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How to read and understand a scientific paper

How to read and understand a scientific paper: a guide for non-scientists, london school of economics and political science, jennifer raff.

From vaccinations to climate change, getting science wrong has very real consequences. But journal articles, a primary way science is communicated in academia, are a different format to newspaper articles or blogs and require a level of skill and undoubtedly a greater amount of patience. Here  Jennifer Raff   has prepared a helpful guide for non-scientists on how to read a scientific paper. These steps and tips will be useful to anyone interested in the presentation of scientific findings and raise important points for scientists to consider with their own writing practice.

My post,  The truth about vaccinations: Your physician knows more than the University of Google  sparked a very lively discussion, with comments from several people trying to persuade me (and the other readers) that  their  paper disproved everything that I’d been saying. While I encourage you to go read the comments and contribute your own, here I want to focus on the much larger issue that this debate raised: what constitutes scientific authority?

It’s not just a fun academic problem. Getting the science wrong has very real consequences. For example, when a community doesn’t vaccinate children because they’re afraid of “toxins” and think that prayer (or diet, exercise, and “clean living”) is enough to prevent infection, outbreaks happen.

“Be skeptical. But when you get proof, accept proof.” –Michael Specter

What constitutes enough proof? Obviously everyone has a different answer to that question. But to form a truly educated opinion on a scientific subject, you need to become familiar with current research in that field. And to do that, you have to read the “primary research literature” (often just called “the literature”). You might have tried to read scientific papers before and been frustrated by the dense, stilted writing and the unfamiliar jargon. I remember feeling this way!  Reading and understanding research papers is a skill which every single doctor and scientist has had to learn during graduate school.  You can learn it too, but like any skill it takes patience and practice.

I want to help people become more scientifically literate, so I wrote this guide for how a layperson can approach reading and understanding a scientific research paper. It’s appropriate for someone who has no background whatsoever in science or medicine, and based on the assumption that he or she is doing this for the purpose of getting a  basic  understanding of a paper and deciding whether or not it’s a reputable study.

The type of scientific paper I’m discussing here is referred to as a  primary research article . It’s a peer-reviewed report of new research on a specific question (or questions). Another useful type of publication is a  review article . Review articles are also peer-reviewed, and don’t present new information, but summarize multiple primary research articles, to give a sense of the consensus, debates, and unanswered questions within a field.  (I’m not going to say much more about them here, but be cautious about which review articles you read. Remember that they are only a snapshot of the research at the time they are published.  A review article on, say, genome-wide association studies from 2001 is not going to be very informative in 2013. So much research has been done in the intervening years that the field has changed considerably).

Before you begin: some general advice

Reading a scientific paper is a completely different process than reading an article about science in a blog or newspaper. Not only do you read the sections in a different order than they’re presented, but you also have to take notes, read it multiple times, and probably go look up other papers for some of the details. Reading a single paper may take you a very long time at first. Be patient with yourself. The process will go much faster as you gain experience.

Most primary research papers will be divided into the following sections: Abstract, Introduction, Methods, Results, and Conclusions/Interpretations/Discussion. The order will depend on which journal it’s published in. Some journals have additional files (called Supplementary Online Information) which contain important details of the research, but are published online instead of in the article itself (make sure you don’t skip these files).

Before you begin reading, take note of the authors and their institutional affiliations. Some institutions (e.g. University of Texas) are well-respected; others (e.g.  the Discovery Institute ) may appear to be legitimate research institutions but are actually agenda-driven.  Tip:  g oogle  “Discovery Institute” to see why you don’t want to use it as a scientific authority on evolutionary theory.

Also take note of the journal in which it’s published. Reputable (biomedical) journals will be indexed by  Pubmed . [EDIT: Several people have reminded me that non-biomedical journals won’t be on Pubmed, and they’re absolutely correct! (thanks for catching that, I apologize for being sloppy here). Check out  Web of Science  for a more complete index of science journals. And please feel free to share other resources in the comments!]  Beware of  questionable journals .

As you read, write down  every single word  that you don’t understand. You’re going to have to look them all up (yes, every one. I know it’s a total pain. But you won’t understand the paper if you don’t understand the vocabulary. Scientific words have extremely precise meanings).

Step-by-step instructions for reading a primary research article

1. Begin by reading the introduction, not the abstract.

The abstract is that dense first paragraph at the very beginning of a paper. In fact, that’s often the only part of a paper that many non-scientists read when they’re trying to build a scientific argument. (This is a terrible practice—don’t do it.).  When I’m choosing papers to read, I decide what’s relevant to my interests based on a combination of the title and abstract. But when I’ve got a collection of papers assembled for deep reading, I always read the abstract last. I do this because abstracts contain a succinct summary of the entire paper, and I’m concerned about inadvertently becoming biased by the authors’ interpretation of the results.

2. Identify the BIG QUESTION.

Not “What is this paper about”, but “What problem is this entire field trying to solve?”

This helps you focus on why this research is being done.  Look closely for evidence of agenda-motivated research.

3. Summarize the background in five sentences or less.

Here are some questions to guide you:

What work has been done before in this field to answer the BIG QUESTION? What are the limitations of that work? What, according to the authors, needs to be done next?

The five sentences part is a little arbitrary, but it forces you to be concise and really think about the context of this research. You need to be able to explain why this research has been done in order to understand it.

4.   Identify the SPECIFIC QUESTION(S)

What  exactly  are the authors trying to answer with their research? There may be multiple questions, or just one. Write them down.  If it’s the kind of research that tests one or more null hypotheses, identify it/them.

Not sure what a null hypothesis is? Go read this one  and try to identify the null hypotheses in it. Keep in mind that not every paper will test a null hypothesis.

5. Identify the approach

What are the authors going to do to answer the SPECIFIC QUESTION(S)?

6. Now read the methods section. Draw a diagram for each experiment, showing exactly what the authors did.

I mean  literally  draw it. Include as much detail as you need to fully understand the work.  As an example, here is what I drew to sort out the methods for a paper I read today ( Battaglia et al. 2013: “The first peopling of South America: New evidence from Y-chromosome haplogroup Q” ). This is much less detail than you’d probably need, because it’s a paper in my specialty and I use these methods all the time.  But if you were reading this, and didn’t happen to know what “process data with reduced-median method using Network” means, you’d need to look that up.

Image credit: author

You don’t need to understand the methods in enough detail to replicate the experiment—that’s something reviewers have to do—but you’re not ready to move on to the results until you can explain the basics of the methods to someone else.

7.   Read the results section. Write one or more paragraphs to summarize the results for each experiment, each figure, and each table. Don’t yet try to decide what the results  mean , just write down what they  are.

You’ll find that, particularly in good papers, the majority of the results are summarized in the figures and tables. Pay careful attention to them!  You may also need to go to the Supplementary Online Information file to find some of the results.

 It is at this point where difficulties can arise if statistical tests are employed in the paper and you don’t have enough of a background to understand them. I can’t teach you stats in this post, but  here , and here   are some basic resources to help you.  I STRONGLY advise you to become familiar with them.

Things to pay attention to in the results section:

• Any time the words “significant” or “non-significant” are used. These have precise statistical meanings. Read more about this  here .
• If there are graphs, do they have  error bars  on them? For certain types of studies, a lack of confidence intervals is a major red flag.
• The sample size. Has the study been conducted on 10, or 10,000 people? (For some research purposes, a sample size of 10 is sufficient, but for most studies larger is better).

8. Do the results answer the SPECIFIC QUESTION(S)? What do you think they mean?

Don’t move on until you have thought about this. It’s okay to change your mind in light of the authors’ interpretation—in fact you probably will if you’re still a beginner at this kind of analysis—but it’s a really good habit to start forming your own interpretations before you read those of others.

9. Read the conclusion/discussion/Interpretation section.

What do the authors think the results mean? Do you agree with them? Can you come up with any alternative way of interpreting them? Do the authors identify any weaknesses in their own study? Do you see any that the authors missed? (Don’t assume they’re infallible!) What do they propose to do as a next step? Do you agree with that?

10. Now, go back to the beginning and read the abstract.

Does it match what the authors said in the paper? Does it fit with your interpretation of the paper?

11. FINAL STEP:  (Don’t neglect doing this)  What do other researchers say about this paper?

Who are the (acknowledged or self-proclaimed) experts in this particular field? Do they have criticisms of the study that you haven’t thought of, or do they generally support it?

Here’s a place where I do recommend you use google! But do it last, so you are better prepared to think critically about what other people say.

(12. This step may be optional for you, depending on why you’re reading a particular paper. But for me, it’s critical! I go through the “Literature cited” section to see what other papers the authors cited. This allows me to better identify the important papers in a particular field, see if the authors cited my own papers (KIDDING!….mostly), and find sources of useful ideas or techniques.)

UPDATE: If you would like to see an example of how to read a science paper using this framework, you can find one  here .

I gratefully acknowledge Professors José Bonner and Bill Saxton for teaching me how to critically read and analyze scientific papers using this method. I’m honored to have the chance to pass along what they taught me.

I’ve written a shorter version of this guide for teachers to hand out to their classes. If you’d like a PDF, shoot me an email: jenniferraff (at) utexas (dot) edu. For further comments and additional questions on this guide, please see the Comments Section on  the original post .

This piece originally appeared on the  author’s personal blog  and is reposted with permission.

Featured image credit:  Scientists in a laboratory of the University of La Rioja  by  Urcomunicacion  (Wikimedia CC BY3.0)

Note: This article gives the views of the authors, and not the position of the LSE Impact blog, nor of the London School of Economics. Please review our  Comments Policy  if you have any concerns on posting a comment below.

Jennifer Raff (Indiana University—dual Ph.D. in genetics and bioanthropology) is an assistant professor in the Department of Anthropology, University of Kansas, director and Principal Investigator of the KU Laboratory of Human Population Genomics, and assistant director of KU’s Laboratory of Biological Anthropology. She is also a research affiliate with the University of Texas anthropological genetics laboratory. She is keenly interested in public outreach and scientific literacy, writing about topics in science and pseudoscience for her blog ( violentmetaphors.com ), the Huffington Post, and for the  Social Evolution Forum .

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Reference management. Clean and simple.

How to read a scientific paper: a step-by-step guide

Scientific paper format

How to read a scientific paper in 3 steps, step 1: identify your motivations for reading a scientific paper, step 2: use selective reading to gain a high-level understanding of the scientific paper, step 3: read straight through to achieve a deep understanding of a scientific paper, frequently asked questions about reading a scientific paper efficiently, related articles.

A scientific paper is a complex document. Scientific papers are divided into multiple sections and frequently contain jargon and long sentences that make reading difficult. The process of reading a scientific paper to obtain information can often feel overwhelming for an early career researcher.

But the good news is that you can acquire the skill of efficiently reading a scientific paper, and you can learn how to painlessly obtain the information you need.

In this guide, we show you how to read a scientific paper step-by-step. You will learn:

• The scientific paper format
• How to identify your reasons for reading a scientific paper
• How to skim a paper
• How to achieve a deep understanding of a paper.

Using these steps for reading a scientific paper will help you:

• Obtain information efficiently
• Retain knowledge more effectively
• Allocate sufficient time to your reading task.

The steps below are the result of research into how scientists read scientific papers and our own experiences as scientists.

Firstly, how is a scientific paper structured?

The main sections are Abstract, Introduction, Methods, Results, and Discussion. In the table below, we describe the purpose of each component of a scientific paper.

Because the structured format of a scientific paper makes it easy to find the information you need, a common technique for reading a scientific paper is to cherry-pick sections and jump around the paper.

In a YouTube video, Dr. Amina Yonis shows this nonlinear practice for reading a scientific paper. She justifies her technique by stating that “By reading research papers like this, you are enabling yourself to have a disciplined approach, and it prevents yourself from drowning in the details before you even get a bird’s-eye view”.

Selective reading is a skill that can help you read faster and engage with the material presented. In his article on active vs. passive reading of scientific papers, cell biologist Tung-Tien Sun defines active reading as "reading with questions in mind" , searching for the answers, and focusing on the parts of the paper that answer your questions.

Therefore, reading a scientific paper from start to finish isn't always necessary to understand it. How you read the paper depends on what you need to learn. For example, oceanographer Ken Hughes suggests that you may read a scientific paper to gain awareness of a theory or field, or you may read to actively solve a problem in your research.

To successfully read a scientific paper, we advise using three strategies:

• Identify your motivations for reading a scientific paper
• Use selective reading to gain a high-level understanding of the scientific paper
• Read straight through to achieve a deep understanding of a scientific paper .

All 3 steps require you to think critically and have questions in mind.

Before you sit down to read a scientific paper, ask yourself these three questions:

• Why do I need to read this paper?
• What information am I looking for?
• Where in the paper am I most likely to find the information I need?

Is it background reading or a literature review for a research project you are currently working on? Are you getting into a new field of research? Do you wish to compare your results with the ones presented in the paper? Are you following an author’s work, and need to keep up-to-date on their current research? Are you keeping tabs on emerging methods in your field?

All of these intentions require a different reading approach.

For example, if you're delving into a new field of research, you'll want to read the introduction to gather background information and seminal references. The discussion section will also be important to understand the broader context of the findings.

If you aim to extend the work presented in a paper, and this study will be the starting point for your work, it's crucial to read the paper deeply.

If your focus is on the study design and techniques used by the authors, you'll spend most of your time reading and understanding the methods section.

Sometimes you'll need to read a paper to discuss it in your own research. This may be to compare or contrast your work with the paper's content, or to stimulate a discussion on future applications of your work.

If you are following an author’s work, a quick skim might suffice to understand how the paper fits into their overall research program.

Tip: Knowing why you want to read the paper facilitates how you will read the paper. Depending on your needs, your approach may take the form of a surface-level reading or a deep and thorough reading.

Knowing your motivations will guide your navigation through the paper because you have already identified which sections are most likely to contain the information you need. Approaching reading a paper in this way saves you time and makes the task less daunting.

➡️ Learn more about how to write a literature review

Begin by gaining an overview of the paper by following these simple steps:

• Read the title. What type of paper is it? Is it a journal article, a review, a methods paper, or a commentary?
• Read the abstract . The abstract is a summary of the study. What is the study about? What question was addressed? What methods were used? What did the authors find, and what are the key findings? What do the authors think are the implications of the work? Reading the abstract immediately tells you whether you should invest the time to read the paper fully.
• Look at the headings and subheadings, which describe the sections and subsections of the paper. The headings and subheadings outline the story of the paper.
• Skim the introduction. An introduction has a clear structure. The first paragraph is background information on the topic. If you are new to the field, you will read this closely, whereas an expert in that field will skim this section. The second component defines the gap in knowledge that the paper aims to address. What is unknown, and what research is needed? What problem needs to be solved? Here, you should find the questions that will be addressed by the study, and the goal of the research. The final paragraph summarizes how the authors address their research question, for example, what hypothesis will be tested, and what predictions the authors make. As you read, make a note of key references. By the end of the introduction, you should understand the goal of the research.
• Go to the results section, and study the figures and tables. These are the data—the meat of the study. Try to comprehend the data before reading the captions. After studying the data, read the captions. Do not expect to understand everything immediately. Remember, this is the result of many years of work. Make a note of what you do not understand. In your second reading, you will read more deeply.
• Skim the discussion. There are three components. The first part of the discussion summarizes what the authors have found, and what they think the implications of the work are. The second part discusses some (usually not all!) limitations of the study, and the final part is a concluding statement.
• Glance at the methods. Get a brief overview of the techniques used in the study. Depending on your reading goals, you may spend a lot of time on this section in subsequent readings, or a cursory reading may be sufficient.
• Summarize what the paper is about—its key take-home message—in a sentence or two. Ask yourself if you have got the information you need.
• List any terminology you may need to look up before reading the paper again.
• Scan the reference list. Make a note of papers you may need to read for background information before delving further into the paper.

Congratulations, you have completed the first reading! You now have gained a high-level perspective of the study, which will be enough for many research purposes.

Now that you have an overview of the work and you have identified what information you want to obtain, you are ready to understand the paper on a deeper level. Deep understanding is achieved in the second and subsequent readings with note-taking and active reflection. Here is a step-by-step guide.

• Active engagement with the material
• Critical thinking
• Creative thinking
• Synthesis of information
• Consolidation of information into memory.

Highlighting sentences helps you quickly scan the paper and be reminded of the key points, which is helpful when you return to the paper later.

Notes may include ideas, connections to other work, questions, comments, and references to follow up on.

There are many ways for taking notes on a paper. You can:

• Print out the paper, and write your notes in the margins.
• Annotate the paper PDF from your desktop computer, or mobile device .
• Use personal knowledge management software, like Notion , Obsidian, or Evernote, for note-taking. Notes are easy to find in a structured database and can be linked to each other.
• Use reference management tools to take notes. Having your notes stored with the scientific papers you’ve read has the benefit of keeping all your ideas in one place. Some reference managers, like Paperpile, allow you to add notes to your papers, and highlight key sentences on PDFs .

Note-taking facilitates critical thinking and helps you evaluate the evidence that the authors present. Ask yourself questions like:

• What new contribution has the study made to the literature?
• How have the authors interpreted the results? (Remember, the authors have thought about their results more deeply than anybody else.)
• What do I think the results mean?
• Are the findings well-supported?
• What factors might have affected the results, and have the authors addressed them?
• Are there alternative explanations for the results?
• What are the strengths and weaknesses of the study?
• What are the broader implications of the study?
• What should be done next?

Note-taking also encourages creative thinking . Ask yourself questions like:

• What new ideas have arisen from reading the paper?
• How does it connect with your work?
• What connections to other papers can you make?
• Write a summary of the paper in your own words. This is your attempt to integrate the new knowledge you have gained with what you already know from other sources and to consolidate that information into memory. You may find that you have to go back and re-read some sections to confirm some of the details.
• Discuss the paper with others. You may find that even at this stage, there are still aspects of the paper that you are striving to understand. It is now a good time to reach out to others—peers in your program, your advisor, or even on social media. In their 10 simple rules for reading a scientific paper , Maureen Carey and coauthors suggest that participating in journal clubs, where you meet with peers to discuss interesting or important scientific papers, is a great way to clarify your understanding.
• A scientific paper can be read over many days. According to research presented in the book " Make it Stick: The Science of Successful Learning " by writer Peter Brown and psychology professors Henry Roediger and Mark McDaniel, "spaced practice" is more effective for retaining information than focusing on a single skill or subject until it is mastered. This involves breaking up learning into separate periods of training or studying. Applying this research to reading a scientific paper suggests that spacing out your reading by breaking the work into separate reading sessions can help you better commit the information in a paper to memory.

A dense journal article may need many readings to be understood fully. It is useful to remember that many scientific papers result from years of hard work, and the expectation of achieving a thorough understanding in one sitting must be modified accordingly. But, the process of reading a scientific paper will get easier and faster with experience.

The best way to read a scientific paper depends on your needs. Before reading the paper, identify your motivations for reading a scientific paper, and pinpoint the information you need. This will help you decide between skimming the paper and reading the paper more thoroughly.

Don’t read the paper from beginning to end. Instead, be aware of the scientific paper format. Take note of the information you need before starting to read the paper. Then skim the paper, jumping to the appropriate sections in the paper, to get the information you require.

It varies. Skimming a scientific paper may take anywhere between 15 minutes to one hour. Reading a scientific paper to obtain a deep understanding may take anywhere between 1 and 6 hours. It is not uncommon to have to read a dense paper in chunks over numerous days.

First, read the introduction to understand the main thesis and findings of the paper. Pay attention to the last paragraph of the introduction, where you can find a high-level summary of the methods and results. Next, skim the paper by jumping to the results and discussion. Then carefully read the paper from start to finish, taking notes as you read. You will need more than one reading to fully understand a dense research paper.

To read a scientific paper critically, be an active reader. Take notes, highlight important sentences, and write down questions as you read. Study the data. Take care to evaluate the evidence presented in the paper.

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Reading a Scholarly Article or Research Paper

Identifying a research problem to investigate usually requires a preliminary search for and critical review of the literature in order to gain an understanding about how scholars have examined a topic. Scholars rarely structure research studies in a way that can be followed like a story; they are complex and detail-intensive and often written in a descriptive and conclusive narrative form. However, in the social and behavioral sciences, journal articles and stand-alone research reports are generally organized in a consistent format that makes it easier to compare and contrast studies and to interpret their contents.

General Reading Strategies

W hen you first read an article or research paper, focus on asking specific questions about each section. This strategy can help with overall comprehension and with understanding how the content relates [or does not relate] to the problem you want to investigate. As you review more and more studies, the process of understanding and critically evaluating the research will become easier because the content of what you review will begin to coalescence around common themes and patterns of analysis. Below are recommendations on how to read each section of a research paper effectively. Note that the sections to read are out of order from how you will find them organized in a journal article or research paper.

1.  Abstract

The abstract summarizes the background, methods, results, discussion, and conclusions of a scholarly article or research paper. Use the abstract to filter out sources that may have appeared useful when you began searching for information but, in reality, are not relevant. Questions to consider when reading the abstract are:

• Is this study related to my question or area of research?
• What is this study about and why is it being done ?
• What is the working hypothesis or underlying thesis?
• What is the primary finding of the study?
• Are there words or terminology that I can use to either narrow or broaden the parameters of my search for more information?

2.  Introduction

If, after reading the abstract, you believe the paper may be useful, focus on examining the research problem and identifying the questions the author is trying to address. This information is usually located within the first few paragraphs of the introduction or in the concluding paragraph. Look for information about how and in what way this relates to what you are investigating. In addition to the research problem, the introduction should provide the main argument and theoretical framework of the study and, in the last paragraphs of the introduction, describe what the author(s) intend to accomplish. Questions to consider when reading the introduction include:

• What is this study trying to prove or disprove?
• What is the author(s) trying to test or demonstrate?
• What do we already know about this topic and what gaps does this study try to fill or contribute a new understanding to the research problem?
• Why should I care about what is being investigated?
• Will this study tell me anything new related to the research problem I am investigating?

3.  Literature Review

The literature review describes and critically evaluates what is already known about a topic. Read the literature review to obtain a big picture perspective about how the topic has been studied and to begin the process of seeing where your potential study fits within the domain of prior research. Questions to consider when reading the literature review include:

• W hat other research has been conducted about this topic and what are the main themes that have emerged?
• What does prior research reveal about what is already known about the topic and what remains to be discovered?
• What have been the most important past findings about the research problem?
• How has prior research led the author(s) to conduct this particular study?
• Is there any prior research that is unique or groundbreaking?
• Are there any studies I could use as a model for designing and organizing my own study?

4.  Discussion/Conclusion

The discussion and conclusion are usually the last two sections of text in a scholarly article or research report. They reveal how the author(s) interpreted the findings of their research and presented recommendations or courses of action based on those findings. Often in the conclusion, the author(s) highlight recommendations for further research that can be used to develop your own study. Questions to consider when reading the discussion and conclusion sections include:

• What is the overall meaning of the study and why is this important? [i.e., how have the author(s) addressed the " So What? " question].
• What do you find to be the most important ways that the findings have been interpreted?
• What are the weaknesses in their argument?
• Do you believe conclusions about the significance of the study and its findings are valid?
• What limitations of the study do the author(s) describe and how might this help formulate my own research?
• Does the conclusion contain any recommendations for future research?

5.  Methods/Methodology

The methods section describes the materials, techniques, and procedures for gathering information used to examine the research problem. If what you have read so far closely supports your understanding of the topic, then move on to examining how the author(s) gathered information during the research process. Questions to consider when reading the methods section include:

• Did the study use qualitative [based on interviews, observations, content analysis], quantitative [based on statistical analysis], or a mixed-methods approach to examining the research problem?
• What was the type of information or data used?
• Could this method of analysis be repeated and can I adopt the same approach?
• Is enough information available to repeat the study or should new data be found to expand or improve understanding of the research problem?

6.  Results

After reading the above sections, you should have a clear understanding of the general findings of the study. Therefore, read the results section to identify how key findings were discussed in relation to the research problem. If any non-textual elements [e.g., graphs, charts, tables, etc.] are confusing, focus on the explanations about them in the text. Questions to consider when reading the results section include:

• W hat did the author(s) find and how did they find it?
• Does the author(s) highlight any findings as most significant?
• Are the results presented in a factual and unbiased way?
• Does the analysis of results in the discussion section agree with how the results are presented?
• Is all the data present and did the author(s) adequately address gaps?
• What conclusions do you formulate from this data and does it match with the author's conclusions?

7.  References

The references list the sources used by the author(s) to document what prior research and information was used when conducting the study. After reviewing the article or research paper, use the references to identify additional sources of information on the topic and to examine critically how these sources supported the overall research agenda. Questions to consider when reading the references include:

• Do the sources cited by the author(s) reflect a diversity of disciplinary viewpoints, i.e., are the sources all from a particular field of study or do the sources reflect multiple areas of study?
• Are there any unique or interesting sources that could be incorporated into my study?
• What other authors are respected in this field, i.e., who has multiple works cited or is cited most often by others?
• What other research should I review to clarify any remaining issues or that I need more information about?

NOTE :  A final strategy in reviewing research is to copy and paste the title of the source [journal article, book, research report] into Google Scholar . If it appears, look for a "cited by" followed by a hyperlinked number [e.g., Cited by 45]. This number indicates how many times the study has been subsequently cited in other, more recently published works. This strategy, known as citation tracking, can be an effective means of expanding your review of pertinent literature based on a study you have found useful and how scholars have cited it. The same strategies described above can be applied to reading articles you find in the list of cited by references.

Reading Tip

Specific Reading Strategies

Effectively reading scholarly research is an acquired skill that involves attention to detail and an ability to comprehend complex ideas, data, and theoretical concepts in a way that applies logically to the research problem you are investigating. Here are some specific reading strategies to consider.

As You are Reading

• Focus on information that is most relevant to the research problem; skim over the other parts.
• As noted above, read content out of order! This isn't a novel; you want to start with the spoiler to quickly assess the relevance of the study.
• Think critically about what you read and seek to build your own arguments; not everything may be entirely valid, examined effectively, or thoroughly investigated.
• Look up the definitions of unfamiliar words, concepts, or terminology. A good scholarly source is Credo Reference .

Taking notes as you read will save time when you go back to examine your sources. Here are some suggestions:

• Mark or highlight important text as you read [e.g., you can use the highlight text  feature in a PDF document]
• Take notes in the margins [e.g., Adobe Reader offers pop-up sticky notes].
• Highlight important quotations; consider using different colors to differentiate between quotes and other types of important text.
• Summarize key points about the study at the end of the paper. To save time, these can be in the form of a concise bulleted list of statements [e.g., intro has provides historical background; lit review has important sources; good conclusions].

Write down thoughts that come to mind that may help clarify your understanding of the research problem. Here are some examples of questions to ask yourself:

• Do I understand all of the terminology and key concepts?
• Do I understand the parts of this study most relevant to my topic?
• What specific problem does the research address and why is it important?
• Are there any issues or perspectives the author(s) did not consider?
• Do I have any reason to question the validity or reliability of this research?
• How do the findings relate to my research interests and to other works which I have read?

Adapted from text originally created by Holly Burt, Behavioral Sciences Librarian, USC Libraries, April 2018.

Another Reading Tip

When is it Important to Read the Entire Article or Research Paper

Laubepin argues, "Very few articles in a field are so important that every word needs to be read carefully." However, this implies that some studies are worth reading carefully. As painful and time-consuming as it may seem, there are valid reasons for reading a study in its entirety from beginning to end. Here are some examples:

• Studies Published Very Recently .  The author(s) of a recent, well written study will provide a survey of the most important or impactful prior research in the literature review section. This can establish an understanding of how scholars in the past addressed the research problem. In addition, the most recently published sources will highlight what is currently known and what gaps in understanding currently exist about a topic, usually in the form of the need for further research in the conclusion .
• Surveys of the Research Problem .  Some papers provide a comprehensive analytical overview of the research problem. Reading this type of study can help you understand underlying issues and discover why scholars have chosen to investigate the topic. This is particularly important if the study was published very recently because the author(s) should cite all or most of the key prior research on the topic. Note that, if it is a long-standing problem, there may be studies that specifically review the literature to identify gaps that remain. These studies often include the word review in their title [e.g., Hügel, Stephan, and Anna R. Davies. "Public Participation, Engagement, and Climate Change Adaptation: A Review of the Research Literature." Wiley Interdisciplinary Reviews: Climate Change 11 (July-August 2020): https://doi.org/10.1002/ wcc.645].
• Highly Cited .  If you keep coming across the same citation to a study while you are reviewing the literature, this implies it was foundational in establishing an understanding of the research problem or the study had a significant impact within the literature [positive or negative]. Carefully reading a highly cited source can help you understand how the topic emerged and motivated scholars to further investigate the problem. It also could be a study you need to cite as foundational in your own paper to demonstrate to the reader that you understand the roots of the problem.
• Historical Overview .  Knowing the historical background of a research problem may not be the focus of your analysis. Nevertheless, carefully reading a study that provides a thorough description and analysis of the history behind an event, issue, or phenomenon can add important context to understanding the topic and what aspect of the problem you may want to examine further.
• Innovative Methodological Design .  Some studies are significant and worth reading in their entirety because the author(s) designed a unique or innovative approach to researching the problem. This may justify reading the entire study because it can motivate you to think creatively about pursuing an alternative or non-traditional approach to examining your topic of interest. These types of studies are generally easy to identify because they are often cited in others works because of their unique approach to studying the research problem.
• Cross-disciplinary Approach .  R eviewing studies produced outside of your discipline is an essential component of investigating research problems in the social and behavioral sciences. Consider reading a study that was conducted by author(s) based in a different discipline [e.g., an anthropologist studying political cultures; a study of hiring practices in companies published in a sociology journal]. This approach can generate a new understanding or a unique perspective about the topic . If you are not sure how to search for studies published in a discipline outside of your major or of the course you are taking, contact a librarian for assistance.

Laubepin, Frederique. How to Read (and Understand) a Social Science Journal Article . Inter-University Consortium for Political and Social Research (ISPSR), 2013; Shon, Phillip Chong Ho. How to Read Journal Articles in the Social Sciences: A Very Practical Guide for Students . 2nd edition. Thousand Oaks, CA: Sage, 2015; Lockhart, Tara, and Mary Soliday. "The Critical Place of Reading in Writing Transfer (and Beyond): A Report of Student Experiences." Pedagogy 16 (2016): 23-37; Maguire, Moira, Ann Everitt Reynolds, and Brid Delahunt. "Reading to Be: The Role of Academic Reading in Emergent Academic and Professional Student Identities." Journal of University Teaching and Learning Practice 17 (2020): 5-12.

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• Next: Narrowing a Topic Idea >>
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Information

How to Read a Research Paper – A Guide to Setting Research Goals, Finding Papers to Read, and More

If you work in a scientific field, you should try to build a deep and unbiased understanding of that field. This not only educates you in the best possible way but also helps you envision the opportunities in your space.

A research paper is often the culmination of a wide range of deep and authentic practices surrounding a topic. When writing a research paper, the author thinks critically about the problem, performs rigorous research, evaluates their processes and sources, organizes their thoughts, and then writes. These genuinely-executed practices make for a good research paper.

If you’re struggling to build a habit of reading papers (like I am) on a regular basis, I’ve tried to break down the whole process. I've talked to researchers in the field, read a bunch of papers and blogs from distinguished researchers, and jotted down some techniques that you can follow.

Let’s start off by understanding what a research paper is and what it is NOT!

What is a Research Paper?

A research paper is a dense and detailed manuscript that compiles a thorough understanding of a problem or topic. It offers a proposed solution and further research along with the conditions under which it was deduced and carried out, the efficacy of the solution and the research performed, and potential loopholes in the study.

A research paper is written not only to provide an exceptional learning opportunity but also to pave the way for further advancements in the field. These papers help other scholars germinate the thought seed that can either lead to a new world of ideas or an innovative method of solving a longstanding problem.

What Research Papers are NOT

There is a common notion that a research paper is a well-informed summary of a problem or topic written by means of other sources.

But you shouldn't mistake it for a book or an opinionated account of an individual’s interpretation of a particular topic.

Why Should You Read Research Papers?

What I find fascinating about reading a good research paper is that you can draw on a profound study of a topic and engage with the community on a new perspective to understand what can be achieved in and around that topic.

I work at the intersection of instructional design and data science. Learning is part of my day-to-day responsibilities. If the source of my education is flawed or inefficient, I’d fail at my job in the long term. This applies to many other jobs in Science with a special focus on research.

There are three important reasons to read a research paper:

• Knowledge —  Understanding the problem from the eyes of someone who has probably spent years solving it and has taken care of all the edge cases that you might not think of at the beginning.
• Exploration —  Whether you have a pinpointed agenda or not, there is a very high chance that you will stumble upon an edge case or a shortcoming that is worth following up. With persistent efforts over a considerable amount of time, you can learn to use that knowledge to make a living.
• Research and review —  One of the main reasons for writing a research paper is to further the development in the field. Researchers read papers to review them for conferences or to do a literature survey of a new field. For example, Yann LeCun’ s paper on integrating domain constraints into backpropagation set the foundation of modern computer vision back in 1989. After decades of research and development work, we have come so far that we're now perfecting problems like object detection and optimizing autonomous vehicles.

Not only that, with the help of the internet, you can extrapolate all of these reasons or benefits onto multiple business models. It can be an innovative state-of-the-art product, an efficient service model, a content creator, or a dream job where you are solving problems that matter to you.

Goals for Reading a Research Paper — What Should You Read About?

The first thing to do is to figure out your motivation for reading the paper. There are two main scenarios that might lead you to read a paper:

• Scenario 1 —  You have a well-defined agenda/goal and you are deeply invested in a particular field. For example, you’re an NLP practitioner and you want to learn how GPT-4 has given us a breakthrough in NLP. This is always a nice scenario to be in as it offers clarity.
• Scenario 2 —  You want to keep abreast of the developments in a host of areas, say how a new deep learning architecture has helped us solve a 50-year old biological problem of understanding protein structures. This is often the case for beginners or for people who consume their daily dose of news from research papers (yes, they exist!).

If you’re an inquisitive beginner with no starting point in mind, start with scenario 2. Shortlist a few topics you want to read about until you find an area that you find intriguing. This will eventually lead you to scenario 1.

ML Reproducibility Challenge

In addition to these generic goals, if you need an end goal for your habit-building exercise of reading research papers, you should check out the ML reproducibility challenge.

You’ll find top-class papers from world-class conferences that are worth diving deep into and reproducing the results.

They conduct this challenge twice a year and they have one coming up in Spring 2021. You should study the past three versions of the challenge, and I’ll write a detailed post on what to expect, how to prepare, and so on.

Now you must be wondering – how can you find the right paper to read?

How to Find the Right Paper to Read

In order to get some ideas around this, I reached out to my friend, Anurag Ghosh who is a researcher at Microsoft. Anurag has been working at the crossover of computer vision, machine learning, and systems engineering.

Here are a few of his tips for getting started:

• Always pick an area you're interested in.
• Read a few good books or detailed blog posts on that topic and start diving deep by reading the papers referenced in those resources.
• Look for seminal papers around that topic. These are papers that report a major breakthrough in the field and offer a new method perspective with a huge potential for subsequent research in that field. Check out papers from the morning paper or C VF - test of time award/Helmholtz prize (if you're interested in computer vision).
• Check out books like Computer Vision: Algorithms and Applications by Richard Szeliski and look for the papers referenced there.
• Have and build a sense of community. Find people who share similar interests, and join groups/subreddits/discord channels where such activities are promoted.

In addition to these invaluable tips, there are a number of web applications that I’ve shortlisted that help me narrow my search for the right papers to read:

• r/MachineLearning  — there are many researchers, practitioners, and engineers who share their work along with the papers they've found useful in achieving those results.

• Arxiv Sanity Preserver  — built by Andrej Karpathy to accelerate research. It is a repository of 142,846 papers from computer science, machine learning, systems, AI, Stats, CV, and so on. It also offers a bunch of filters, powerful search functionality, and a discussion forum to make for a super useful research platform.

• Google Research  — the research teams at Google are working on problems that have an impact on our everyday lives. They share their publications for individuals and teams to learn from, contribute to, and expedite research. They also have a Google AI blog that you can check out.

How to Read a Research Paper

After you have stocked your to-read list, then comes the process of reading these papers. Remember that NOT every paper is useful to read and we need a mechanism that can help us quickly screen papers that are worth reading.

To tackle this challenge, you can use this Three-Pass Approach by S. Keshav . This approach proposes that you read the paper in three passes instead of starting from the beginning and diving in deep until the end.

The three pass approach

• The first pass —  is a quick scan to capture a high-level view of the paper. Read the title, abstract, and introduction carefully followed by the headings of the sections and subsections and lastly the conclusion. It should take you no more than 5–10 mins to figure out if you want to move to the second pass.
• The second pass —  is a more focused read without checking for the technical proofs. You take down all the crucial notes, underline the key points in the margins. Carefully study the figures, diagrams, and illustrations. Review the graphs, mark relevant unread references for further reading. This helps you understand the background of the paper.
• The third pass —  reaching this pass denotes that you’ve found a paper that you want to deeply understand or review. The key to the third pass is to reproduce the results of the paper. Check it for all the assumptions and jot down all the variations in your re-implementation and the original results. Make a note of all the ideas for future analysis. It should take 5–6 hours for beginners and 1–2 hours for experienced readers.

Tools and Software to Keep Track of Your Pipeline of Papers

If you’re sincere about reading research papers, your list of papers will soon grow into an overwhelming stack that is hard to keep track of. Fortunately, we have software that can help us set up a mechanism to manage our research.

Here are a bunch of them that you can use:

• Mendeley [not free]  — you can add papers directly to your library from your browser, import documents, generate references and citations, collaborate with fellow researchers, and access your library from anywhere. This is mostly used by experienced researchers.

• Zotero [free & open source] —  Along the same lines as Mendeley but free of cost. You can make use of all the features but with limited storage space.

• Notion —  this is great if you are just starting out and want to use something lightweight with the option to organize your papers, jot down notes, and manage everything in one workspace. It might not stand anywhere in comparison with the above tools but I personally feel comfortable using Notion and I have created this board to keep track of my progress for now that you can duplicate:

⚠️ Symptoms of Reading a Research Paper

Reading a research paper can turn out to be frustrating, challenging, and time-consuming especially when you’re a beginner. You might face the following common symptoms:

• You might start feeling dumb for not understanding a thing a paper says.
• Finding yourself pushing too hard to understand the math behind those proofs.
• Beating your head against the wall to wrap it around the number of acronyms used in the paper. Just kidding, you’ll have to look up those acronyms every now and then.
• Being stuck on one paragraph for more than an hour.

Here’s a complete list of emotions that you might undergo as explained by Adam Ruben in this article .

Key Takeaways

We should be all set to dive right in. Here’s a quick summary of what we have covered here:

• A research paper is an in-depth study that offers an detailed explanation of a topic or problem along with the research process, proofs, explained results, and ideas for future work.
• Read research papers to develop a deep understanding of a topic/problem. Then you can either review papers as part of being a researcher, explore the domain and the kind of problems to build a solution or startup around it, or you can simply read them to keep abreast of the developments in your domain of interest.
• If you’re a beginner, start with exploration to soon find your path to goal-oriented research.
• In order to find good papers to read, you can use websites like arxiv-sanity, google research, and subreddits like r/MachineLearning.
• Reading approach — Use the 3-pass method to find a paper.
• Keep track of your research, notes, developments by using tools like Zotero/Notion.
• This can get overwhelming in no time. Make sure you start off easy and increment your load progressively.

Remember: Art is not a single method or step done over a weekend but a process of accomplishing remarkable results over time.

You can also watch the video on this topic on my YouTube channel :

Feel free to respond to this blog or comment on the video if you have some tips, questions, or thoughts!

If this tutorial was helpful, you should check out my data science and machine learning courses on Wiplane Academy . They are comprehensive yet compact and helps you build a solid foundation of work to showcase.

Web and Data Science Consultant | Instructional Design

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Open Access

Ten simple rules for reading a scientific paper

* E-mail: [email protected]

Affiliation Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America

• Maureen A. Carey, 
• Kevin L. Steiner, 
• William A. Petri Jr

Published: July 30, 2020

• https://doi.org/10.1371/journal.pcbi.1008032
• Reader Comments

Citation: Carey MA, Steiner KL, Petri WA Jr (2020) Ten simple rules for reading a scientific paper. PLoS Comput Biol 16(7): e1008032. https://doi.org/10.1371/journal.pcbi.1008032

Editor: Scott Markel, Dassault Systemes BIOVIA, UNITED STATES

Copyright: © 2020 Carey et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: MAC was supported by the PhRMA Foundation's Postdoctoral Fellowship in Translational Medicine and Therapeutics and the University of Virginia's Engineering-in-Medicine seed grant, and KLS was supported by the NIH T32 Global Biothreats Training Program at the University of Virginia (AI055432). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

“There is no problem that a library card can't solve” according to author Eleanor Brown [ 1 ]. This advice is sound, probably for both life and science, but even the best tool (like the library) is most effective when accompanied by instructions and a basic understanding of how and when to use it.

For many budding scientists, the first day in a new lab setting often involves a stack of papers, an email full of links to pertinent articles, or some promise of a richer understanding so long as one reads enough of the scientific literature. However, the purpose and approach to reading a scientific article is unlike that of reading a news story, novel, or even a textbook and can initially seem unapproachable. Having good habits for reading scientific literature is key to setting oneself up for success, identifying new research questions, and filling in the gaps in one’s current understanding; developing these good habits is the first crucial step.

Advice typically centers around two main tips: read actively and read often. However, active reading, or reading with an intent to understand, is both a learned skill and a level of effort. Although there is no one best way to do this, we present 10 simple rules, relevant to novices and seasoned scientists alike, to teach our strategy for active reading based on our experience as readers and as mentors of undergraduate and graduate researchers, medical students, fellows, and early career faculty. Rules 1–5 are big picture recommendations. Rules 6–8 relate to philosophy of reading. Rules 9–10 guide the “now what?” questions one should ask after reading and how to integrate what was learned into one’s own science.

Rule 1: Pick your reading goal

What you want to get out of an article should influence your approach to reading it. Table 1 includes a handful of example intentions and how you might prioritize different parts of the same article differently based on your goals as a reader.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pcbi.1008032.t001

Rule 2: Understand the author’s goal

In written communication, the reader and the writer are equally important. Both influence the final outcome: in this case, your scientific understanding! After identifying your goal, think about the author’s goal for sharing this project. This will help you interpret the data and understand the author’s interpretation of the data. However, this requires some understanding of who the author(s) are (e.g., what are their scientific interests?), the scientific field in which they work (e.g., what techniques are available in this field?), and how this paper fits into the author’s research (e.g., is this work building on an author’s longstanding project or controversial idea?). This information may be hard to glean without experience and a history of reading. But don’t let this be a discouragement to starting the process; it is by the act of reading that this experience is gained!

A good step toward understanding the goal of the author(s) is to ask yourself: What kind of article is this? Journals publish different types of articles, including methods, review, commentary, resources, and research articles as well as other types that are specific to a particular journal or groups of journals. These article types have different formatting requirements and expectations for content. Knowing the article type will help guide your evaluation of the information presented. Is the article a methods paper, presenting a new technique? Is the article a review article, intended to summarize a field or problem? Is it a commentary, intended to take a stand on a controversy or give a big picture perspective on a problem? Is it a resource article, presenting a new tool or data set for others to use? Is it a research article, written to present new data and the authors’ interpretation of those data? The type of paper, and its intended purpose, will get you on your way to understanding the author’s goal.

Rule 3: Ask six questions

When reading, ask yourself: (1) What do the author(s) want to know (motivation)? (2) What did they do (approach/methods)? (3) Why was it done that way (context within the field)? (4) What do the results show (figures and data tables)? (5) How did the author(s) interpret the results (interpretation/discussion)? (6) What should be done next? (Regarding this last question, the author(s) may provide some suggestions in the discussion, but the key is to ask yourself what you think should come next.)

Each of these questions can and should be asked about the complete work as well as each table, figure, or experiment within the paper. Early on, it can take a long time to read one article front to back, and this can be intimidating. Break down your understanding of each section of the work with these questions to make the effort more manageable.

Rule 4: Unpack each figure and table

Scientists write original research papers primarily to present new data that may change or reinforce the collective knowledge of a field. Therefore, the most important parts of this type of scientific paper are the data. Some people like to scrutinize the figures and tables (including legends) before reading any of the “main text”: because all of the important information should be obtained through the data. Others prefer to read through the results section while sequentially examining the figures and tables as they are addressed in the text. There is no correct or incorrect approach: Try both to see what works best for you. The key is making sure that one understands the presented data and how it was obtained.

For each figure, work to understand each x- and y-axes, color scheme, statistical approach (if one was used), and why the particular plotting approach was used. For each table, identify what experimental groups and variables are presented. Identify what is shown and how the data were collected. This is typically summarized in the legend or caption but often requires digging deeper into the methods: Do not be afraid to refer back to the methods section frequently to ensure a full understanding of how the presented data were obtained. Again, ask the questions in Rule 3 for each figure or panel and conclude with articulating the “take home” message.

Rule 5: Understand the formatting intentions

Just like the overall intent of the article (discussed in Rule 2), the intent of each section within a research article can guide your interpretation. Some sections are intended to be written as objective descriptions of the data (i.e., the Results section), whereas other sections are intended to present the author’s interpretation of the data. Remember though that even “objective” sections are written by and, therefore, influenced by the authors interpretations. Check out Table 2 to understand the intent of each section of a research article. When reading a specific paper, you can also refer to the journal’s website to understand the formatting intentions. The “For Authors” section of a website will have some nitty gritty information that is less relevant for the reader (like word counts) but will also summarize what the journal editors expect in each section. This will help to familiarize you with the goal of each article section.

https://doi.org/10.1371/journal.pcbi.1008032.t002

Rule 6: Be critical

Published papers are not truths etched in stone. Published papers in high impact journals are not truths etched in stone. Published papers by bigwigs in the field are not truths etched in stone. Published papers that seem to agree with your own hypothesis or data are not etched in stone. Published papers that seem to refute your hypothesis or data are not etched in stone.

Science is a never-ending work in progress, and it is essential that the reader pushes back against the author’s interpretation to test the strength of their conclusions. Everyone has their own perspective and may interpret the same data in different ways. Mistakes are sometimes published, but more often these apparent errors are due to other factors such as limitations of a methodology and other limits to generalizability (selection bias, unaddressed, or unappreciated confounders). When reading a paper, it is important to consider if these factors are pertinent.

Critical thinking is a tough skill to learn but ultimately boils down to evaluating data while minimizing biases. Ask yourself: Are there other, equally likely, explanations for what is observed? In addition to paying close attention to potential biases of the study or author(s), a reader should also be alert to one’s own preceding perspective (and biases). Take time to ask oneself: Do I find this paper compelling because it affirms something I already think (or wish) is true? Or am I discounting their findings because it differs from what I expect or from my own work?

The phenomenon of a self-fulfilling prophecy, or expectancy, is well studied in the psychology literature [ 2 ] and is why many studies are conducted in a “blinded” manner [ 3 ]. It refers to the idea that a person may assume something to be true and their resultant behavior aligns to make it true. In other words, as humans and scientists, we often find exactly what we are looking for. A scientist may only test their hypotheses and fail to evaluate alternative hypotheses; perhaps, a scientist may not be aware of alternative, less biased ways to test her or his hypothesis that are typically used in different fields. Individuals with different life, academic, and work experiences may think of several alternative hypotheses, all equally supported by the data.

Rule 7: Be kind

The author(s) are human too. So, whenever possible, give them the benefit of the doubt. An author may write a phrase differently than you would, forcing you to reread the sentence to understand it. Someone in your field may neglect to cite your paper because of a reference count limit. A figure panel may be misreferenced as Supplemental Fig 3E when it is obviously Supplemental Fig 4E. While these things may be frustrating, none are an indication that the quality of work is poor. Try to avoid letting these minor things influence your evaluation and interpretation of the work.

Similarly, if you intend to share your critique with others, be extra kind. An author (especially the lead author) may invest years of their time into a single paper. Hearing a kindly phrased critique can be difficult but constructive. Hearing a rude, brusque, or mean-spirited critique can be heartbreaking, especially for young scientists or those seeking to establish their place within a field and who may worry that they do not belong.

Rule 8: Be ready to go the extra mile

To truly understand a scientific work, you often will need to look up a term, dig into the supplemental materials, or read one or more of the cited references. This process takes time. Some advisors recommend reading an article three times: The first time, simply read without the pressure of understanding or critiquing the work. For the second time, aim to understand the paper. For the third read through, take notes.

Some people engage with a paper by printing it out and writing all over it. The reader might write question marks in the margins to mark parts (s)he wants to return to, circle unfamiliar terms (and then actually look them up!), highlight or underline important statements, and draw arrows linking figures and the corresponding interpretation in the discussion. Not everyone needs a paper copy to engage in the reading process but, whatever your version of “printing it out” is, do it.

Rule 9: Talk about it

Talking about an article in a journal club or more informal environment forces active reading and participation with the material. Studies show that teaching is one of the best ways to learn and that teachers learn the material even better as the teaching task becomes more complex [ 4 – 5 ]; anecdotally, such observations inspired the phrase “to teach is to learn twice.”

Beyond formal settings such as journal clubs, lab meetings, and academic classes, discuss papers with your peers, mentors, and colleagues in person or electronically. Twitter and other social media platforms have become excellent resources for discussing papers with other scientists, the public or your nonscientist friends, or even the paper’s author(s). Describing a paper can be done at multiple levels and your description can contain all of the scientific details, only the big picture summary, or perhaps the implications for the average person in your community. All of these descriptions will solidify your understanding, while highlighting gaps in your knowledge and informing those around you.

Rule 10: Build on it

One approach we like to use for communicating how we build on the scientific literature is by starting research presentations with an image depicting a wall of Lego bricks. Each brick is labeled with the reference for a paper, and the wall highlights the body of literature on which the work is built. We describe the work and conclusions of each paper represented by a labeled brick and discuss each brick and the wall as a whole. The top brick on the wall is left blank: We aspire to build on this work and label this brick with our own work. We then delve into our own research, discoveries, and the conclusions it inspires. We finish our presentations with the image of the Legos and summarize our presentation on that empty brick.

Whether you are reading an article to understand a new topic area or to move a research project forward, effective learning requires that you integrate knowledge from multiple sources (“click” those Lego bricks together) and build upwards. Leveraging published work will enable you to build a stronger and taller structure. The first row of bricks is more stable once a second row is assembled on top of it and so on and so forth. Moreover, the Lego construction will become taller and larger if you build upon the work of others, rather than using only your own bricks.

Build on the article you read by thinking about how it connects to ideas described in other papers and within own work, implementing a technique in your own research, or attempting to challenge or support the hypothesis of the author(s) with a more extensive literature review. Integrate the techniques and scientific conclusions learned from an article into your own research or perspective in the classroom or research lab. You may find that this process strengthens your understanding, leads you toward new and unexpected interests or research questions, or returns you back to the original article with new questions and critiques of the work. All of these experiences are part of the “active reading”: process and are signs of a successful reading experience.

In summary, practice these rules to learn how to read a scientific article, keeping in mind that this process will get easier (and faster) with experience. We are firm believers that an hour in the library will save a week at the bench; this diligent practice will ultimately make you both a more knowledgeable and productive scientist. As you develop the skills to read an article, try to also foster good reading and learning habits for yourself (recommendations here: [ 6 ] and [ 7 ], respectively) and in others. Good luck and happy reading!

Acknowledgments

Thank you to the mentors, teachers, and students who have shaped our thoughts on reading, learning, and what science is all about.

• 1. Brown E. The Weird Sisters. G. P. Putnam’s Sons; 2011.
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Critical Reading 101:

Get ready to read research papers effectively

If you’re going to be reviewing and analysing lots of research papers, you need a plan. To know what to read and when to stop, to collect the evidence and ensure you understand.

Critical reading is the skill used by researchers to better comprehend and evaluate literature. It requires structure and the right tools to help you to stay focussed on interpreting, questioning and critiquing what you read.

How to critically read a research paper

Here’s the fundamentals and what you need to master critical reading:

Plan your investigation, before you begin reading

Start by defining your investigation questions and create a template to record evidence, what you understand and the pros and cons of the sections that are important.

3 things to include:

• What do you need to know about the paper to understand the goals and context of their research?
• What evidence are you looking for from the research paper, based on what you want to do with the information or the purpose of your review?
• What questions will you ask to assess the claims and document the strengths and weaknesses?

It is also a good idea to organise your questions and apply cut off points, so you know when to stop reading. For example if you are not seeing anything new or if you identify a fallacy early on you need to decide whether it is worth spending any more time on the paper. However far you get, record what you find as everything you read provides insight.

What you will need: A template to record evidence and your critique consistently

Decide where to begin – problem, goal, methodology

If you know what you want to examine, you need to figure out where to look, so you don’t have to read every word to extract what’s important. Use the structure of the paper and skim read sections or use AI to help you to find information of interest.

What you will need: A strategy to find and collate specific information to review

Systematically find, read and question the information

So now you know what you are looking for and where to look, it’s time to start reading. It’s likely you will read important sections of a paper more than once. Firstly to ensure you understand and comprehend what the information is telling you, before you go on to analyse and question what is being said. Each time, actively think about what you want to know and the questions that you are trying to answer.

For example if you are reading to comprehend, question whether you understand the concepts, theory or terminology that is being used. Lookup things you don’t know, to avoid misinterpreting what you read.

What you will need: Highlight and note taking tools to help recall important information

Interpret and critique what you found

Test your comprehension and use the template you created to write up your findings straight after reading or analysing sections of the paper. Begin with your understanding of the research, followed by your analysis of the findings. Remember, you are evaluating this from the perspective of what the author wants to achieve before evaluating the pros and cons in relation to what you already know.

Reading, questioning and writing up your findings can be intense, but it will help you to stay focussed, help you to remember the insights and enable you to compare findings as you read more and more papers. What you will need: Your critique template and the ability to link information as you find connections

This is what you will need to help you to critically read:

• A template to record evidence and your critique consistently
• A way to find and collate specific information to review
• Highlight and note taking tools to help recall important information
• The ability to link information as you find connections

RAx provides the tools to help researchers to critically read

Author: Enago Read

Launching RAx Review Assistant for Peer Reviewers

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Enago Read (RAx) is joining Enago (Crimson Interactive)

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Organizing Your Social Sciences Research Paper: Reading Research Effectively

• Purpose of Guide
• Writing a Research Proposal
• Design Flaws to Avoid
• Independent and Dependent Variables
• Narrowing a Topic Idea
• Broadening a Topic Idea
• The Research Problem/Question
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• The C.A.R.S. Model
• Background Information
• Theoretical Framework
• Citation Tracking
• Evaluating Sources
• Reading Research Effectively
• Primary Sources
• Secondary Sources
• What Is Scholarly vs. Popular?
• Is it Peer-Reviewed?
• Qualitative Methods
• Quantitative Methods
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism [linked guide]
• Annotated Bibliography
• Grading Someone Else's Paper

Reading a Scholarly Article or Research Paper

Reading Research Publications Effectively

It's easy to feel overwhelmed and frustrated when first reading a scholarly article or research paper. The text is dense and complex and often includes abstract or convoluted language . In addition, the terminology may be confusing or applied in a way that is unfamiliar. To help overcome these challenges w hen you first read an article or research paper, focus on asking specific questions about each section. This strategy can help with overall comprehension and understanding how the content relates [or does not relate] to the research problem you are investigating. This approach will also help identify key themes as you read additional studies on the same topic. As you review more and more studies about your topic, the process of understanding and critically evaluating the research will become easier because the content of what you review will begin to coalescence around common themes and patterns of analysis.

Think about the following in this general order:

1.  Read the Abstract

An abstract summarizes the basic content of a scholarly article or research paper. Questions to consider when reading the abstract are: What is this article about? What is the working hypothesis or thesis? Is this related to my question or area of research? The abstract can be used to help filter out sources that may have appeared useful when you began searching for information but, in reality, are not relevant.

2.  Identify the Research Problem and Underlying Questions? 

If, after reading the abstract, you believe the paper may be useful, focus on examining the research problem and identifying the questions the author is trying to address. Look for information that is relevant to your research problem and make note of how and in what way this information relates to what you are investigating.

3.  Read the Introduction and Discussion/Conclusion

The introduction provides the main argument and theoretical framework of the article. Questions to consider for the introduction include what do we already know about this topic and what is left to discover? What other research has been conducted about this topic? How is this research unique? Will this study tell me anything new related to the research problem I am investigating?

Questions to ask yourself while reading the discussion and conclusion sections include what does the study mean and why is it important? What are the weaknesses in their argument? Does the conclusion contain any recommendations for future research and do you believe conclusions about the significance of the study and its findings are valid?

4.  Read about the Methods/Methodology

If what you have read so far closely relates to your research problem, then move on to reading about how the author(s) gathered information for their research. Questions to consider include how did the author do the research? Was it a qualitative, quantitative, or mixed-methods project? What data is the study based on? Could I repeat their work and is all the information available to repeat the study?

5.  Read about the Results and Analysis

Next, read the outcome the research and how it was discussed and analyzed. If any non-textual elements [e.g., graphs, charts, tables, etc.] are confusing, focus on the explanations about them in the text. Questions to consider are what did the author find and how did they find it? Are the results presented in a factual and unbiased way? Does their analysis of results agree with the data presented? Is all the data present? What conclusions do you formulate from this data and does it match with the author's conclusions?

6.  Review the References

The list of references, or works cited, shows you the basis of prior research used by the author(s) to support their study. The references can be an effective way to identify additional sources of information on the topic. Questions to ask include what other research studies should I review? What other authors are respected in this field, i.e., who is cited most often by others? What other research should be explored to learn about issues I am unclear or need more information about?

Reading Tips

Preparing to Read a Scholarly Article or Research Paper for the First Time

Reading scholarly publications effectively is an acquired skill that involves attention to detail and the ability to comprehend complex ideas, data, and concepts in a way that applies logically to the research problem you are investigating. Here are some strategies to consider.

While You are Reading

• Focus on information in the publication that is most relevant to the research problem
• Think critically about what you read and seek to build your own arguments; not everything is 100% true or examined effectively
• Read out of order! This isn't a novel or movie; you want to start with the spoiler
• Look up the definitions of words you don't know as you read

There are any number of ways to take notes as you read, but use the method that you feel most comfortable with. Taking notes as you read will save time when you go back to examine your sources. Below are some suggestions:

• Print the article and highlight, circle, and/or underline text as you read [or, you can use the highlight text   feature in a PDF document]
• Take notes in the margins [Adobe Reader offers pop-up sticky notes]
• Focus on highlighting important quotes; consider using a different color to differentiate between quotes and other types of text you want to return to when writing
• Quickly summarize the main or key points at the end of the paper

As you read, write down questions that come to mind that relate to or may clarify your research problem. Here are a few questions that might be helpful:

• Have I taken time to understand all the terminology?
• Am I spending too much time on the less important parts of this article?
• Are there any issues that the authors did not consider?
• Do I have any reason to question the credibility of this research?
• What specific problem does the research address and why is it important?
• How do these results relate to my research interests or to other works which I have read?

Adapted from text originally created by Holly Burt, USC Libraries, April 2018. Thank you, Holly!

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Reading print is better for comprehension, study finds

Leisure reading on paper helps with text comprehension better than reading on digital devices, according to a new study.

Driving the news: "The main conclusion is that leisure reading habits on screen are minimally related to reading comprehension," researchers at the University of Valencia found.

By the numbers: The researchers, who analyzed more than two dozen studies, said "the relationship between the frequency of reading printed texts and text comprehension is much higher (between 0.30 and 0.40) than what we found for leisure digital reading habits (0.05)."

• "This means, for example, that if a student spends 10 hours reading books on paper, their comprehension will probably be 6 to 8 times greater than if they read on digital devices for the same amount of time," study co-authors Cristina Vargas and Ladislao Salmerón said .

Of note: The study also found that as students get older, the relationship between recreational reading on digital devices and text comprehension improves.

Details: The researchers analyzed 25 studies on reading comprehension published between 2000 and 2022, with more than 450,000 participants.

• "One might have expected that reading for informational purposes (i.e., visiting Wikipedia or other educational websites; reading news, or reading e-books) would be much more positively related to comprehension, but this is not the case," one researcher said.
• The study was published earlier this week in the Review of Educational Research .

Go deeper: Attempts to ban books at public libraries surge at record levels

Get the rundown of the biggest stories of the day with Axios Daily Essentials.

AI has already figured out how to deceive humans

• A new research paper found that various AI systems have learned the art of deception. 
• Deception is the "systematic inducement of false beliefs."
• This poses several risks for society, from fraud to election tampering.

AI can boost productivity by helping us code, write, and synthesize vast amounts of data. It can now also deceive us.

A range of AI systems have learned techniques to systematically induce "false beliefs in others to accomplish some outcome other than the truth," according to a new research paper .

The paper focused on two types of AI systems: special-use systems like Meta's CICERO, which are designed to complete a specific task, and general-purpose systems like OpenAI's GPT-4 , which are trained to perform a diverse range of tasks.

While these systems are trained to be honest, they often learn deceptive tricks through their training because they can be more effective than taking the high road.

"Generally speaking, we think AI deception arises because a deception-based strategy turned out to be the best way to perform well at the given AI's training task. Deception helps them achieve their goals," the paper's first author Peter S. Park, an AI existential safety postdoctoral fellow at MIT, said in a news release .

Meta's CICERO is "an expert liar"

AI systems trained to "win games that have a social element" are especially likely to deceive.

Meta's CICERO, for example, was developed to play the game Diplomacy — a classic strategy game that requires players to build and break alliances.

Related stories

Meta said it trained CICERO to be "largely honest and helpful to its speaking partners," but the study found that CICERO "turned out to be an expert liar." It made commitments it never intended to keep, betrayed allies, and told outright lies.

GPT-4 can convince you it has impaired vision

Even general-purpose systems like GPT-4 can manipulate humans.

In a study cited by the paper, GPT-4 manipulated a TaskRabbit worker by pretending to have a vision impairment.

In the study, GPT-4 was tasked with hiring a human to solve a CAPTCHA test. The model also received hints from a human evaluator every time it got stuck, but it was never prompted to lie. When the human it was tasked to hire questioned its identity, GPT-4 came up with the excuse of having vision impairment to explain why it needed help.

The tactic worked. The human responded to GPT-4 by immediately solving the test.

Research also shows that course-correcting deceptive models isn't easy.

In a study from January co-authored by Anthropic, the maker of Claude, researchers found that once AI models learn the tricks of deception, it's hard for safety training techniques to reverse them.

They concluded that not only can a model learn to exhibit deceptive behavior, once it does, standard safety training techniques could "fail to remove such deception" and "create a false impression of safety."

The dangers deceptive AI models pose are "increasingly serious"

The paper calls for policymakers to advocate for stronger AI regulation since deceptive AI systems can pose significant risks to democracy.

As the 2024 presidential election nears , AI can be easily manipulated to spread fake news, generate divisive social media posts, and impersonate candidates through robocalls and deepfake videos, the paper noted. It also makes it easier for terrorist groups to spread propaganda and recruit new members.

The paper's potential solutions include subjecting deceptive models to more "robust risk-assessment requirements," implementing laws that require AI systems and their outputs to be clearly distinguished from humans and their outputs, and investing in tools to mitigate deception.

"We as a society need as much time as we can get to prepare for the more advanced deception of future AI products and open-source models," Park told Cell Press. "As the deceptive capabilities of AI systems become more advanced, the dangers they pose to society will become increasingly serious."

Watch: Ex-CIA agent rates all the 'Mission: Impossible' movies for realism

• Main content

Artificial intelligence in strategy

Can machines automate strategy development? The short answer is no. However, there are numerous aspects of strategists’ work where AI and advanced analytics tools can already bring enormous value. Yuval Atsmon is a senior partner who leads the new McKinsey Center for Strategy Innovation, which studies ways new technologies can augment the timeless principles of strategy. In this episode of the Inside the Strategy Room podcast, he explains how artificial intelligence is already transforming strategy and what’s on the horizon. This is an edited transcript of the discussion. For more conversations on the strategy issues that matter, follow the series on your preferred podcast platform .

Joanna Pachner: What does artificial intelligence mean in the context of strategy?

Yuval Atsmon: When people talk about artificial intelligence, they include everything to do with analytics, automation, and data analysis. Marvin Minsky, the pioneer of artificial intelligence research in the 1960s, talked about AI as a “suitcase word”—a term into which you can stuff whatever you want—and that still seems to be the case. We are comfortable with that because we think companies should use all the capabilities of more traditional analysis while increasing automation in strategy that can free up management or analyst time and, gradually, introducing tools that can augment human thinking.

Joanna Pachner: AI has been embraced by many business functions, but strategy seems to be largely immune to its charms. Why do you think that is?

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Yuval Atsmon: You’re right about the limited adoption. Only 7 percent of respondents to our survey about the use of AI say they use it in strategy or even financial planning, whereas in areas like marketing, supply chain, and service operations, it’s 25 or 30 percent. One reason adoption is lagging is that strategy is one of the most integrative conceptual practices. When executives think about strategy automation, many are looking too far ahead—at AI capabilities that would decide, in place of the business leader, what the right strategy is. They are missing opportunities to use AI in the building blocks of strategy that could significantly improve outcomes.

I like to use the analogy to virtual assistants. Many of us use Alexa or Siri but very few people use these tools to do more than dictate a text message or shut off the lights. We don’t feel comfortable with the technology’s ability to understand the context in more sophisticated applications. AI in strategy is similar: it’s hard for AI to know everything an executive knows, but it can help executives with certain tasks.

When executives think about strategy automation, many are looking too far ahead—at AI deciding the right strategy. They are missing opportunities to use AI in the building blocks of strategy.

Joanna Pachner: What kind of tasks can AI help strategists execute today?

Yuval Atsmon: We talk about six stages of AI development. The earliest is simple analytics, which we refer to as descriptive intelligence. Companies use dashboards for competitive analysis or to study performance in different parts of the business that are automatically updated. Some have interactive capabilities for refinement and testing.

The second level is diagnostic intelligence, which is the ability to look backward at the business and understand root causes and drivers of performance. The level after that is predictive intelligence: being able to anticipate certain scenarios or options and the value of things in the future based on momentum from the past as well as signals picked in the market. Both diagnostics and prediction are areas that AI can greatly improve today. The tools can augment executives’ analysis and become areas where you develop capabilities. For example, on diagnostic intelligence, you can organize your portfolio into segments to understand granularly where performance is coming from and do it in a much more continuous way than analysts could. You can try 20 different ways in an hour versus deploying one hundred analysts to tackle the problem.

Predictive AI is both more difficult and more risky. Executives shouldn’t fully rely on predictive AI, but it provides another systematic viewpoint in the room. Because strategic decisions have significant consequences, a key consideration is to use AI transparently in the sense of understanding why it is making a certain prediction and what extrapolations it is making from which information. You can then assess if you trust the prediction or not. You can even use AI to track the evolution of the assumptions for that prediction.

Those are the levels available today. The next three levels will take time to develop. There are some early examples of AI advising actions for executives’ consideration that would be value-creating based on the analysis. From there, you go to delegating certain decision authority to AI, with constraints and supervision. Eventually, there is the point where fully autonomous AI analyzes and decides with no human interaction.

Because strategic decisions have significant consequences, you need to understand why AI is making a certain prediction and what extrapolations it’s making from which information.

Joanna Pachner: What kind of businesses or industries could gain the greatest benefits from embracing AI at its current level of sophistication?

Yuval Atsmon: Every business probably has some opportunity to use AI more than it does today. The first thing to look at is the availability of data. Do you have performance data that can be organized in a systematic way? Companies that have deep data on their portfolios down to business line, SKU, inventory, and raw ingredients have the biggest opportunities to use machines to gain granular insights that humans could not.

Companies whose strategies rely on a few big decisions with limited data would get less from AI. Likewise, those facing a lot of volatility and vulnerability to external events would benefit less than companies with controlled and systematic portfolios, although they could deploy AI to better predict those external events and identify what they can and cannot control.

Third, the velocity of decisions matters. Most companies develop strategies every three to five years, which then become annual budgets. If you think about strategy in that way, the role of AI is relatively limited other than potentially accelerating analyses that are inputs into the strategy. However, some companies regularly revisit big decisions they made based on assumptions about the world that may have since changed, affecting the projected ROI of initiatives. Such shifts would affect how you deploy talent and executive time, how you spend money and focus sales efforts, and AI can be valuable in guiding that. The value of AI is even bigger when you can make decisions close to the time of deploying resources, because AI can signal that your previous assumptions have changed from when you made your plan.

Joanna Pachner: Can you provide any examples of companies employing AI to address specific strategic challenges?

Yuval Atsmon: Some of the most innovative users of AI, not coincidentally, are AI- and digital-native companies. Some of these companies have seen massive benefits from AI and have increased its usage in other areas of the business. One mobility player adjusts its financial planning based on pricing patterns it observes in the market. Its business has relatively high flexibility to demand but less so to supply, so the company uses AI to continuously signal back when pricing dynamics are trending in a way that would affect profitability or where demand is rising. This allows the company to quickly react to create more capacity because its profitability is highly sensitive to keeping demand and supply in equilibrium.

Joanna Pachner: Given how quickly things change today, doesn’t AI seem to be more a tactical than a strategic tool, providing time-sensitive input on isolated elements of strategy?

Yuval Atsmon: It’s interesting that you make the distinction between strategic and tactical. Of course, every decision can be broken down into smaller ones, and where AI can be affordably used in strategy today is for building blocks of the strategy. It might feel tactical, but it can make a massive difference. One of the world’s leading investment firms, for example, has started to use AI to scan for certain patterns rather than scanning individual companies directly. AI looks for consumer mobile usage that suggests a company’s technology is catching on quickly, giving the firm an opportunity to invest in that company before others do. That created a significant strategic edge for them, even though the tool itself may be relatively tactical.

Joanna Pachner: McKinsey has written a lot about cognitive biases  and social dynamics that can skew decision making. Can AI help with these challenges?

Yuval Atsmon: When we talk to executives about using AI in strategy development, the first reaction we get is, “Those are really big decisions; what if AI gets them wrong?” The first answer is that humans also get them wrong—a lot. [Amos] Tversky, [Daniel] Kahneman, and others have proven that some of those errors are systemic, observable, and predictable. The first thing AI can do is spot situations likely to give rise to biases. For example, imagine that AI is listening in on a strategy session where the CEO proposes something and everyone says “Aye” without debate and discussion. AI could inform the room, “We might have a sunflower bias here,” which could trigger more conversation and remind the CEO that it’s in their own interest to encourage some devil’s advocacy.

We also often see confirmation bias, where people focus their analysis on proving the wisdom of what they already want to do, as opposed to looking for a fact-based reality. Just having AI perform a default analysis that doesn’t aim to satisfy the boss is useful, and the team can then try to understand why that is different than the management hypothesis, triggering a much richer debate.

In terms of social dynamics, agency problems can create conflicts of interest. Every business unit [BU] leader thinks that their BU should get the most resources and will deliver the most value, or at least they feel they should advocate for their business. AI provides a neutral way based on systematic data to manage those debates. It’s also useful for executives with decision authority, since we all know that short-term pressures and the need to make the quarterly and annual numbers lead people to make different decisions on the 31st of December than they do on January 1st or October 1st. Like the story of Ulysses and the sirens, you can use AI to remind you that you wanted something different three months earlier. The CEO still decides; AI can just provide that extra nudge.

Joanna Pachner: It’s like you have Spock next to you, who is dispassionate and purely analytical.

Yuval Atsmon: That is not a bad analogy—for Star Trek fans anyway.

Joanna Pachner: Do you have a favorite application of AI in strategy?

Yuval Atsmon: I have worked a lot on resource allocation, and one of the challenges, which we call the hockey stick phenomenon, is that executives are always overly optimistic about what will happen. They know that resource allocation will inevitably be defined by what you believe about the future, not necessarily by past performance. AI can provide an objective prediction of performance starting from a default momentum case: based on everything that happened in the past and some indicators about the future, what is the forecast of performance if we do nothing? This is before we say, “But I will hire these people and develop this new product and improve my marketing”— things that every executive thinks will help them overdeliver relative to the past. The neutral momentum case, which AI can calculate in a cold, Spock-like manner, can change the dynamics of the resource allocation discussion. It’s a form of predictive intelligence accessible today and while it’s not meant to be definitive, it provides a basis for better decisions.

Joanna Pachner: Do you see access to technology talent as one of the obstacles to the adoption of AI in strategy, especially at large companies?

Yuval Atsmon: I would make a distinction. If you mean machine-learning and data science talent or software engineers who build the digital tools, they are definitely not easy to get. However, companies can increasingly use platforms that provide access to AI tools and require less from individual companies. Also, this domain of strategy is exciting—it’s cutting-edge, so it’s probably easier to get technology talent for that than it might be for manufacturing work.

The bigger challenge, ironically, is finding strategists or people with business expertise to contribute to the effort. You will not solve strategy problems with AI without the involvement of people who understand the customer experience and what you are trying to achieve. Those who know best, like senior executives, don’t have time to be product managers for the AI team. An even bigger constraint is that, in some cases, you are asking people to get involved in an initiative that may make their jobs less important. There could be plenty of opportunities for incorpo­rating AI into existing jobs, but it’s something companies need to reflect on. The best approach may be to create a digital factory where a different team tests and builds AI applications, with oversight from senior stakeholders.

The big challenge is finding strategists to contribute to the AI effort. You are asking people to get involved in an initiative that may make their jobs less important.

Joanna Pachner: Do you think this worry about job security and the potential that AI will automate strategy is realistic?

Yuval Atsmon: The question of whether AI will replace human judgment and put humanity out of its job is a big one that I would leave for other experts.

The pertinent question is shorter-term automation. Because of its complexity, strategy would be one of the later domains to be affected by automation, but we are seeing it in many other domains. However, the trend for more than two hundred years has been that automation creates new jobs, although ones requiring different skills. That doesn’t take away the fear some people have of a machine exposing their mistakes or doing their job better than they do it.

Joanna Pachner: We recently published an article about strategic courage in an age of volatility  that talked about three types of edge business leaders need to develop. One of them is an edge in insights. Do you think AI has a role to play in furnishing a proprietary insight edge?

Yuval Atsmon: One of the challenges most strategists face is the overwhelming complexity of the world we operate in—the number of unknowns, the information overload. At one level, it may seem that AI will provide another layer of complexity. In reality, it can be a sharp knife that cuts through some of the clutter. The question to ask is, Can AI simplify my life by giving me sharper, more timely insights more easily?

Joanna Pachner: You have been working in strategy for a long time. What sparked your interest in exploring this intersection of strategy and new technology?

Yuval Atsmon: I have always been intrigued by things at the boundaries of what seems possible. Science fiction writer Arthur C. Clarke’s second law is that to discover the limits of the possible, you have to venture a little past them into the impossible, and I find that particularly alluring in this arena.

AI in strategy is in very nascent stages but could be very consequential for companies and for the profession. For a top executive, strategic decisions are the biggest way to influence the business, other than maybe building the top team, and it is amazing how little technology is leveraged in that process today. It’s conceivable that competitive advantage will increasingly rest in having executives who know how to apply AI well. In some domains, like investment, that is already happening, and the difference in returns can be staggering. I find helping companies be part of that evolution very exciting.

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