills.
• Engage in Scholarly Dialogue : Your critique contributes to the ongoing academic conversation, offering valuable insights and thoughtful observations to the existing body of knowledge.
• Enhance Writing Skills : By analyzing and providing feedback, you develop a keen eye for effective writing techniques, benefiting your own writing endeavors.
• Promote Continuous Learning : Through the writing process, you continually refine your analytical abilities, becoming an avid and astute learner in the pursuit of knowledge.

How to Critique an Article: Steps to Follow

The process of crafting an article critique may seem overwhelming, especially when dealing with intricate academic writing. However, fear not, for it is more straightforward than it appears! To excel in this art, all you require is a clear starting point and the skill to align your critique with the complexities of the content. To help you on your journey, follow these 3 simple steps and unlock the potential to provide insightful evaluations:

Step 1: Read the Article

The first and most crucial step when wondering how to do an article critique is to thoroughly read and absorb its content. As you delve into the written piece, consider these valuable tips from our custom essay writer to make your reading process more effective:

• Take Notes : Keep a notebook or digital document handy while reading. Jot down key points, noteworthy arguments, and any questions or observations that arise.
• Annotate the Text : Underline or highlight significant passages, quotes, or sections that stand out to you. Use different colors to differentiate between positive aspects and areas that may need improvement.
• Consider the Author's Purpose : Reflect on the author's main critical point and the intended audience. Much like an explanatory essay , evaluate how effectively the article conveys its message to the target readership.

Now, let's say you are writing an article critique on climate change. While reading, you come across a compelling quote from a renowned environmental scientist highlighting the urgency of addressing global warming. By taking notes and underlining this impactful quote, you can later incorporate it into your critique as evidence of the article's effectiveness in conveying the severity of the issue.

Step 2: Take Notes/ Make sketches

Once you've thoroughly read the article, it's time to capture your thoughts and observations by taking comprehensive notes or creating sketches. This step plays a crucial role in organizing your critique and ensuring you don't miss any critical points. Here's how to make the most out of this process:

• Highlight Key Arguments : Identify the main arguments presented by the author and highlight them in your notes. This will help you focus on the core ideas that shape the article.
• Record Supporting Evidence : Take note of any evidence, examples, or data the author uses to support their arguments. Assess the credibility and effectiveness of this evidence in bolstering their claims.
• Examine Structure and Flow : Pay attention to the article's structure and how each section flows into the next. Analyze how well the author transitions between ideas and whether the organization enhances or hinders the reader's understanding.
• Create Visual Aids : If you're a visual learner, consider using sketches or diagrams to map out the article's key points and their relationships. Visual representations can aid in better grasping the content's structure and complexities.

Step 3: Format Your Paper

Once you've gathered your notes and insights, it's time to give structure to your article critique. Proper formatting ensures your critique is organized, coherent, and easy to follow. Here are essential tips for formatting an article critique effectively:

• Introduction : Begin with a clear and engaging introduction that provides context for the article you are critiquing. Include the article's title, author's name, publication details, and a brief overview of the main theme or thesis.
• Thesis Statement : Present a strong and concise thesis statement that conveys your overall assessment of the article. Your thesis should reflect whether you found the article compelling, convincing, or in need of improvement.
• Body Paragraphs : Organize your critique into well-structured body paragraphs. Each paragraph should address a specific point or aspect of the article, supported by evidence and examples from your notes.
• Use Evidence : Back up your critique with evidence from the article itself. Quote relevant passages, cite examples, and reference data to strengthen your analysis and demonstrate your understanding of the article's content.
• Conclusion : Conclude your critique by summarizing your main points and reiterating your overall evaluation. Avoid introducing new arguments in the conclusion and instead provide a concise and compelling closing statement.
• Citation Style : If required, adhere to the specific citation style guidelines (e.g., APA, MLA) for in-text citations and the reference list. Properly crediting the original article and any additional sources you use in your critique is essential.

How to Critique a Journal Article: Mastering the Steps

So, you've been assigned the task of critiquing a journal article, and not sure where to start? Worry not, as we've prepared a comprehensive guide with different steps to help you navigate this process with confidence. Journal articles are esteemed sources of scholarly knowledge, and effectively critiquing them requires a systematic approach. Let's dive into the steps to expertly evaluate and analyze a journal article:

Step 1: Understanding the Research Context

Begin by familiarizing yourself with the broader research context in which the journal article is situated. Learn about the field, the topic's significance, and any previous relevant research. This foundational knowledge will provide a valuable backdrop for your journal article critique example.

Step 2: Evaluating the Article's Structure

Assess the article's overall structure and organization. Examine how the introduction sets the stage for the research and how the discussion flows logically from the methodology and results. A well-structured article enhances readability and comprehension.

Step 3: Analyzing the Research Methodology

Dive into the research methodology section, which outlines the approach used to gather and analyze data. Scrutinize the study's design, data collection methods, sample size, and any potential biases or limitations. Understanding the research process will enable you to gauge the article's reliability.

Step 4: Assessing the Data and Results

Examine the presentation of data and results in the article. Are the findings clear and effectively communicated? Look for any discrepancies between the data presented and the interpretations made by the authors.

Step 5: Analyzing the Discussion and Conclusions

Evaluate the discussion section, where the authors interpret their findings and place them in the broader context. Assess the soundness of their conclusions, considering whether they are adequately supported by the data.

Step 6: Considering Ethical Considerations

Reflect on any ethical considerations raised by the research. Assess whether the study respects the rights and privacy of participants and adheres to ethical guidelines.

Step 7: Identifying Strengths and Weaknesses

Identify the article's strengths, such as well-designed experiments, comprehensive, relevant literature reviews, or innovative approaches. Also, pinpoint any weaknesses, like gaps in the research, unclear explanations, or insufficient evidence.

Step 8: Offering Constructive Feedback

Provide constructive feedback to the authors, highlighting both positive aspects and areas for improvement for future research. Suggest ways to enhance the research methods, data analysis, or discussion to bolster its overall quality.

Step 9: Presenting Your Critique

Organize your critique into a well-structured paper, starting with an introduction that outlines the article's context and purpose. Develop a clear and focused thesis statement that conveys your assessment. Support your points with evidence from the article and other credible sources.

By following these steps on how to critique a journal article, you'll be well-equipped to craft a thoughtful and insightful piece, contributing to the scholarly discourse in your field of study!

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An Article Critique: Journal Vs. Research

In the realm of academic writing, the terms 'journal article' and 'research paper' are often used interchangeably, which can lead to confusion about their differences. Understanding the distinctions between critiquing a research article and a journal piece is essential. Let's delve into the key characteristics that set apart a journal article from a research paper and explore how the critique process may differ for each:

Publication Scope:

• Journal Article: Presents focused and concise research findings or new insights within a specific subject area.
• Research Paper: Explores a broader range of topics and can cover extensive research on a particular subject.

Format and Structure:

• Journal Article: Follows a standardized format with sections such as abstract, introduction, methodology, results, discussion, and conclusion.
• Research Paper: May not adhere to a specific format and allows flexibility in organizing content based on the research scope.

Depth of Analysis:

• Journal Article: Provides a more concise and targeted analysis of the research topic or findings.
• Research Paper: Offers a more comprehensive and in-depth analysis, often including extensive literature reviews and data analyses.
• Journal Article: Typically shorter in length, ranging from a few pages to around 10-15 pages.
• Research Paper: Tends to be longer, spanning from 20 to several hundred pages, depending on the research complexity.

Publication Type:

• Journal Article: Published in academic journals after undergoing rigorous peer review.
• Research Paper: May be published as a standalone work or as part of a thesis, dissertation, or academic report.
• Journal Article: Targeted at academics, researchers, and professionals within the specific field of study.
• Research Paper: Can cater to a broader audience, including students, researchers, policymakers, and the general public.
• Journal Article: Primarily aimed at sharing new research findings, contributing to academic discourse, and advancing knowledge in the field.
• Research Paper: Focuses on comprehensive exploration and analysis of a research topic, aiming to make a substantial contribution to the body of knowledge.

Appreciating these differences becomes paramount when engaging in the critique of these two forms of scholarly publications, as they each demand a unique approach and thoughtful consideration of their distinctive attributes. And if you find yourself desiring a flawlessly crafted research article critique example, entrusting the task to professional writers is always an excellent option – you can easily order essay that meets your needs.

Article Critique Example

Our collection of essay samples offers a comprehensive and practical illustration of the critique process, granting you access to valuable insights.

Tips on How to Critique an Article

Critiquing an article requires a keen eye, critical thinking, and a thoughtful approach to evaluating its content. To enhance your article critique skills and provide insightful analyses, consider incorporating these five original and practical tips into your process:

1. Analyze the Author's Bias : Be mindful of potential biases in the article, whether they are political, cultural, or personal. Consider how these biases may influence the author's perspective and the presentation of information. Evaluating the presence of bias enables you to discern the objectivity and credibility of the article's arguments.

2. Examine the Supporting Evidence : Scrutinize the quality and relevance of the evidence used to support the article's claims. Look for well-researched data, credible sources, and up-to-date statistics. Assess how effectively the author integrates evidence to build a compelling case for their arguments.

3. Consider the Audience's Perspective : Put yourself in the shoes of the intended audience and assess how well the article communicates its ideas. Consider whether the language, tone, and level of complexity are appropriate for the target readership. A well-tailored article is more likely to engage and resonate with its audience.

4. Investigate the Research Methodology : If the article involves research or empirical data, delve into the methodology used to gather and analyze the information. Evaluate the soundness of the study design, sample size, and data collection methods. Understanding the research process adds depth to your critique.

5. Discuss the Implications and Application : Consider the broader implications of the article's findings or arguments. Discuss how the insights presented in the article could impact the field of study or have practical applications in real-world scenarios. Identifying the potential consequences of the article's content strengthens your critique's depth and relevance.

Wrapping Up

In a nutshell, article critique is an essential skill that helps us grow as critical thinkers and active participants in academia. Embrace the opportunity to analyze and offer constructive feedback, contributing to a brighter future of knowledge and understanding. Remember, each critique is a chance to engage with new ideas and expand our horizons. So, keep honing your critique skills and enjoy the journey of discovery in the world of academic exploration!

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Guidelines:

• Critiquing Research Articles (Flinders University)
• Framework for How to Read and Critique a Research Study (American Nurses Association)
• How to Critique a Journal Article (UIS)
• How to Critique a Research Paper (University of Michigan)
• How to Write an Article Critique
• Research Article Critique Form
• Writing a Critique or Review of a Research Article (University of Calgary)

Presentations:

• The Critique Process: Reviewing and Critiquing Research
• Writing a Critique
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• Last Updated: Apr 30, 2024 12:52 PM
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How To Write an Article Critique: 4 Steps To Follow

If you need to know how to write an article critique, keep reading for our step-by-step guide.

In an article critique, you will be asked to critically read a research article, reflect on the article, and identify the strong and weak points of that piece. Whether you have been asked to critique a research paper, an essay, or an entire book, it would be best if you reflected on the argument’s effectiveness and validity. The key point to writing a solid article critique is to think critically.

Every author or researcher tries to convince you of the correctness of their point of view. However, even if that point of view is flawed, the author is trying to make it look good. Therefore, your job is to critique the paper critically, identifying its strong and weak points. There are several steps involved in the process.

Materials Needed

Step 1: read the piece, step 2: gather evidence to support your article critique, step 3: format your paper, step 4. proofread your article critique, what is the format of an article critique, what is the difference between a critique and a review, what are the components of a critique .

To write an article critique, there are several materials you need to have. They include:

• The paper, book, or article you are going to be critiquing
• A computer or a notepad you can use to take notes
• Writing materials, such as pens and pencils
• Highlighters and tabs you can use to keep the information organized

If you want to write a decisive critique, you need to read the piece first. On the other hand, you don’t want to try to read a summary and grasp everything from the article. Otherwise, you risk losing a significant amount of context from the article.

As you read the article or book, there are several questions you need to answer. They include:

• If the author is considered an expert or authority in the field, why is that the case?
• What is the thesis statement or hypothesis the author is presenting? Does the author have enough evidence to support their point of view?
• Who is the target audience of the article? For example, is the target audience people with a specific viewpoint, people of a particular background, or people with a predetermined point of view?
• Are the arguments presented in the article valid? Does it seem like the sources have been cherry-picked? Or does the author appear to consider all possible answers to the question?
• Does the author appear to have any flaws in the argument? Is the author overlooking something important?
• Does the author appear to reach a logical conclusion based on the evidence in the paper?

As you read through the article, you should take notes and answer the questions above. This will give you plenty of information you can use to craft your article critique. 

You need to note the author’s sources as you read the paper. These could include footnotes, endnotes, quotes, and other sources referenced in the paper. You may want to review the sources to ensure the author has drawn an appropriate conclusion based on the information in the source. You may also want to do your research to identify other sources that either support the author’s point of view or refute it.

You should also go to the article to see if there are any biased opinions. It is not unusual for someone to pick a side and not even consider the opposing point of view. If you believe you can draw a different logical conclusion based on the same evidence, you should include that in your article critique.

Remember that the language of the article will also play a vital role. You should pay close attention to word choice, particularly if the language is politically charged. Readers can interpret words differently, and you will need to explain the interpretation of the language in the article.

You may also want to identify any logical fallacies in the article. Some of the most common fallacies people use in their writing include:

• Ad Hominem: This fallacy occurs when someone attacks the individual instead of the substance of their point of view. Discrediting the person does not necessarily discredit the argument.
• Correlation and Causation: Correlation does not always equal causation. Just because something came first doesn’t mean it caused the second action. 
• Slippery Slope: Many people will make the “slippery slope” argument. Just because one action takes place doesn’t mean it will end up in the worst-case scenario. 

If you notice these logical fallacies, you should use them in your article critique. You might also be interested in learning how to write a case study .

You may be asked to follow APA format in your article critique. In general, there will be four separate parts to your article. They include:

• The Introduction: In the introduction, you need to include the author’s name and the title of the piece you are critiquing. You should also mention the core idea or point of view that the author has. It would be best if you also had a clear thesis reflecting your article critique’s direction.
• The Summary: In the summary, you need to include the main points of the article. If there are central arguments in the article, you should present them. Then, be sure to include the article’s main conclusion as well.
• The Critique: In your critique, you need to include both the strong and weak points of the article. Mention what the article does well, and mention what the article does poorly. You should discuss the evidence in the article and any other evidence you might have gathered.
• The Conclusion: Again, you should summarize the article’s key points. Conclude the validity of the piece you have analyzed. You may want to include some future directions that merit further research. 

Once you have finished your article critique, be sure to proofread it before you submit it.

Once you have finished your article critique, be sure to proofread it before you submit it. Check for spelling, grammar, and syntax errors when proofreading your article.

Frequently Asked Questions

In academic writing, the format of an article critique includes an introduction, a brief summary, the critique itself, and the conclusion. In your critique, you should include everything from the title of the article and the author’s ideas to the research methods and research questions (or journalistic questions), depending on whether you are critiquing a research paper or a journal article.

Generally, a good critique is written by someone considered an expert in that field. In contrast, a review is written by someone interested in that field but is not necessarily considered an expert.

The components of a critique paper include the background information and author’s main point (in the introduction), a summary in the body paragraphs, a critical evaluation in the critique section, and future research or following questions in conclusion.

If you are interested in learning more, check out our essay writing tips !

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• Research Guides

How to Critique an Article (Psychology)

Introduction.

• The introduction is a justification for why the study was conducted.
• By the end of the introduction you should have a very good idea of what the researchers are going to study, and be convinced that the study is absolutely necessary to advance the field.
• The justification should be a combination of improving on previous research and good theoretical reasons and practical reasons for why the study is important.
• If the authors are talking about a controversial issue, are they presenting both sides in a reasonable way? Is their choice of one side over the other based on hard evidence?
• Do you understand what their hypotheses are e.g. what they expect to find?
• It is not good enough just to say that the study has not been done before. There are plenty of topics that have not been scientifically researched before but that doesn't mean that they should be. For example, I doubt that anyone has ever looked at the correlation between favorite color of Skittles and personality, but that doesn't mean that it should be researched unless there is a good theoretical reason for why we would expect a relationship and a good reason to think that knowing the relationship would advance our understanding of personality in some meaningful way.

• Last Updated: Nov 5, 2021 9:46 AM
• Subjects: Psychology

Step-by-step guide to critiquing research. Part 2: Qualitative research

Affiliation.

• 1 School of Nursing and Midwifery, University of Dublin, Trinity College, Dublin, Ireland, UK.
• PMID: 17851363
• DOI: 10.12968/bjon.2007.16.12.23726

As with a quantitative study, critical analysis of a qualitative study involves an in-depth review of how each step of the research was undertaken. Qualitative and quantitative studies are, however, fundamentally different approaches to research and therefore need to be considered differently with regard to critiquing. The different philosophical underpinnings of the various qualitative research methods generate discrete ways of reasoning and distinct terminology; however, there are also many similarities within these methods. Because of this and its subjective nature, qualitative research it is often regarded as more difficult to critique. Nevertheless, an evidenced-based profession such as nursing cannot accept research at face value, and nurses need to be able to determine the strengths and limitations of qualitative as well as quantitative research studies when reviewing the available literature on a topic.

Publication types

• Anthropology, Cultural
• Data Collection / ethics
• Data Collection / methods
• Data Interpretation, Statistical
• Evidence-Based Medicine
• Guidelines as Topic
• Interviews as Topic
• Nursing Methodology Research / ethics
• Nursing Methodology Research / organization & administration*
• Nursing Theory
• Philosophy, Nursing
• Qualitative Research*
• Reproducibility of Results
• Research Design*

Writing a Critique Paper: Seven Easy Steps

Were you assigned or asked by your professor to write a critique paper? It’s easy to write one. Just follow the following four steps in writing a critique paper and three steps in presenting it, then you’re ready to go.

One of the students’ requirements I specified in the course module is a critique paper. Just so everyone benefits from the guide I prepared for that class, I share it here.

To standardize the format they use in writing a critique paper, I came up with the following steps to make their submissions worthwhile.

Since they are graduate students, more is expected of them. Hence, most of the verbs I use in writing the lesson’s objectives reside in the domain of higher thinking skills or HOTS. Developing the students’ critical thinking skills will help them analyze future problems and propose solutions that embody environmental principles thus resonate desirable outcomes aligned with the goal of sustainable development.

Table of Contents

Step-by-step procedure in writing a critique paper.

I quickly wrote this simple guide on writing a critique paper to help you evaluate any composition you want to write about. It could be a book, a scientific article, a gray paper, or whatever your professor assigns. I integrated the essence of the approach in this article.

The critique paper essentially comprises two major parts, namely the:

1) Procedure in Writing a Critique Paper, and the

2) Format of the Critique Paper.

First, you will need to know the procedure that will guide you in evaluating a paper. Second, the format of the critique paper refers to how you present it so that it becomes logical and scholarly in tone.

The Four Steps in Writing a Critique Paper

Here are the four steps in writing a critique paper:

To write a good critique paper, it pays to adhere to a smooth flow of thought in your evaluation of the piece. You will need to introduce the topic, analyze, interpret, then conclude it.

Introduce the Discussion Topic

Introduce the topic of the critique paper. To capture the author’s idea, you may apply the  5Ws and 1H approach  in writing your technical report.

That means, when you write your critique paper, you should be able to answer the Why , When , Where , What , Who , and How questions. Using this approach prevents missing out on the essential details. If you can write a critique paper that adheres to this approach, that would be excellent.

Here’s a simplified example to illustrate the technique:

The news article by John Doe was a narrative about a bank robbery. Accordingly, a masked man  (Who)  robbed a bank  (What)  the other day  (When)  next to a police station  (Where) . He did so in broad daylight  (How) . He used a bicycle to escape from the scene of the crime  (How) . In his haste, he bumped into a post. His mask fell off; thus, everyone saw his face, allowing witnesses to describe him. As a result, he had difficulty escaping the police, who eventually retrieved his loot and put him in jail because of his wrongdoing  (Why) .

Hence, you give details about the topic, in this case, a bank robbery. Briefly describe what you want to tell your audience. State the overall purpose of writing the piece and its intention.

Is the essay written to inform, entertain, educate, raise an issue for debate, and so on? Don’t parrot or repeat what the writer wrote in his paper. And write a paragraph or a few sentences as succinctly as you can.

Analyze means to break down the abstract ideas presented into manageable bits.

What are the main points of the composition? How was it structured? Did the view expressed by the author allow you, as the reader, to understand?

In the example given above, it’s easy to analyze the event as revealed by the chain of events. How do you examine the situation?

The following steps are helpful in the analysis of information:

• Ask yourself what your objective is in writing the critique paper. Come up with a guidepost in examining it. Are you looking at it with some goal or purpose in mind? Say you want to find out how thieves carry out bank robberies. Perhaps you can categorize those robberies as either planned or unplanned.
• Find out the source, or  basis, of the information that you need. Will you use the paper as your source of data, or do you have corroborating evidence?
• Remove  unnecessary information  from your data source. Your decision to do so depends on your objective. If there is irrelevant data, remove it from your critique.

We can use an analogy here to clearly explain the analysis portion.

If you want to split a log, what would you do? Do you use an ax, a chainsaw, or perhaps a knife? The last one is out of the question. It’s inappropriate.

Thus, it would be best if you defined the tools of your analysis. Tools facilitate understanding and allow you to make an incisive analysis.

Read More : 5 Tools in Writing the Analysis Section of the Critique Paper

Now, you are ready to interpret the article, book, or any composition once the requisites of analysis are in place.

Visualize the event in your mind and interpret the behavior of actors in the bank robbery incident. You have several actors in that bank heist: the robber, the police, and the witnesses of the crime.

While reading the story, it might have occurred to you that the robber is inexperienced. We can see some discrepancies in his actions.

Imagine, his mode of escape is a bicycle. What got into him? Maybe he did not plan the robbery at all. Besides, there was no mention that the robber used a gun in the heist.

That fact confirms the first observation that he was not ready at all. Escaping the scene of the crime using a bicycle with nothing to defend himself once pursued? He’s insane. Unimaginable. He’s better off sleeping at home and waiting for food to land on his lap if food will come at all.

If we examine the police’s response, they were relatively quick. Right after the robber escaped the crime scene, they appeared to remedy the situation. The robber did not put up a fight.

What? With bare knuckles? It makes little sense.

If we look at the witnesses’ behavior, we can discern that perhaps they willingly informed the police of the bank robber’s details. They were not afraid. And that’s because the robber appears to be unarmed. But there was no specific mention of it.

Narrate the importance of each of the different sections or paragraphs. How does the write-up contribute to the overall picture of the issue or problem being studied?

Assess or Evaluate

Finally, judge whether the article was a worthwhile account after all. Did it meet expectations? Was it able to convey the information most efficiently? Or are there loopholes or flaws that should have been mentioned?

Format of Presenting the Critique Paper

The logical format in writing a critique paper comprises at least three sections: the introduction, the body, and the conclusion. This approach is systematic and achieves a good flow that readers can follow.

Introduction

Include the title and name of the author in your introduction. Make a general description of the topic being discussed, including the author’s assumptions, inferences, or contentions. Find out the thesis or central argument , which will be the basis of your discussion.

The robbery example appears to be inappropriate to demonstrate this section, as it is so simple. So we level up to a scientific article.

In any scientific article, there is always a thesis that guides the write-up. A thesis is a statement that expresses what the author believes in and tries to test in his study. The investigation or research converges (ideally) to this central theme as the author’s argument.

You can find the thesis in the paper’s hypothesis section. That’s because a hypothesis is a tentative thesis. Hypo means “below or under,” meaning it is the author’s tentative explanation of whatever phenomenon he tackles.

If you need more information about this, please refer to my previous post titled “ How to Write a Thesis .”

How is the introduction of a critique paper structured? It follows the general guidelines of writing from a broad perspective to more specific concerns or details. See how it’s written here:  Writing a Thesis Introduction: from General to Specific .

You may include the process you adopted in writing the critique paper in this section.

The body of the paper includes details about the article being examined. It is here where you place all those musings of yours after applying the  analytical tools .

This section is similar to the results and discussion portion of a scientific paper. It describes the outcome of your analysis and interpretation.

In explaining or expressing your argument, substantiate it by citing references to make it believable. Make sure that those references are relevant as well as timely. Don’t cite references that are so far out in the past. These, perhaps, would not amount to a better understanding of the topic at hand. Find one that will help you understand the situation.

Besides, who wants to adopt the perspective of an author who has not even got hold of a mobile phone if your paper is about  using mobile phones to facilitate learning during the pandemic caused by COVID-19 ? Find a more recent one that will help you understand the situation.

Objectively examine the major points presented by the author by giving details about the work. How does the author present or express the idea or concept? Is he (or she) convincing the way he/she presents his/her paper’s thesis?

Well, I don’t want to be gender-biased, but I find the “he/she” term somewhat queer. I’ll get back to the “he” again, to represent both sexes.

I mention the gender issue because the literature says that there is a difference in how a person sees things based on gender. For example, Ragins & Sundstrom (1989) observed that it would be more difficult for women to obtain power in the organization than men. And there’s a paper on gender and emotions by Shields et al. (2006) , although I wouldn’t know the outcome of that study as it is behind a paywall. My point is just that there is a difference in perspective between men and women. Alright.

Therefore, always find evidence to support your position. Explain why you agree or disagree with the author. Point out the discrepancies or strengths of the paper.

Well, everything has an end. Write a critique paper that incorporates the  key takeaways  of the document examined. End the critique with an overall interpretation of the article, whatever that is.

Why do you think is the paper relevant in the course’s context that you are taking? How does it contribute to say, the study of human behavior (in reference to the bank robbery)? Are there areas that need to be considered by future researchers, investigators, or scientists? That will be the knowledge gap that the next generation of researchers will have to look into.

If you have read up to this point, then thank you for reading my musings. I hope that helped you clarify the steps in writing a critique paper. A well-written critique paper depends on your writing style.

Read More : How to Write an Article with AI: A Guide to Using AI for Article Creation and Refinement

Notice that my writing style changes based on the topic that I discuss. Hence, if your professor assigns you a serious, rigorous, incisive, and detailed analysis of a scientific article, then that is the way to go. Adopt a formal mode in your writing.

Final Tip : Find a paper that is easy for you to understand. In that way, you can clearly express your thoughts. Write a critique paper that rocks!

Related Reading

Master Content Analysis: An All-in-One Guide

Ragins, B. R., & Sundstrom, E. (1989). Gender and power in organizations: A longitudinal perspective. Psychological bulletin , 105 (1), 51.

Shields, S. A., Garner, D. N., Di Leone, B., & Hadley, A. M. (2006). Gender and emotion. In Handbook of the sociology of emotions (pp. 63-83). Springer, Boston, MA.

© 2020 November 20 P. A. Regoniel

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About the author, patrick regoniel.

Dr. Regoniel, a faculty member of the graduate school, served as consultant to various environmental research and development projects covering issues and concerns on climate change, coral reef resources and management, economic valuation of environmental and natural resources, mining, and waste management and pollution. He has extensive experience on applied statistics, systems modelling and analysis, an avid practitioner of LaTeX, and a multidisciplinary web developer. He leverages pioneering AI-powered content creation tools to produce unique and comprehensive articles in this website.

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A Step-by-Step Guide on the Research Process for PhD Students

Are you about to commence a PhD? It’s quite an exciting time, with so much anticipation and nerves. You can’t be more of an expert on a topic than having a Doctorate on a particular subject, so you need to be passionate about your subject area to undertake this strenuous, demanding qualification. Some might be unsure about choosing an edD or PhD , but both are valuable qualifications. However, in this informative article, we’re going to focus on the PhD, and particularly the research process for students studying this intense qualification.

Researching for a doctoral thesis is hard work, and without the proper methods, you could find yourself floundering. Lucky for you, this helpful article will cover a step-by-step guide to the research process, so if you need to step up your research game for your postgraduate qualification, you can. Continue reading to learn more.

Consider Your Goal

The first thing to think about is your goal for undertaking a PhD or what you hope to achieve. Are you doing it to become an expert in a niche field, thereby increasing your employability? Or are you just deadly passionate about the topic and want to explore in-depth learning about your field? Before figuring out your research approach, it helps to define the reasons you’re embarking on this full-on journey of learning.

Pick a Research Methodology, and be Careful Here

The first step in conducting effective and efficient research for a PhD is to select the correct research methodology. There are various research methodologies, including quantitative, qualitative, and mixed methods research . Each approach has its strengths and drawbacks, and you should choose the one that best matches your research question and objectives. For instance, research about people’s experiences in a specific job is bound to be qualitative, but the long-term effects of a biological phenomenon should essentially be quantitative.

Develop and Write Up a Research Plan

Once you have picked your research methodology as described above, the next step is to develop and write up your research plan. A research plan will detail each step of your research in order to help you make sense of it and plot it out. It should include the main research question you’re asking, the research objectives, research design ideas, data collection methods, data analysis methods, interview schedules for qualitative research, and ethical considerations.

Perform a Literature Review

Before you start conducting interviews or collecting data for your PhD research, consider conducting a literature review . You’ll have full access to your tertiary institution’s libraries, including online journal articles, where existing research on your topic should exist.

A literature review will assist you in learning about the current existing knowledge and research dearth in your field of study. It will also help you create a theoretical framework for your research topic and will provide you with rich ideas for your thesis and data collection methods.

Data Collection Methods and Approaches

One essential part of PhD research is data collection for either qualitative or quantitative research. Qualitative data is people’s experiences, stories, and anecdotes – their thoughts, feelings, and impressions. At the same time, quantitative data is pure numbers and percentages. You should collect the data that is pertinent to your research question and objectives, as developed in your research plan that you’ve already prepared.

There are various data collection methods, all with benefits and drawbacks. These include interviews, surveys, experiments, and observations. You can select the data collection method that best matches your research question and objectives as outlined in your plan.

Choose a Supervisor

All PhD students need a supervisor, usually an academic Professor with expertise in their chosen research area. Some students even have a key supervisor with a few additional supervisors. Some may have up to four. You need to approach each one who will review your research plan and methodology and provide guidance throughout the process. It’s important to note that as professional academics, their time and attention are limited, so be sure to work closely with them to fit their busy schedules.

Manage Budgets

Some research projects for a PhD will require a budget, for instance, to book lab time or to reimburse research interview participants with gift cards or cash. You may need to design and manage the research budget for your project and request financial assistance through a grant application, which must be written to precise guidelines to ensure a chance of securing some funding.

Write Often and Early

A mistake some PhD students make is waiting until they’ve collected and analyzed all their data before they start writing their thesis . You should instead begin jotting down ideas and thoughts from the beginning of the process. By getting into the habit of writing early and often, you’ll make the mammoth task of writing your thesis easier as you’ll be in the practice and flow of writing. For instance, writing the literature review and research plan is a good starting point, but you should take extensive notes and jot down hypotheses and questions that arise throughout the whole research process.

A PhD Research Summary

This helpful and informative article has covered a step-by-step guide on the research process for PhD students. If you’re preparing to undergo this rigorous and intense period of study, knowing how to research effectively is critical to your success. So follow this guide and use it to your advantage.

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Article Contents

Ai: a global governance challenge, empirical perspectives, normative perspectives, acknowledgement, conflict of interest.

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The Global Governance of Artificial Intelligence: Next Steps for Empirical and Normative Research

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Jonas Tallberg, Eva Erman, Markus Furendal, Johannes Geith, Mark Klamberg, Magnus Lundgren, The Global Governance of Artificial Intelligence: Next Steps for Empirical and Normative Research, International Studies Review , Volume 25, Issue 3, September 2023, viad040, https://doi.org/10.1093/isr/viad040

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Artificial intelligence (AI) represents a technological upheaval with the potential to change human society. Because of its transformative potential, AI is increasingly becoming subject to regulatory initiatives at the global level. Yet, so far, scholarship in political science and international relations has focused more on AI applications than on the emerging architecture of global AI regulation. The purpose of this article is to outline an agenda for research into the global governance of AI. The article distinguishes between two broad perspectives: an empirical approach, aimed at mapping and explaining global AI governance; and a normative approach, aimed at developing and applying standards for appropriate global AI governance. The two approaches offer questions, concepts, and theories that are helpful in gaining an understanding of the emerging global governance of AI. Conversely, exploring AI as a regulatory issue offers a critical opportunity to refine existing general approaches to the study of global governance.

La inteligencia artificial (IA) representa una revolución tecnológica que tiene el potencial de poder cambiar la sociedad humana. Debido a este potencial transformador, la IA está cada vez más sujeta a iniciativas reguladoras a nivel global. Sin embargo, hasta ahora, el mundo académico en el área de las ciencias políticas y las relaciones internacionales se ha centrado más en las aplicaciones de la IA que en la arquitectura emergente de la regulación global en materia de IA. El propósito de este artículo es esbozar una agenda para la investigación sobre la gobernanza global en materia de IA. El artículo distingue entre dos amplias perspectivas: por un lado, un enfoque empírico, destinado a mapear y explicar la gobernanza global en materia de IA y, por otro lado, un enfoque normativo, destinado a desarrollar y a aplicar normas para una gobernanza global adecuada de la IA. Los dos enfoques ofrecen preguntas, conceptos y teorías que resultan útiles para comprender la gobernanza global emergente en materia de IA. Por el contrario, el hecho de estudiar la IA como si fuese una cuestión reguladora nos ofrece una oportunidad de gran relevancia para poder perfeccionar los enfoques generales existentes en el estudio de la gobernanza global.

L'intelligence artificielle (IA) constitue un bouleversement technologique qui pourrait bien changer la société humaine. À cause de son potentiel transformateur, l'IA fait de plus en plus l'objet d'initiatives réglementaires au niveau mondial. Pourtant, jusqu'ici, les chercheurs en sciences politiques et relations internationales se sont davantage concentrés sur les applications de l'IA que sur l’émergence de l'architecture de la réglementation mondiale de l'IA. Cet article vise à exposer les grandes lignes d'un programme de recherche sur la gouvernance mondiale de l'IA. Il fait la distinction entre deux perspectives larges : une approche empirique, qui vise à représenter et expliquer la gouvernance mondiale de l'IA; et une approche normative, qui vise à mettre au point et appliquer les normes d'une gouvernance mondiale de l'IA adéquate. Les deux approches proposent des questions, des concepts et des théories qui permettent de mieux comprendre l’émergence de la gouvernance mondiale de l'IA. À l'inverse, envisager l'IA telle une problématique réglementaire présente une opportunité critique d'affiner les approches générales existantes de l’étude de la gouvernance mondiale.

Artificial intelligence (AI) represents a technological upheaval with the potential to transform human society. It is increasingly viewed by states, non-state actors, and international organizations (IOs) as an area of strategic importance, economic competition, and risk management. While AI development is concentrated to a handful of corporations in the United States, China, and Europe, the long-term consequences of AI implementation will be global. Autonomous weapons will have consequences for armed conflicts and power balances; automation will drive changes in job markets and global supply chains; generative AI will affect content production and challenge copyright systems; and competition around the scarce hardware needed to train AI systems will shape relations among both states and businesses. While the technology is still only lightly regulated, state and non-state actors are beginning to negotiate global rules and norms to harness and spread AI’s benefits while limiting its negative consequences. For example, in the past few years, the United Nations Educational, Scientific and Cultural Organization (UNESCO) adopted recommendations on the ethics of AI, the European Union (EU) negotiated comprehensive AI legislation, and the Group of Seven (G7) called for developing global technical standards on AI.

Our purpose in this article is to outline an agenda for research into the global governance of AI. 1 Advancing research on the global regulation of AI is imperative. The rules and arrangements that are currently being developed to regulate AI will have a considerable impact on power differentials, the distribution of economic value, and the political legitimacy of AI governance for years to come. Yet there is currently little systematic knowledge on the nature of global AI regulation, the interests influential in this process, and the extent to which emerging arrangements can manage AI’s consequences in a just and democratic manner. While poised for rapid expansion, research on the global governance of AI remains in its early stages (but see Maas 2021 ; Schmitt 2021 ).

This article complements earlier calls for research on AI governance in general ( Dafoe 2018 ; Butcher and Beridze 2019 ; Taeihagh 2021 ; Büthe et al. 2022 ) by focusing specifically on the need for systematic research into the global governance of AI. It submits that global efforts to regulate AI have reached a stage where it is necessary to start asking fundamental questions about the characteristics, sources, and consequences of these governance arrangements.

We distinguish between two broad approaches for studying the global governance of AI: an empirical perspective, informed by a positive ambition to map and explain AI governance arrangements; and a normative perspective, informed by philosophical standards for evaluating the appropriateness of AI governance arrangements. Both perspectives build on established traditions of research in political science, international relations (IR), and political philosophy, and offer questions, concepts, and theories that are helpful as we try to better understand new types of governance in world politics.

We argue that empirical and normative perspectives together offer a comprehensive agenda of research on the global governance of AI. Pursuing this agenda will help us to better understand characteristics, sources, and consequences of the global regulation of AI, with potential implications for policymaking. Conversely, exploring AI as a regulatory issue offers a critical opportunity to further develop concepts and theories of global governance as they confront the particularities of regulatory dynamics in this important area.

We advance this argument in three steps. First, we argue that AI, because of its economic, political, and social consequences, presents a range of governance challenges. While these challenges initially were taken up mainly by national authorities, recent years have seen a dramatic increase in governance initiatives by IOs. These efforts to regulate AI at global and regional levels are likely driven by several considerations, among them AI applications creating cross-border externalities that demand international cooperation and AI development taking place through transnational processes requiring transboundary regulation. Yet, so far, existing scholarship on the global governance of AI has been mainly descriptive or policy-oriented, rather than focused on theory-driven positive and normative questions.

Second, we argue that an empirical perspective can help to shed light on key questions about characteristics and sources of the global governance of AI. Based on existing concepts, the emerging governance architecture for AI can be described as a regime complex—a structure of partially overlapping and diverse governance arrangements without a clearly defined central institution or hierarchy. IR theories are useful in directing our attention to the role of power, interests, ideas, and non-state actors in the construction of this regime complex. At the same time, the specific conditions of AI governance suggest ways in which global governance theories may be usefully developed.

Third, we argue that a normative perspective raises crucial questions regarding the nature and implications of global AI governance. These questions pertain both to procedure (the process for developing rules) and to outcome (the implications of those rules). A normative perspective suggests that procedures and outcomes in global AI governance need to be evaluated in terms of how they meet relevant normative ideals, such as democracy and justice. How could the global governance of AI be organized to live up to these ideals? To what extent are emerging arrangements minimally democratic and fair in their procedures and outcomes? Conversely, the global governance of AI raises novel questions for normative theorizing, for instance, by invoking aims for AI to be “trustworthy,” “value aligned,” and “human centered.”

Advancing this agenda of research is important for several reasons. First, making more systematic use of social science concepts and theories will help us to gain a better understanding of various dimensions of the global governance of AI. Second, as a novel case of governance involving unique features, AI raises questions that will require us to further refine existing concepts and theories of global governance. Third, findings from this research agenda will be of importance for policymakers, by providing them with evidence on international regulatory gaps, the interests that have influenced current arrangements, and the normative issues at stake when developing this regime complex going forward.

The remainder of this article is structured in three substantive sections. The first section explains why AI has become a concern of global governance. The second section suggests that an empirical perspective can help to shed light on the characteristics and drivers of the global governance of AI. The third section discusses the normative challenges posed by global AI governance, focusing specifically on concerns related to democracy and justice. The article ends with a conclusion that summarizes our proposed agenda for future research on the global governance of AI.

Why does AI pose a global governance challenge? In this section, we answer this question in three steps. We begin by briefly describing the spread of AI technology in society, then illustrate the attempts to regulate AI at various levels of governance, and finally explain why global regulatory initiatives are becoming increasingly common. We argue that the growth of global governance initiatives in this area stems from AI applications creating cross-border externalities that demand international cooperation and from AI development taking place through transnational processes requiring transboundary regulation.

Due to its amorphous nature, AI escapes easy definition. Instead, the definition of AI tends to depend on the purposes and audiences of the research ( Russell and Norvig 2020 ). In the most basic sense, machines are considered intelligent when they can perform tasks that would require intelligence if done by humans ( McCarthy et al. 1955 ). This could happen through the guiding hand of humans, in “expert systems” that follow complex decision trees. It could also happen through “machine learning,” where AI systems are trained to categorize texts, images, sounds, and other data, using such categorizations to make autonomous decisions when confronted with new data. More specific definitions require that machines display a level of autonomy and capacity for learning that enables rational action. For instance, the EU’s High-Level Expert Group on AI has defined AI as “systems that display intelligent behaviour by analysing their environment and taking actions—with some degree of autonomy—to achieve specific goals” (2019, 1). Yet, illustrating the potential for conceptual controversy, this definition has been criticized for denoting both too many and too few technologies as AI ( Heikkilä 2022a ).

AI technology is already implemented in a wide variety of areas in everyday life and the economy at large. For instance, the conversational chatbot ChatGPT is estimated to have reached 100 million users just  two months after its launch at the end of 2022 ( Hu 2023 ). AI applications enable new automation technologies, with subsequent positive or negative effects on the demand for labor, employment, and economic equality ( Acemoglu and Restrepo 2020 ). Military AI is integral to lethal autonomous weapons systems (LAWS), whereby machines take autonomous decisions in warfare and battlefield targeting ( Rosert and Sauer 2018 ). Many governments and public agencies have already implemented AI in their daily operations in order to more efficiently evaluate welfare eligibility, flag potential fraud, profile suspects, make risk assessments, and engage in mass surveillance ( Saif et al. 2017 ; Powers and Ganascia 2020 ; Berk 2021 ; Misuraca and van Noordt 2022 , 38).

Societies face significant governance challenges in relation to the implementation of AI. One type of challenge arises when AI systems function poorly, such as when applications involving some degree of autonomous decision-making produce technical failures with real-world implications. The “Robodebt” scheme in Australia, for instance, was designed to detect mistaken social security payments, but the Australian government ultimately had to rescind 400,000 wrongfully issued welfare debts ( Henriques-Gomes 2020 ). Similarly, Dutch authorities recently implemented an algorithm that pushed tens of thousands of families into poverty after mistakenly requiring them to repay child benefits, ultimately forcing the government to resign ( Heikkilä 2022b ).

Another type of governance challenge arises when AI systems function as intended but produce impacts whose consequences may be regarded as problematic. For instance, the inherent opacity of AI decision-making challenges expectations on transparency and accountability in public decision-making in liberal democracies ( Burrell 2016 ; Erman and Furendal 2022a ). Autonomous weapons raise critical ethical and legal issues ( Rosert and Sauer 2019 ). AI applications for surveillance in law enforcement give rise to concerns of individual privacy and human rights ( Rademacher 2019 ). AI-driven automation involves changes in labor markets that are painful for parts of the population ( Acemoglu and Restrepo 2020 ). Generative AI upends conventional ways of producing creative content and raises new copyright and data security issues ( Metz 2022 ).

More broadly, AI presents a governance challenge due to its effects on economic competitiveness, military security, and personal integrity, with consequences for states and societies. In this respect, AI may not be radically different from earlier general-purpose technologies, such as the steam engine, electricity, nuclear power, and the internet ( Frey 2019 ). From this perspective, it is not the novelty of AI technology that makes it a pressing issue to regulate but rather the anticipation that AI will lead to large-scale changes and become a source of power for state and societal actors.

Challenges such as these have led to a rapid expansion in recent years of efforts to regulate AI at different levels of governance. The OECD AI Policy Observatory records more than 700 national AI policy initiatives from 60 countries and territories ( OECD 2021 ). Earlier research into the governance of AI has therefore naturally focused mostly on the national level ( Radu 2021 ; Roberts et al. 2021 ; Taeihagh 2021 ). However, a large number of governance initiatives have also been undertaken at the global level, and many more are underway. According to an ongoing inventory of AI regulatory initiatives by the Council of Europe, IOs overtook national authorities as the main source of such initiatives in 2020 ( Council of Europe 2023 ).  Figure 1 visualizes this trend.

Origins of AI governance initiatives, 2015–2022. Source : Council of Europe (2023 ).

According to this source, national authorities launched 170 initiatives from 2015 to 2022, while IOs put in place 210 initiatives during the same period. Over time, the share of regulatory initiatives emanating from IOs has thus grown to surpass the share resulting from national authorities. Examples of the former include the OECD Principles on Artificial Intelligence agreed in 2019, the UNESCO Recommendation on Ethics of AI adopted in 2021, and the EU’s ongoing negotiations on the EU AI Act. In addition, several governance initiatives emanate from the private sector, civil society, and multistakeholder partnerships. In the next section, we will provide a more developed characterization of these global regulatory initiatives.

Two concerns likely explain why AI increasingly is becoming subject to governance at the global level. First, AI creates externalities that do not follow national borders and whose regulation requires international cooperation. China’s Artificial Intelligence Development Plan, for instance, clearly states that the country is using AI as a leapfrog technology in order to enhance national competitiveness ( Roberts et al. 2021 ). Since states with less regulation might gain a competitive edge when developing certain AI applications, there is a risk that such strategies create a regulatory race to the bottom. International cooperation that creates a level playing field could thus be said to be in the interest of all parties.

Second, the development of AI technology is a cross-border process carried out by transnational actors—multinational firms in particular. Big tech corporations, such as Google, Meta, or the Chinese drone maker DJI, are investing vast sums into AI development. The innovations of hardware manufacturers like Nvidia enable breakthroughs but depend on complex global supply chains, and international research labs such as DeepMind regularly present cutting-edge AI applications. Since the private actors that develop AI can operate across multiple national jurisdictions, the efforts to regulate AI development and deployment also need to be transboundary. Only by introducing common rules can states ensure that AI businesses encounter similar regulatory environments, which both facilitates transboundary AI development and reduces incentives for companies to shift to countries with laxer regulation.

Successful global governance of AI could help realize many of the potential benefits of the technology while mitigating its negative consequences. For AI to contribute to increased economic productivity, for instance, there needs to be predictable and clear regulation as well as global coordination around standards that prevent competition between parallel technical systems. Conversely, a failure to provide suitable global governance could lead to substantial risks. The intentional misuse of AI technology may undermine trust in institutions, and if left unchecked, the positive and negative externalities created by automation technologies might fall unevenly across different groups. Race dynamics similar to those that arose around nuclear technology in the twentieth century—where technological leadership created large benefits—might lead international actors and private firms to overlook safety issues and create potentially dangerous AI applications ( Dafoe 2018 ; Future of Life Institute 2023 ). Hence, policymakers face the task of disentangling beneficial from malicious consequences and then foster the former while regulating the latter. Given the speed at which AI is developed and implemented, governance also risks constantly being one step behind the technological frontier.

A prime example of how AI presents a global governance challenge is the efforts to regulate military AI, in particular autonomous weapons capable of identifying and eliminating a target without the involvement of a remote human operator ( Hernandez 2021 ). Both the development and the deployment of military applications with autonomous capabilities transcend national borders. Multinational defense companies are at the forefront of developing autonomous weapons systems. Reports suggest that such autonomous weapons are now beginning to be used in armed conflicts ( Trager and Luca 2022 ). The development and deployment of autonomous weapons involve the types of competitive dynamics and transboundary consequences identified above. In addition, they raise specific concerns with respect to accountability and dehumanization ( Sparrow 2007 ; Stop Killer Robots 2023 ). For these reasons, states have begun to explore the potential for joint global regulation of autonomous weapons systems. The principal forum is the Group on Governmental Experts (GGE) within the Convention on Certain Conventional Weapons (CCW). Yet progress in these negotiations is slow as the major powers approach this issue with competing interests in mind, illustrating the challenges involved in developing joint global rules.

The example of autonomous weapons further illustrates how the global governance of AI raises urgent empirical and normative questions for research. On the empirical side, these developments invite researchers to map emerging regulatory initiatives, such as those within the CCW, and to explain why these particular frameworks become dominant. What are the principal characteristics of global regulatory initiatives in the area of autonomous weapons, and how do power differentials, interest constellations, and principled ideas influence those rules? On the normative side, these developments invite researchers to address key normative questions raised by the development and deployment of autonomous weapons. What are the key normative issues at stake in the regulation of autonomous weapons, both with respect to the process through which such rules are developed and with respect to the consequences of these frameworks? To what extent are existing normative ideals and frameworks, such as just war theory, applicable to the governing of military AI ( Roach and Eckert 2020 )? Despite the global governance challenge of AI development and use, research on this topic is still in its infancy (but see Maas 2021 ; Schmitt 2021 ). In the remainder of this article, we therefore present an agenda for research into the global governance of AI. We begin by outlining an agenda for positive empirical research on the global governance of AI and then suggest an agenda for normative philosophical research.

An empirical perspective on the global governance of AI suggests two main questions: How may we describe the emerging global governance of AI? And how may we explain the emerging global governance of AI? In this section, we argue that concepts and theories drawn from the general study of global governance will be helpful as we address these questions, but also that AI, conversely, raises novel issues that point to the need for new or refined theories. Specifically, we show how global AI governance may be mapped along several conceptual dimensions and submit that theories invoking power dynamics, interests, ideas, and non-state actors have explanatory promise.

Mapping AI Governance

A key priority for empirical research on the global governance of AI is descriptive: Where and how are new regulatory arrangements emerging at the global level? What features characterize the emergent regulatory landscape? In answering such questions, researchers can draw on scholarship on international law and IR, which have conceptualized mechanisms of regulatory change and drawn up analytical dimensions to map and categorize the resulting regulatory arrangements.

Any mapping exercise must consider the many different ways in global AI regulation may emerge and evolve. Previous research suggests that legal development may take place in at least three distinct ways. To begin with, existing rules could be reinterpreted to also cover AI ( Maas 2021 ). For example, the principles of distinction, proportionality, and precaution in international humanitarian law could be extended, via reinterpretation, to apply to LAWS, without changing the legal source. Another manner in which new AI regulation may appear is via “ add-ons ” to existing rules. For example, in the area of global regulation of autonomous vehicles, AI-related provisions were added to the 1968 Vienna Road Traffic Convention through an amendment in 2015 ( Kunz and Ó hÉigeartaigh 2020 ). Finally, AI regulation may appear as a completely new framework , either through new state behavior that results in customary international law or through a new legal act or treaty ( Maas 2021 , 96). Here, one example of regulating AI through a new framework is the aforementioned EU AI Act, which would take the form of a new EU regulation.

Once researchers have mapped emerging regulatory arrangements, a central task will be to categorize them. Prior scholarship suggests that regulatory arrangements may be fruitfully analyzed in terms of five key dimensions (cf. Koremenos et al. 2001 ; Wahlgren 2022 , 346–347). A first dimension is whether regulation is horizontal or vertical . A horizontal regulation covers several policy areas, whereas a vertical regulation is a delimited legal framework covering one specific policy area or application. In the field of AI, emergent governance appears to populate both ends of this spectrum. For example, the proposed EU AI Act (2021), the UNESCO Recommendations on the Ethics of AI (2021), and the OECD Principles on AI (2019), which are not specific to any particular AI application or field, would classify as attempts at horizontal regulation. When it comes to vertical regulation, there are fewer existing examples, but discussions on a new protocol on LAWS within the CCW signal that this type of regulation is likely to become more important in the future ( Maas 2019a ).

A second dimension runs from centralization to decentralization . Governance is centralized if there is a single, authoritative institution at the heart of a regime, such as in trade, where the World Trade Organization (WTO) fulfills this role. In contrast, decentralized arrangements are marked by parallel and partly overlapping institutions, such as in the governance of the environment, the internet, or genetic resources (cf. Raustiala and Victor 2004 ). While some IOs with universal membership, such as UNESCO, have taken initiatives relating to AI governance, no institution has assumed the role as the core regulatory body at the global level. Rather, the proliferation of parallel initiatives, across levels and regions, lends weight to the conclusion that contemporary arrangements for the global governance of AI are strongly decentralized ( Cihon et al. 2020a ).

A third dimension is the continuum from hard law to soft law . While domestic statutes and treaties may be described as hard law, soft law is associated with guidelines of conduct, recommendations, resolutions, standards, opinions, ethical principles, declarations, guidelines, board decisions, codes of conduct, negotiated agreements, and a large number of additional normative mechanisms ( Abbott and Snidal 2000 ; Wahlgren 2022 ). Even though such soft documents may initially have been drafted as non-legal texts, they may in actual practice acquire considerable strength in structuring international relations ( Orakhelashvili 2019 ). While some initiatives to regulate AI classify as hard law, including the EU’s AI Act, Burri (2017 ) suggests that AI governance is likely to be dominated by “supersoft law,” noting that there are currently numerous processes underway creating global standards outside traditional international law-making fora. In a phenomenon that might be described as “bottom-up law-making” ( Koven Levit 2017 ), states and IOs are bypassed, creating norms that defy traditional categories of international law ( Burri 2017 ).

A fourth dimension concerns private versus public regulation . The concept of private regulation overlaps partly with substance understood as soft law, to the extent that private actors develop non-binding guidelines ( Wahlgren 2022 ). Significant harmonization of standards may be developed by private standardization bodies, such as the IEEE ( Ebers 2022 ). Public authorities may regulate the responsibility of manufacturers through tort law and product liability law ( Greenstein 2022 ). Even though contracts are originally matters between private parties, some contractual matters may still be regulated and enforced by law ( Ubena 2022 ).

A fifth dimension relates to the division between military and non-military regulation . Several policymakers and scholars describe how military AI is about to escalate into a strategic arms race between major powers such as the United States and China, similar to the nuclear arms race during the Cold War (cf. Petman 2017 ; Thompson and Bremmer 2018 ; Maas 2019a ). The process in the CCW Group of Governmental Experts on the regulation of LAWS is probably the largest single negotiation on AI ( Maas 2019b ) next to the negotiations on the EU AI Act. The zero-sum logic that appears to exist between states in the area of national security, prompting a military AI arms race, may not be applicable to the same extent to non-military applications of AI, potentially enabling a clearer focus on realizing positive-sum gains through regulation.

These five dimensions can provide guidance as researchers take up the task of mapping and categorizing global AI regulation. While the evidence is preliminary, in its present form, the global governance of AI must be understood as combining horizontal and vertical elements, predominantly leaning toward soft law, being heavily decentralized, primarily public in nature, and mixing military and non-military regulation. This multi-faceted and non-hierarchical nature of global AI governance suggests that it is best characterized as a regime complex , or a “larger web of international rules and regimes” ( Alter and Meunier 2009 , 13; Keohane and Victor 2011 ) rather than as a single, discrete regime.

If global AI governance can be understood as a regime complex, which some researchers already claim ( Cihon et al. 2020a ), future scholarship should look for theoretical and methodological inspiration in research on regime complexity in other policy fields. This research has found that regime complexes are characterized by path dependence, as existing rules shape the formulation of new rules; venue shopping, as actors seek to steer regulatory efforts to the fora most advantageous to their interests; and legal inconsistencies, as rules emerge from fractious and overlapping negotiations in parallel processes ( Raustiala and Victor 2004 ). Scholars have also considered the design of regime complexes ( Eilstrup-Sangiovanni and Westerwinter 2021 ), institutional overlap among bodies in regime complexes ( Haftel and Lenz 2021 ), and actors’ forum-shopping within regime complexes ( Verdier 2022 ). Establishing whether these patterns and dynamics are key features also of the AI regime complex stands out as an important priority in future research.

Explaining AI Governance

As our understanding of the empirical patterns of global AI governance grows, a natural next step is to turn to explanatory questions. How may we explain the emerging global governance of AI? What accounts for variation in governance arrangements and how do they compare with those in other policy fields, such as environment, security, or trade? Political science and IR offer a plethora of useful theoretical tools that can provide insights into the global governance of AI. However, at the same time, the novelty of AI as a governance challenge raises new questions that may require novel or refined theories. Thus far, existing research on the global governance of AI has been primarily concerned with descriptive tasks and largely fallen short in engaging with explanatory questions.

We illustrate the potential of general theories to help explain global AI governance by pointing to three broad explanatory perspectives in IR ( Martin and Simmons 2012 )—power, interests, and ideas—which have served as primary sources of theorizing on global governance arrangements in other policy fields. These perspectives have conventionally been associated with the paradigmatic theories of realism, liberalism, and constructivism, respectively, but like much of the contemporary IR discipline, we prefer to formulate them as non-paradigmatic sources for mid-level theorizing of more specific phenomena (cf. Lake 2013 ). We focus our discussion on how accounts privileging power, interests, and ideas have explained the origins and designs of IOs and how they may help us explain wider patterns of global AI governance. We then discuss how theories of non-state actors and regime complexity, in particular, offer promising avenues for future research into the global governance of AI. Research fields like science and technology studies (e.g., Jasanoff 2016 ) or the political economy of international cooperation (e.g., Gilpin 1987 ) can provide additional theoretical insights, but these literatures are not discussed in detail here.

A first broad explanatory perspective is provided by power-centric theories, privileging the role of major states, capability differentials, and distributive concerns. While conventional realism emphasizes how states’ concern for relative gains impedes substantive international cooperation, viewing IOs as epiphenomenal reflections of underlying power relations ( Mearsheimer 1994 ), developed power-oriented theories have highlighted how powerful states seek to design regulatory contexts that favor their preferred outcomes ( Gruber 2000 ) or shape the direction of IOs using informal influence ( Stone 2011 ; Dreher et al. 2022 ).

In research on global AI governance, power-oriented perspectives are likely to prove particularly fruitful in investigating how great-power contestation shapes where and how the technology will be regulated. Focusing on the major AI powerhouses, scholars have started to analyze the contrasting regulatory strategies and policies of the United States, China, and the EU, often emphasizing issues of strategic competition, military balance, and rivalry ( Kania 2017 ; Horowitz et al. 2018 ; Payne 2018 , 2021 ; Johnson 2019 ; Jensen et al. 2020 ). Here, power-centric theories could help understand the apparent emphasis on military AI in both the United States and China, as witnessed by the recent establishment of a US National Security Commission on AI and China’s ambitious plans of integrating AI into its military forces ( Ding 2018 ). The EU, for its part, is negotiating the comprehensive AI Act, seeking to use its market power to set a European standard for AI that subsequently can become the global standard, as it previously did with its GDPR law on data protection and privacy ( Schmitt 2021 ). Given the primacy of these three actors in AI development, their preferences and outlook regarding regulatory solutions will remain a key research priority.

Power-based accounts are also likely to provide theoretical inspiration for research on AI governance in the domain of security and military competition. Some scholars are seeking to assess the implications of AI for strategic rivalries, and their possible regulation, by drawing on historical analogies ( Leung 2019 ; see also Drezner 2019 ). Observing that, from a strategic standpoint, military AI exhibits some similarities to the problems posed by nuclear weapons, researchers have examined whether lessons from nuclear arms control have applicability in the domain of AI governance. For example, Maas (2019a ) argues that historical experience suggests that the proliferation of military AI can potentially be slowed down via institutionalization, while Zaidi and Dafoe (2021 ), in a study of the Baruch Plan for Nuclear Weapons, contend that fundamental strategic obstacles—including mistrust and fear of exploitation by other states—need to be overcome to make regulation viable. This line of investigation can be extended by assessing other historical analogies, such as the negotiations that led to the Strategic Arms Limitation Talks (SALT) in 1972 or more recent efforts to contain the spread of nuclear weapons, where power-oriented factors have shown continued analytical relevance (e.g., Ruzicka 2018 ).

A second major explanatory approach is provided by the family of theoretical accounts that highlight how international cooperation is shaped by shared interests and functional needs ( Keohane 1984 ; Martin 1992 ). A key argument in rational functionalist scholarship is that states are likely to establish IOs to overcome barriers to cooperation—such as information asymmetries, commitment problems, and transaction costs—and that the design of these institutions will reflect the underlying problem structure, including the degree of uncertainty and the number of involved actors (e.g., Koremenos et al. 2001 ; Hawkins et al. 2006 ; Koremenos 2016 ).

Applied to the domain of AI, these approaches would bring attention to how the functional characteristics of AI as a governance problem shape the regulatory response. They would also emphasize the investigation of the distribution of interests and the possibility of efficiency gains from cooperation around AI governance. The contemporary proliferation of partnerships and initiatives on AI governance points to the suitability of this theoretical approach, and research has taken some preliminary steps, surveying state interests and their alignment (e.g., Campbell 2019 ; Radu 2021 ). However, a systematic assessment of how the distribution of interests would explain the nature of emerging governance arrangements, both in the aggregate and at the constituent level, has yet to be undertaken.

A third broad explanatory perspective is provided by theories emphasizing the role of history, norms, and ideas in shaping global governance arrangements. In contrast to accounts based on power and interests, this line of scholarship, often drawing on sociological assumptions and theory, focuses on how institutional arrangements are embedded in a wider ideational context, which itself is subject to change. This perspective has generated powerful analyses of how societal norms influence states’ international behavior (e.g., Acharya and Johnston 2007 ), how norm entrepreneurs play an active role in shaping the origins and diffusion of specific norms (e.g., Finnemore and Sikkink 1998 ), and how IOs socialize states and other actors into specific norms and behaviors (e.g., Checkel 2005 ).

Examining the extent to which domestic and societal norms shape discussions on global governance arrangements stands out as a particularly promising area of inquiry. Comparative research on national ethical standards for AI has already indicated significant cross-country convergence, indicating a cluster of normative principles that are likely to inspire governance frameworks in many parts of the world (e.g., Jobin et al. 2019 ). A closely related research agenda concerns norm entrepreneurship in AI governance. Here, preliminary findings suggest that civil society organizations have played a role in advocating norms relating to fundamental rights in the formulation of EU AI policy and other processes ( Ulnicane 2021 ). Finally, once AI governance structures have solidified further, scholars can begin to draw on norms-oriented scholarship to design strategies for the analysis of how those governance arrangements may play a role in socialization.

In light of the particularities of AI and its political landscape, we expect that global governance scholars will be motivated to refine and adapt these broad theoretical perspectives to address new questions and conditions. For example, considering China’s AI sector-specific resources and expertise, power-oriented theories will need to grapple with questions of institutional creation and modification occurring under a distribution of power that differs significantly from the Western-centric processes that underpin most existing studies. Similarly, rational functionalist scholars will need to adapt their tools to address questions of how the highly asymmetric distribution of AI capabilities—in particular between producers, which are few, concentrated, and highly resourced, and users and subjects, which are many, dispersed, and less resourced—affects the formation of state interests and bargaining around institutional solutions. For their part, norm-oriented theories may need to be refined to capture the role of previously understudied sources of normative and ideational content, such as formal and informal networks of computer programmers, which, on account of their expertise, have been influential in setting the direction of norms surrounding several AI technologies.

We expect that these broad theoretical perspectives will continue to inspire research on the global governance of AI, in particular for tailored, mid-level theorizing in response to new questions. However, a fully developed research agenda will gain from complementing these theories, which emphasize particular independent variables (power, interests, and norms), with theories and approaches that focus on particular issues, actors, and phenomena. There is an abundance of theoretical perspectives that can be helpful in this regard, including research on the relationship between science and politics ( Haas 1992 ; Jasanoff 2016 ), the political economy of international cooperation ( Gilpin 1987 ; Frieden et al. 2017 ), the complexity of global governance ( Raustiala and Victor 2004 ; Eilstrup-Sangiovanni and Westerwinter 2021 ), and the role of non-state actors ( Risse 2012 ; Tallberg et al. 2013 ). We focus here on the latter two: theories of regime complexity, which have grown to become a mainstream approach in global governance scholarship, as well as theories of non-state actors, which provide powerful tools for understanding how private organizations influence regulatory processes. Both literatures hold considerable promise in advancing scholarship of AI global governance beyond its current state.

As concluded above, the current structure of global AI governance fits the description of a regime complex. Thus, approaching AI governance through this theoretical lens, understanding it as a larger web of rules and regulations, can open new avenues of research (see Maas 2021 for a pioneering effort). One priority is to analyze the AI regime complex in terms of core dimensions, such as scale, diversity, and density ( Eilstrup-Sangiovanni and Westerwinter 2021 ). Pointing to the density of this regime complex, existing studies have suggested that global AI governance is characterized by a high degree of fragmentation ( Schmitt 2021 ), which has motivated assessments of the possibility of greater centralization ( Cihon et al. 2020b ). Another area of research is to examine the emergence of legal inconsistencies and tensions, likely to emerge because of the diverging preferences of major AI players and the tendency of self-interest actors to forum-shop when engaging within a regime complex. Finally, given that the AI regime complex exists in a very early state, it provides researchers with an excellent opportunity to trace the origins and evolution of this form of governance structure from the outset, thus providing a good case for both theory development and novel empirical applications.

If theories of regime complexity can shine a light on macro-level properties of AI governance, other theoretical approaches can guide research into micro-level dynamics and influences. Recognizing that non-state actors are central in both AI development and its emergent regulation, researchers should find inspiration in theories and tools developed to study the role and influence of non-state actors in global governance (for overviews, see Risse 2012 ; Jönsson and Tallberg forthcoming ). Drawing on such work will enable researchers to assess to what extent non-state actor involvement in the AI regime complex differs from previous experiences in other international regimes. It is clear that large tech companies, like Google, Meta, and Microsoft, have formed regulatory preferences and that their monetary resources and technological expertise enable them to promote these interests in legislative and bureaucratic processes. For example, the Partnership on AI (PAI), a multistakeholder organization with more than 50 members, includes American tech companies at the forefront of AI development and fosters research on issues of AI ethics and governance ( Schmitt 2021 ). Other non-state actors, including civil society watchdog organizations, like the Civil Liberties Union for Europe, have been vocal in the negotiations of the EU AI Act, further underlining the relevance of this strand of research.

When investigating the role of non-state actors in the AI regime complex, research may be guided by four primary questions. A first question concerns the interests of non-state actors regarding alternative AI global governance architectures. Here, a survey by Chavannes et al. (2020 ) on possible regulatory approaches to LAWS suggests that private companies developing AI applications have interests that differ from those of civil society organizations. Others have pointed to the role of actors rooted in research and academia who have sought to influence the development of AI ethics guidelines ( Zhu 2022 ). A second question is to what extent the regulatory institutions and processes are accessible to the aforementioned non-state actors in the first place. Are non-state actors given formal or informal opportunities to be substantively involved in the development of new global AI rules? Research points to a broad and comprehensive opening up of IOs over the past two decades ( Tallberg et al. 2013 ) and, in the domain of AI governance, early indications are that non-state actors have been granted access to several multilateral processes, including in the OECD and the EU (cf. Niklas and Dencik 2021 ). A third question concerns actual participation: Are non-state actors really making use of the opportunities to participate, and what determines the patterns of participation? In this vein, previous research has suggested that the participation of non-state actors is largely dependent on their financial resources ( Uhre 2014 ) or the political regime of their home country ( Hanegraaff et al. 2015 ). In the context of AI governance, this raises questions about if and how the vast resource disparities and divergent interests between private tech corporations and civil society organizations may bias patterns of participation. There is, for instance, research suggesting that private companies are contributing to a practice of ethics washing by committing to nonbinding ethical guidelines while circumventing regulation ( Wagner 2018 ; Jobin et al. 2019 ; Rességuier and Rodrigues 2020 ). Finally, a fourth question is to what extent, and how, non-state actors exert influence on adopted AI rules. Existing scholarship suggests that non-state actors typically seek to shape the direction of international cooperation via lobbying ( Dellmuth and Tallberg 2017 ), while others have argued that non-state actors use participation in international processes largely to expand or sustain their own resources ( Hanegraaff et al. 2016 ).

The previous section suggested that emerging global initiatives to regulate AI amount to a regime complex and that an empirical approach could help to map and explain these regulatory developments. In this section, we move beyond positive empirical questions to consider the normative concerns at stake in the global governance of AI. We argue that normative theorizing is needed both for assessing how well existing arrangements live up to ideals such as democracy and justice and for evaluating how best to specify what these ideals entail for the global governance of AI.

Ethical values frequently highlighted in the context of AI governance include transparency, inclusion, accountability, participation, deliberation, fairness, and beneficence ( Floridi et al. 2018 ; Jobin et al. 2019 ). A normative perspective suggests several ways in which to theorize and analyze such values in relation to the global governance of AI. One type of normative analysis focuses on application, that is, on applying an existing normative theory to instances of AI governance, assessing how well such regulatory arrangements realize their principles (similar to how political theorists have evaluated whether global governance lives up to standards of deliberation; see Dryzek 2011 ; Steffek and Nanz 2008 ). Such an analysis could also be pursued more narrowly by using a certain normative theory to assess the implications of AI technologies, for instance, by approaching the problem of algorithmic bias based on notions of fairness or justice ( Vredenburgh 2022 ). Another type of normative analysis moves from application to justification, analyzing the structure of global AI governance with the aim of theory construction. In this type of analysis, the goal is to construe and evaluate candidate principles for these regulatory arrangements in order to arrive at the best possible (most justified) normative theory. In this case, the theorist starts out from a normative ideal broadly construed (concept) and arrives at specific principles (conception).

In the remainder of this section, we will point to the promises of analyzing global AI governance based on the second approach. We will focus specifically on the normative ideals of justice and democracy. While many normative ideals could serve as focal points for an analysis of the AI domain, democracy and justice appear particularly central for understanding the normative implications of the governance of AI. Previous efforts to deploy political philosophy to shed light on normative aspects of global governance point to the promise of this focus (e.g., Caney 2005 , 2014 ; Buchanan 2013 ). It is also natural to focus on justice and democracy given that many of the values emphasized in AI ethics and existing ethics guidelines are analytically close to justice and democracy. Our core argument will be that normative research needs to be attentive to how these ideals would be best specified in relation to both the procedures and outcomes of the global governance of AI.

AI Ethics and the Normative Analysis of Global AI Governance

Although there is a rich literature on moral or ethical aspects related to specific AI applications, investigations into normative aspects of global AI governance are surprisingly sparse (for exceptions, see Müller 2020 ; Erman and Furendal 2022a , 2022b ). Researchers have so far focused mostly on normative and ethical questions raised by AI considered as a tool, enabling, for example, autonomous weapons systems ( Sparrow 2007 ) and new forms of political manipulation ( Susser et al. 2019 ; Christiano 2021 ). Some have also considered AI as a moral agent of its own, focusing on how we could govern, or be governed by, a hypothetical future artificial general intelligence ( Schwitzgebel and Garza 2015 ; Livingston and Risse 2019 ; cf. Tasioulas 2019 ; Bostrom et al. 2020 ; Erman and Furendal 2022a ). Examples such as these illustrate that there is, by now, a vibrant field of “AI ethics” that aims to consider normative aspects of specific AI applications.

As we have shown above, however, initiatives to regulate AI beyond the nation-state have become increasingly common, and they are often led by IOs, multinational companies, private standardization bodies, and civil society organizations. These developments raise normative issues that require a shift from AI ethics in general to systematic analyses of the implications of global AI governance. It is crucial to explore these normative dimensions of how AI is governed, since how AI is governed invokes key normative questions pertaining to the ideals that ought to be met.

Apart from attempts to map or describe the central norms in the existing global governance of AI (cf. Jobin et al.), most normative analyses of the global governance of AI can be said to have proceeded in two different ways. The dominant approach is to employ an outcome-based focus ( Dafoe 2018 ; Winfield et al. 2019 ; Taeihagh 2021 ), which starts by identifying a potential problem or promise created by AI technology and then seeks to identify governance mechanisms or principles that can minimize risks or make a desired outcome more likely. This approach can be contrasted with a procedure-based focus, which attaches comparatively more weight to how governance processes happen in existing or hypothetical regulatory arrangements. It recognizes that there are certain procedural aspects that are important and might be overlooked by an analysis that primarily assesses outcomes.

The benefits of this distinction become apparent if we focus on the ideals of justice and democracy. Broadly construed, we understand justice as an ideal for how to distribute benefits and burdens—specifying principles that determine “who owes what to whom”—and democracy as an ideal for collective decision-making and the exercise of political power—specifying principles that determine “who has political power over whom” ( Barry 1991 ; Weale 1999 ; Buchanan and Keohane 2006 ; Christiano 2008 ; Valentini 2012 , 2013 ). These two ideals can be analyzed with a focus on procedure or outcome, producing four fruitful avenues of normative research into global AI governance. First, justice could be understood as a procedural value or as a distributive outcome. Second, and likewise, democracy could be a feature of governance processes or an outcome of those processes. Below, we discuss existing research from the standpoint of each of these four avenues. We conclude that there is great potential for novel insights if normative theorists consider the relatively overlooked issues of outcome aspects of justice and procedural aspects of democracy in the global governance of AI.

Procedural and Outcome Aspects of Justice

Discussions around the implications of AI applications on justice, or fairness, are predominantly concerned with procedural aspects of how AI systems operate. For instance, ever since the problem of algorithmic bias—i.e., the tendency that AI-based decision-making reflects and exacerbates existing biases toward certain groups—was brought to public attention, AI ethicists have offered suggestions of why this is wrong, and AI developers have sought to construct AI systems that treat people “fairly” and thus produce “justice.” In this context, fairness and justice are understood as procedural ideals, which AI decision-making frustrates when it fails to treat like cases alike, and instead systematically treats individuals from different groups differently ( Fazelpour and Danks 2021 ; Zimmermann and Lee-Stronach 2022 ). Paradigmatic examples include automated predictions about recidivism among prisoners that have impacted decisions about people’s parole and algorithms used in recruitment that have systematically favored men over women ( Angwin et al. 2016 ; O'Neil 2017 ).

However, the emerging global governance of AI also has implications for how the benefits and burdens of AI technology are distributed among groups and states—i.e., outcomes ( Gilpin 1987 ; Dreher and Lang 2019 ). Like the regulation of earlier technological innovations ( Krasner 1991 ; Drezner 2019 ), AI governance may not only produce collective benefits, but also favor certain actors at the expense of others ( Dafoe 2018 ; Horowitz 2018 ). For instance, the concern about AI-driven automation and its impact on employment is that those who lose their jobs because of AI might carry a disproportionately large share of the negative externalities of the technology without being compensated through access to its benefits (cf. Korinek and Stiglitz 2019 ; Erman and Furendal 2022a ). Merely focusing on justice as a procedural value would overlook such distributive effects created by the diffusion of AI technology.

Moreover, this example illustrates that since AI adoption may produce effects throughout the global economy, regulatory efforts will have to go beyond issues relating to the technology itself. Recognizing the role of outcomes of AI governance entails that a broad range of policies need to be pursued by existing and emerging governance regimes. The global trade regime, for instance, may need to be reconsidered in order for the distribution of positive and negative externalities of AI technology to be just. Suggestions include pursuing policies that can incentivize certain kinds of AI technology or enable the profits gained by AI developers to be shared more widely (cf. Floridi et al. 2018 ; Erman and Furendal 2022a ).

In sum, with regard to outcome aspects of justice, theories are needed to settle which benefits and burdens created by global AI adoption ought to be fairly distributed and why (i.e., what the “site” and “scope” of AI justice are) (cf. Gabriel 2022 ). Similarly, theories of procedural aspects should look beyond individual applications of AI technology and ask whether a fairer distribution of influence over AI governance may help produce more fair outcomes, and if so how. Extending existing theories of distributive justice to the realm of global AI governance may put many of their central assumptions in a new light.

Procedural and Outcome Aspects of Democracy

Normative research could also fruitfully shed light on how emerging AI governance should be analyzed in relation to the ideal of democracy, such as what principles or criteria of democratic legitimacy are most defensible. It could be argued, for instance, that the decision process must be open to democratic influence for global AI governance to be democratically legitimate ( Erman and Furendal 2022b ). Here, normative theory can explain why it matters from the standpoint of democracy whether the affected public has had a say—either directly through open consultation or indirectly through representation—in formulating the principles that guide AI governance. The nature of the emerging AI regime complex—where prominent roles are held by multinational companies and private standard-setting bodies—suggests that it is far from certain that the public will have this kind of influence.

Importantly, it is likely that democratic procedures will take on different shapes in global governance compared to domestic politics ( Dahl 1999 ; Scholte 2011 ). A viable democratic theory must therefore make sense of how the unique properties of global governance raise issues or require solutions that are distinct from those in the domestic context. For example, the prominent influence of non-state actors, including the large tech corporations developing cutting-edge AI technology, suggests that it is imperative to ask whether different kinds of decision-making may require different normative standards and whether different kinds of actors may have different normative status in such decision-making arrangements.

Initiatives from non-state actors, such as the tech company-led PAI discussed above, often develop their own non-coercive ethics guidelines. Such documents may seek effects similar to coercively upheld regulation, such as the GDPR or the EU AI Act. For example, both Google and the EU specify that AI should not reinforce biases ( High-Level Expert Group on Artificial Intelligence 2019 ; Google 2022 ). However, from the perspective of democratic legitimacy, it may matter extensively which type of entity adopts AI regulations and on what grounds those decision-making entities have the authority to issue AI regulations ( Erman and Furendal 2022b ).

Apart from procedural aspects, a satisfying democratic theory of global AI governance will also have to include a systematic analysis of outcome aspects. Important outcome aspects of democracy include accountability and responsiveness. Accountability may be improved, for example, by instituting mechanisms to prevent corruption among decision-makers and to secure public access to governing documents, and responsiveness may be improved by strengthening the discursive quality of global decision processes, for instance, by involving international NGOs and civil movements that give voice to marginalized groups in society. With regard to tracing citizens’ preferences, some have argued that democratic decision-making can be enhanced by AI technology that tracks what people want and consistently reach “better” decisions than human decision-makers (cf. König and Wenzelburger 2022 ). Apart from accountability and responsiveness, other relevant outcome aspects of democracy include, for example, the tendency to promote conflict resolution, improve the epistemic quality of decisions, and dignity and equality among citizens.

In addition, it is important to analyze how procedural and outcome concerns are related. This issue is often neglected, which again can be illustrated by the ethics guidelines from IOs, such as the OECD Principles on Artificial Intelligence and the UNESCO Recommendation on Ethics of AI. Such documents often stress the importance of democratic values and principles, such as transparency, accountability, participation, and deliberation. Yet they typically treat these values as discrete and rarely explain how they are interconnected ( Jobin et al. 2019 ; Schiff et al. 2020 ; Hagendorff 2020 , 103). Democratic theory can fruitfully step in to explain how the ideal of “the rule by the people” includes two sides that are intimately connected. First, there is an access side of political power, where those affected should have a say in the decision-making, which might require participation, deliberation, and political equality. Second, there is an exercise side of political power, where those very decisions should apply in appropriate ways, which in turn might require effectiveness, transparency, and accountability. In addition to efforts to map and explain norms and values in the global governance of AI, theories of democratic AI governance can hence help explain how these two aspects are connected (cf. Erman 2020 ).

In sum, the global governance of AI raises a number of issues for normative research. We have identified four promising avenues, focused on procedural and outcome aspects of justice and democracy in the context of global AI governance. Research along these four avenues can help to shed light on the normative challenges facing the global governance of AI and the key values at stake, as well as provide the impetus for novel theories on democratic and just global AI governance.

This article has charted a new agenda for research into the global governance of AI. While existing scholarship has been primarily descriptive or policy-oriented, we propose an agenda organized around theory-driven positive and normative questions. To this end, we have outlined two broad analytical perspectives on the global governance of AI: an empirical approach, aimed at conceptualizing and explaining global AI governance; and a normative approach, aimed at developing and applying ideals for appropriate global AI governance. Pursuing these empirical and normative approaches can help to guide future scholarship on the global governance of AI toward critical questions, core concepts, and promising theories. At the same time, exploring AI as a regulatory issue provides an opportunity to further develop these general analytical approaches as they confront the particularities of this important area of governance.

We conclude this article by highlighting the key takeaways from this research agenda for future scholarship on empirical and normative dimensions of the global governance of AI. First, research is required to identify where and how AI is becoming globally governed . Mapping and conceptualizing the emerging global governance of AI is a first necessary step. We argue that research may benefit from considering the variety of ways in which new regulation may come about, from the reinterpretation of existing rules and the extension of prevailing sectoral governance to the negotiation of entirely new frameworks. In addition, we suggest that scholarship may benefit from considering how global AI governance may be conceptualized in terms of key analytical dimensions, such as horizontal–vertical, centralized–decentralized, and formal–informal.

Second, research is necessary to explain why AI is becoming globally governed in particular ways . Having mapped global AI governance, we need to account for the factors that drive and shape these regulatory processes and arrangements. We argue that political science and IR offer a variety of theoretical tools that can help to explain the global governance of AI. In particular, we highlight the promise of theories privileging the role of power, interests, ideas, regime complexes, and non-state actors, but also recognize that research fields such as science and technology studies and political economy can yield additional theoretical insights.

Third, research is needed to identify what normative ideals global AI governance ought to meet . Moving from positive to normative issues, a first critical question pertains to the ideals that should guide the design of appropriate global AI governance. We argue that normative theory provides the tools necessary to engage with this question. While normative theory can suggest several potential principles, we believe that it may be especially fruitful to start from the ideals of democracy and justice, which are foundational and recurrent concerns in discussions about political governing arrangements. In addition, we suggest that these two ideals are relevant both for the procedures by which AI regulation is adopted and for the outcomes of such regulation.

Fourth, research is required to evaluate how well global AI governance lives up to these normative ideals . Once appropriate normative ideals have been selected, we can assess to what extent and how existing arrangements conform to these principles. We argue that previous research on democracy and justice in global governance offers a model in this respect. A critical component of such research is the integration of normative and empirical research: normative research for elucidating how normative ideals would be expressed in practice, and empirical research for analyzing data on whether actual arrangements live up to those ideals.

In all, the research agenda that we outline should be of interest to multiple audiences. For students of political science and IR, it offers an opportunity to apply and refine concepts and theories in a novel area of global governance of extensive future importance. For scholars of AI, it provides an opportunity to understand how political actors and considerations shape the conditions under which AI applications may be developed and used. For policymakers, it presents an opportunity to learn about evolving regulatory practices and gaps, interests shaping emerging arrangements, and trade-offs to be confronted in future efforts to govern AI at the global level.

A previous version of this article was presented at the Global and Regional Governance workshop at Stockholm University. We are grateful to Tim Bartley, Niklas Bremberg, Lisa Dellmuth, Felicitas Fritzsche, Faradj Koliev, Rickard Söder, Carl Vikberg, Johanna von Bahr, and three anonymous reviewers for ISR for insightful comments and suggestions. The research for this article was funded by the WASP-HS program of the Marianne and Marcus Wallenberg Foundation (Grant no. MMW 2020.0044).

We use “global governance” to refer to regulatory processes beyond the nation-state, whether on a global or regional level. While states and IOs often are central to these regulatory processes, global governance also involves various types of non-state actors ( Rosenau 1999 ).

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Corporate strategy evaluation (CORE): a new method to measure strategies in organizations

• Original Article
• Published: 07 May 2024
• Volume 4 , article number  60 , ( 2024 )

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• Jheyce Milena da Silva Barros   ORCID: orcid.org/0000-0001-9908-8951 1 ,
• Brigitte Renata Bezerra de Oliveira   ORCID: orcid.org/0000-0003-0038-1053 2 ,
• Telma Lúcia de Andrade Lima   ORCID: orcid.org/0000-0001-7140-9290 2 &
• Marcos Felipe Falcão Sobral   ORCID: orcid.org/0000-0002-4768-2622 3  

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In response to challenges and constraints within the market, companies frequently embrace corporate strategies and collaborate with other entities to amplify their impact on the market and respond to market threats and limitations, seeking synergy with other companies to increase their market. The adequate adoption of corporate strategies is fundamental for the success of organizations. Despite the importance of strategies, there is no specific procedure for identifying and measuring corporate strategies, and this article introduces a novel method for measuring corporate strategies named CORE: Corporate Strategy Evaluation. The design of the (CORE) started with a systematic literature review, adopting the PRISMA methodology. Five dimension questions were constructed: vertical integration, alliances, mergers, acquisitions, and diversification. Then, aggregation and sensitivity analysis procedures were created. The proposed method was experimentally evaluated in two scenarios with random data to test it. This study aims to enhance decision accuracy and strategic identification through a two-step process. Firstly, diagnostic questions are employed in step 1 to ascertain a company's adoption of a corporate strategy, leading to step 2. This method bringing a new way to mediate corporate strategies, analyze the behavior of companies over time, compare companies in the same segment, compare companies from different elements, identify patterns of strategy, enable future crossings between strategies and variables such as performance, risk, and also with other levels of strategy.

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The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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da Silva Barros, J.M., de Oliveira, B.R.B., de Andrade Lima, T.L. et al. Corporate strategy evaluation (CORE): a new method to measure strategies in organizations. SN Bus Econ 4 , 60 (2024). https://doi.org/10.1007/s43546-024-00649-y

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