Tag: AI in scholarly publishing

AI in Scholarly Publishing: Finding the Sweet Spot Between Innovation and Integrity

Posted on by Ashutosh Ghildiyal

A summary of [“Artificial intelligence in publishing: Navigating the balance between assistance and originality” by Ashutosh Ghildiyal, published in Editing Practice, December 2024.]

In a thought-provoking perspective piece, Ashutosh Ghildiyal, Vice President of Strategy and Growth at Integra, delves into one of academic publishing’s most pressing challenges: the integration of artificial intelligence while preserving the essence of scholarly work.

As AI tools become increasingly sophisticated, the publishing industry faces a crucial balancing act. While these tools offer promising solutions for common challenges like language barriers and structural requirements, their unchecked use could potentially undermine the very foundation of academic literature.

The Heart of Academic Writing: Human Insight

Ghildiyal emphasizes a fundamental truth: genuine scholarly work must stem from researchers’ direct observations and experiences. Words without lived experience lack depth and meaning. While an idea doesn’t need to be entirely unique to be original, it should reflect the writer’s unique perspective – something that AI alone cannot provide.

Where AI Shines (And Where It Shouldn’t)

The article outlines several appropriate applications for AI in scholarly publishing:

  • As an editing tool: Particularly valuable for non-native English speakers and those who need help with structure and clarity
  • As a thought partner: Useful for brainstorming and dialogue, while ensuring human judgment remains central
  • In technical assessment: Helping with plagiarism detection, formatting checks, and reviewer selection

However, Ghildiyal warns against letting AI replace human judgment in critical areas like peer review and editorial decision-making. The core functions that require nuanced understanding, ethical considerations, and contextual awareness must remain firmly in human hands.

A Framework for Thoughtful Implementation

The article suggests a measured approach to AI integration:

  • Begin with comprehensive workflow analysis
  • Focus first on time-consuming tasks that require minimal creativity
  • Maintain robust human oversight
  • Establish clear metrics for success
  • Roll out gradually, starting with low-risk, high-volume tasks
The Path Forward

The future of scholarly publishing lies not in choosing between human expertise and AI capabilities, but in finding ways to leverage both effectively. Success will come from thoughtful collaboration that preserves the integrity of academic work while embracing innovation’s benefits.

As Ghildiyal notes, “We should use AI to make our work better but not at the expense of our own unique thinking, insights, and work.” The goal isn’t to resist technological progress but to ensure it enhances rather than diminishes the quality and authenticity of scholarly publishing.

This balanced perspective offers valuable insights for publishers, researchers, and academic institutions navigating the AI revolution. It reminds us that while AI can be an invaluable tool, the heart of scholarly work remains fundamentally human.

Take the Next Step

At Integra, we celebrate the invaluable contributions of editorial professionals and recognize their essential role in advancing the scholarly community. Our advanced tools empower them to continue playing a crucial part in advancing human knowledge through research. As a trusted partner, we offer human expert-led, technology-assisted solutions tailored for editorial workflows, research integrity verification, and peer review management.

Contact us to explore how we can help you succeed!

About the Author

Ashutosh Ghildiyal is the Vice President of Strategy and Growth at Integra, a leading global provider of publishing services and technology. With over 18 years of experience in scholarly publishing, he champions innovation through AI-driven solutions while leading strategic growth initiatives. A recognized thought leader in scholarly communication, he works closely with scholarly societies, university presses, and educational publishers worldwide to advance transformative solutions in academic publishing.

Use of AI in Scholarly Publishing: Striking the Balance Between Innovation and Integrity

Posted on by Prakash Nagarajan

AI is taking an increasingly prominent role in scholarly publishing, offering the promise of streamlining editorial processes, improving efficiency, and reducing human error. However, as we embrace AI’s potential, the critical question remains: Can we use AI without compromising the core values of research integrity? Are we prepared to trust AI’s judgments over human expertise? Let’s take a closer look at how AI can be ethically applied in scholarly publishing—enhancing rather than overshadowing human contributions.

1. Pre-Editing: Assisting, Not Replacing Authorial Voice

AI-driven language editing tools can be invaluable, particularly for authors whose first language is not English. These tools can help refine grammar and clarity, ensuring that the author’s ideas are conveyed effectively. However, there is a risk of allowing AI to replace the authentic voice of the author rather than simply enhancing it. AI should be seen as a tool for improvement, not a substitute for the author’s unique perspective. The rise of AI-generated articles raises ethical concerns, blurring the line between enhancement and authorship. With the increasing threat of “papermills”—which sell fake authorship and fabricated research—AI could be exploited to produce work that lacks originality. The challenge is to maintain the human essence of scholarly writing while leveraging AI for efficiency.

2. Technical Assessment: Complementing Human Review, Not Replacing It

AI can significantly aid the technical assessment of manuscripts by quickly identifying missing metadata, formatting issues, or incomplete sections. This can reduce delays in the editorial process and ensure a smoother transition to peer review. However, while AI can streamline these preliminary checks, it cannot replace human review entirely. Human editors must still ensure that editorial standards are met and that no critical nuances are overlooked. AI should assist, not replace, the essential role of human oversight in maintaining quality and consistency.

3. Editorial Checks: Supporting Plagiarism and Image Manipulation Detection

AI tools that detect plagiarism, self-citations, or image manipulation are becoming a cornerstone of editorial checks. These tools are crucial for maintaining the integrity of research, but they raise an important question: Can we rely on AI alone for these sensitive checks, or should human expertise still play a central role? AI can alert editors to potential ethical violations, but human judgment is essential to interpret context, intent, and the subtleties of a case. Experienced editors should be the ones to make final decisions, ensuring fairness and accuracy in handling these red flags.

4. Reviewer Selection: Enhancing Diversity While Maintaining Transparency

AI can help identify qualified and diverse reviewers by analyzing manuscripts and generating relevant keywords. This approach broadens the pool of potential reviewers and can reduce biases that are common in traditional reviewer selection methods. While this is a step forward, it’s important that AI is not relied upon to make reviewer selections autonomously. Human editors must retain the final say to ensure transparency and prevent over-reliance on automated decisions. The goal should be to use AI to complement human judgment, not replace it.

5. Research Evaluation: AI as a Supplement, Not a Substitute

AI can assist in the peer review process by providing preliminary evaluations or flagging areas that require closer attention. While this can streamline the process, AI can never fully replace the nuanced understanding and expertise that human reviewers provide. The role of AI should be to support, not supplant, the critical analysis that human reviewers contribute. Similarly, using AI to generate responses to reviewer comments may seem tempting, but this risks losing the depth and insight that only human experts can provide. Human judgment should always remain at the core of manuscript evaluation.

6. User Identification: Ensuring Integrity and Transparency

User identification is a critical aspect of maintaining research integrity. AI can play a vital role in detecting duplicate accounts, spoofed emails, and undisclosed conflicts of interest between authors and reviewers. However, when using AI for identity verification, we must ensure that fairness, privacy, and transparency are upheld. It’s essential that AI is used to support—rather than replace—traditional identity checks, ensuring a robust and transparent verification process.

7. AI for Data Integrity: Verifying, Not Replacing Human Expertise

AI shows great potential in verifying the integrity of data within research articles, especially when working with large datasets. By identifying outliers, inconsistencies, or errors in data visualization, AI can assist editors in maintaining accuracy. However, AI should never be the sole arbiter of data accuracy. While it can act as a valuable safety net, human experts must retain oversight to interpret the data’s context and ensure its validity. AI’s role here is to complement human expertise, not replace it.

8. Automating Metadata and Reference Management: Time-Saving, But with Caution

Metadata and reference management are crucial for indexing and discovery, but they are time-consuming tasks. AI can automate much of this work, making it easier for authors and editors to format references and ensure proper indexing. However, relying on AI to manage metadata and references carries the risk of errors. A poorly formatted reference or inaccurate metadata can impact an article’s accessibility. Therefore, while AI can save time, editorial oversight remains necessary to ensure accuracy and consistency.

9. Encouraging Transparency in AI Usage

Transparency in how AI is used in scholarly publishing is essential for maintaining trust. Journals should be open about the role AI plays in manuscript evaluation, ensuring that stakeholders understand its limitations and contributions. Clear guidelines on AI usage should be established, so that authors, editors, and reviewers are aware of the tools in use and how they affect the publishing process. This openness will help manage expectations and ensure that AI is used ethically and responsibly.

Final Thoughts

AI has the potential to significantly enhance research integrity in scholarly publishing, but only if it is used thoughtfully and ethically. The key lies in how we apply AI: as a tool to support and complement human expertise, not as a replacement for it. By establishing clear guidelines, maintaining transparency, and ensuring human oversight, we can use AI as a force for good—one that supports the growth and development of knowledge while upholding the ethical standards that define scholarly publishing.

Call to Action

The scholarly publishing community must work together to establish ethical frameworks and guidelines for AI usage. Let’s ensure that AI enhances, rather than undermines, the integrity of research. By being transparent about how AI is applied and retaining human oversight, we can foster an environment where innovation and integrity coexist, ultimately benefiting the advancement of knowledge.

About the author:

Abdul Hakkim is the Senior Manager, Peer Review Services at Integra, a leader in scholarly publishing services. With extensive experience in setting up teams and ensuring the highest standards of quality, Hakkim excels at meeting publisher requirements and driving operational excellence. His expertise spans across supporting research integrity, enhancing manuscript screening, and optimizing peer review processes. Hakkim is dedicated to improving efficiency and fostering innovation in the publishing industry, shaping its future through leadership and strategic growth.

Leveraging AI to Combat Reviewer Fatigue

Posted on by Prakash Nagarajan

Peer review is the cornerstone of academic integrity, ensuring that published research meets the highest standards of quality and reliability. However, the peer review process is under increasing strain due to a surge in manuscript submissions. This has led to widespread reviewer fatigue, threatening the quality, timeliness, and credibility of the entire academic publishing process.

Understanding Reviewer Fatigue

Reviewer fatigue, often referred to as burnout, occurs when peer reviewers—typically academics or researchers—become overwhelmed by the growing volume of manuscripts they are asked to review. This strain can lead to delays, lower-quality reviews, and a decreased willingness to participate in the peer review process.

Key Factors Contributing to Reviewer Fatigue:

  1. High Volume of Submissions: The global increase in research output has led to a surge in manuscript submissions, placing a heavier burden on reviewers.
  2. Time Constraints: Academics often juggle multiple professional responsibilities, leaving little time for thorough reviews.
  3. Lack of Incentives: Peer reviewing is generally a voluntary activity with limited direct rewards or recognition.
  4. Repeated Requests: A small pool of expert reviewers is frequently called upon, exacerbating the burden.
  5. Complexity of Research: The increasing specialization and complexity of research make reviews more time-consuming.

The Impact of Reviewer Fatigue

Reviewer fatigue has several negative consequences for the scholarly publishing ecosystem:

  • Decreased Review Quality: Overburdened reviewers may provide rushed or superficial assessments, compromising the quality of the peer review process.
  • Delayed Publication Timelines: A shortage of willing reviewers leads to longer review cycles, delaying the dissemination of research.
  • Reduced Reviewer Pool: As fatigue grows, fewer scholars are willing to engage in peer review, creating a vicious cycle.
  • Damage to Academic Reputation: The credibility of the peer review system is jeopardized, potentially diminishing trust in published research.

An article published by Cambridge University Press titled “Reviewer Fatigue? Why Scholars Decline to Review Their Peers’ Work” investigates reviewer fatigue among political science scholars, shedding light on why scholars decline to review manuscripts. The findings show the many reasons beyond just too many review requests:

  • Reviewer Fatigue: Overload of review requests accounts for 14.1% of declines (or 19.7% of those who provided a reason).
  • Busy Professional and Personal Lives: A larger proportion of scholars cited being “too busy,” making up 24.8% of declines overall (or 34.6% of those who provided a reason).
  • Acceptance Rates: Despite concerns about fatigue, 82.8% of scholars responded to review requests, with 60% accepting and completing their assignments, indicating a high willingness to contribute when time allows.

Strategies for Scholarly Publishers to Alleviate Reviewer Fatigue

Scholarly publishers play a crucial role in mitigating reviewer fatigue and fostering a sustainable peer review ecosystem. Here are some effective strategies:

  1. Recognition and Incentives:
    • Tangible Rewards: Offer certificates, discounts on publication fees, or access to journal content.
    • Public Recognition: Acknowledge reviewers’ contributions in the journal or on its website.
  1. Streamlined Review Processes:
    • Efficient Manuscript Management Systems: Implement systems that reduce administrative burdens on reviewers.
    • Clear and Concise Review Forms: Simplify the review process to make it more straightforward and less time-consuming.
  1. Reviewer Training and Support:
    • Training Programs: Offer training to help reviewers understand expectations and conduct high-quality reviews efficiently.
    • Resources and Guidelines: Provide access to guidelines and other helpful materials.
  1. Broadening the Reviewer Pool:
    • Recruit New Reviewers: Actively recruit new reviewers, including early-career researchers eager to gain experience.
    • Diversify the Pool: Include international reviewers and those from underrepresented disciplines.
  1. Flexible Deadlines:
    • Flexible Timelines: Allow more flexible timelines for completing reviews, especially for complex or lengthy manuscripts.
    • Extensions: Provide extensions when needed, recognizing that reviewers have other commitments.
  1. Reduced Review Load:
    • Limit Review Requests: Restrict the number of manuscripts a reviewer is asked to review within a certain timeframe.
    • Rotation System: Implement a rotation system to distribute the workload more evenly.
  1. Automated Tools:
    • AI and Machine Learning Tools: Use tools to assist with initial manuscript screening and identify potential reviewers.
    • Plagiarism and Formatting Tools: Implement tools to check for plagiarism or basic formatting issues, reducing the burden on human reviewers.
  1. Reviewer Support:
    • Mentorship Programs: Offer training and support for new reviewers.
    • Peer Support Networks: Create opportunities for reviewers to connect and share experiences.

Alleviating Reviewer Burnout with AI: Revolutionizing the Peer Review Process

Reviewer burnout is a growing concern in the scholarly publishing industry, as the increasing volume of manuscript submissions and the demand for rapid publication timelines place significant pressure on reviewers. To address this challenge, AI tools are being integrated into the peer review process to streamline various tasks, reduce workload, and ultimately alleviate reviewer burnout. Here’s how AI is transforming the review process:

  • Automated Review Summarization: AI can generate concise summaries of peer review reports, providing a clear and efficient overview of key feedback. This allows editors to make informed decisions more quickly, freeing up time for reviewers to focus on more complex evaluations.
  • AI-Based Translation for Accessibility and Inclusivity: AI-powered translation tools support non-native English-speaking reviewers and authors by translating manuscripts and reviews with high accuracy, enhancing the diversity and reach of the peer review process.
  • AI-Based Fact-Checking for Accuracy: AI tools assist reviewers by automatically verifying facts, data, and references in manuscripts. This reduces the cognitive load on reviewers and enhances the reliability of the review process.
  • Reviewer Matching Optimization: AI optimizes the assignment of manuscripts to reviewers by analyzing reviewer profiles, expertise, and workloads. This ensures a fair distribution of reviews and improves the quality and relevance of peer reviews.
  • AI-Powered Peer Review Reports: AI-generated peer review reports provide an additional layer of analysis and insight, helping to identify potential issues that may have been overlooked by human reviewers, leading to higher-quality publications.

The Impact of AI on Reviewer Well-Being

The implementation of AI tools in the peer review process has the potential to significantly improve the well-being of reviewers by automating routine tasks, enhancing accuracy, and optimizing workload distribution. As a result, reviewers can focus on the more intellectually rewarding aspects of the review process, reducing the risk of burnout and maintaining high standards of scholarly evaluation.

Supporting Editorial Teams with AI

AI also enhances the efficiency and effectiveness of editorial teams:

  1. AI-Driven Editorial Support: Platforms like Author Pilot provide advanced language and technical assessments, generate quality reports, and automate manuscript triage.
  2. Automated Editing: AI-powered editing tools, such as Wyse, ensure manuscripts are clear, accurate, and adhere to editorial standards.
  3. Data-Driven Reviewer Recommendations: AI optimizes reviewer matching by analyzing expertise, past performance, and availability.
  4. Research Integrity Checks: AI tools detect academic misconduct by analyzing textual similarities, citation patterns, and other indicators.
  5. Automated Peer Review Summarization: AI generates concise summaries of peer reviews, helping editors make informed decisions and providing clearer feedback to authors.

AI-Powered Peer Review Reports: Enhancing the Review Process with AI Agents

The peer review process is crucial for maintaining the quality and integrity of scholarly research. However, with the increasing volume of manuscript submissions and the growing complexity of research, traditional peer review methods face significant challenges. Platforms like Quixl have developed AI agents capable of generating peer review reports that complement human peer reviews, creating a more efficient and robust review process.

Integrating AI with Human Peer Review: A Balanced Approach

AI-generated peer review reports offer several advantages when used alongside traditional human reviews:

  1. Speed and Efficiency: AI agents can process and analyze manuscripts rapidly, generating preliminary review reports in a fraction of the time it takes human reviewers. This can significantly reduce the time to publication, particularly for high-volume journals.
  2. Consistency and Objectivity: AI agents provide consistent and objective evaluations based on predefined criteria, ensuring that all manuscripts are assessed against the same standards.
  3. Identifying Key Areas of Focus: AI agents can highlight specific areas of a manuscript that may require closer scrutiny by human reviewers, such as statistical analysis or data integrity.
  4. Augmenting Reviewer Expertise: AI-generated reports can provide additional insights, especially in areas where human reviewers may lack specific expertise.
  5. Reducing Reviewer Fatigue: By handling routine or technical aspects of the review process, AI agents alleviate the burden on human reviewers, allowing them to focus on more nuanced elements of the manuscript.

The Future of Peer Review: Human-AI Collaboration

The integration of AI-generated peer review reports represents a significant step forward in the evolution of scholarly publishing. By combining the strengths of AI—speed, objectivity, and data processing—with the irreplaceable expertise and judgment of human reviewers, the peer review process can become more efficient, rigorous, and fair.

As platforms like Quixl continue to refine their AI agents, the potential for AI to play a supportive role in peer review will only grow. By embracing this technology, publishers and editors can enhance the quality of peer reviews, accelerate publication timelines, and ultimately improve the dissemination of scholarly knowledge.

Enhancing Scholarly Publishing with AI

AI-powered peer review reports and other AI-assisted tools, when used in conjunction with traditional human reviews, have the potential to revolutionize the peer review process. These tools offer speed, consistency, and insights that can complement and enhance the work of human reviewers. By integrating AI into the peer review process, scholarly publishing can address the challenges of increasing manuscript submissions and the rising demands on reviewers. The future of peer review lies in the collaborative efforts of humans and AI, working together to ensure the integrity and quality of academic research.

As AI technology continues to evolve, its role in supporting and enhancing the peer review process will only grow, offering new possibilities for efficiency, accuracy, and fairness in scholarly publishing. Embracing AI as a tool for peer review is not just a solution to the challenges faced by the publishing industry today—it is a step toward a more resilient and future-proof system of academic evaluation.

At Integra, we celebrate the contributions of editorial professionals and recognize the invaluable service they provide to the scholarly community. We empower them with our advanced tools, acknowledging their crucial role in curating and disseminating research that drives the advancement of human knowledge. As a trusted partner, we deliver human-led, technology-assisted solutions tailored for editorial, research integrity, and peer review management.

Integra is committed to delivering exceptional quality, efficiency, and innovation to our clients. Let us help you streamline your publishing workflows and achieve your goals.

Are you looking to explore how AI can alleviate reviewer fatigue? Integra can help—let’s talk!

Author Bio

Ashutosh Ghildiyal is the Vice President of Growth and Strategy at Integra, a leading global provider of publishing services and technology. With over 18 years of experience in scholarly publishing, he is adept at driving sustainable growth and expanding the company’s global presence. Ashutosh is deeply committed to advancing the scholarly publishing community and shaping the future of the industry.

Navigating New Frontiers with AI: Research Integrity in Scholarly Publishing

Posted on by Prakash Nagarajan

The widespread adoption of artificial intelligence (AI) represents a pivotal moment in global history. Often described as a transformative ‘superpower,’ generative AI is accessible to anyone with a computer and internet connection. Its influence is already evident across various industries, signaling the onset of far-reaching and disruptive changes yet to be fully realized.

AI, a remarkable product of decades of scholarly research and development, stands as a paradox in the realm of scholarly communication. This field, pivotal in broadcasting progress across various research areas, now faces the dual impacts of AI. This article aims to examine AI’s role in scholarly communication, with a special focus on journal article publishing lifecycle, and to contemplate its future implications for all involved stakeholders.

Journal Publication Growth

A basic analysis using the Dimensions app reveals a significant increase in the number of journal articles published from 2012 to 2022. There was an 89% growth over the past decade, with the number of articles rising from 2.8 million in 2012 to 5.3 million in 2022. In this period, the industry also experienced notable growth in the number of open access journals, a model also adopted by commercial publishers too. These journals were a major contributor in providing platforms for disseminating research to a broader audience.

The surge in publication numbers, coupled with disruptions to traditional business models and increasing publishing costs, has compelled publishers to reevaluate their operational strategies. They have swiftly embraced various technological enablers throughout the publishing lifecycle. As digital content consumption has skyrocketed over the years, publishers have had to revise their workflows. The shift from print-only to online-ahead-of-print, and now to a predominantly online-only model for article publication, has become the norm.

AI in Journal Publishing Workflows

Journal publishers in the academic publishing sector were early adopters of technology, enhancing their publishing workflows significantly. This included using markup languages to partly automate content production and to aid in archival and retrieval. With AI-enabled systems and generative AI, today, we stand at a pivotal juncture with the potential to revolutionize the industry.

Disruptive innovation, a hallmark of any industry, opens up vast opportunities to delve into unexplored areas and confront challenges. This is particularly true for scholarly communication and journal publishing, which navigate their unique challenges in this unfamiliar landscape. At the same time, these fields are harnessing the potential that AI technologies offer.

AI-enablement has been a welcome change in the journal publishing domain which has been trying to accommodate to emerging business models and changing market demands. In an industry where speed of publication of journal has been continuously reducing, publishers have been quick to adopt technology solutions to manage both upstream and downstream publishing activities. There are many AI-enabled solutions for every stakeholder involved in the entire scientific publication life-cycle.

Scientific

Safeguarding Research Communication Integrity in the Age of AI

The advent of social media and widespread smartphone use has led to a staggering increase in the volume of content published and consumed every minute. Journal publishing is also experiencing a surge in content, overwhelming the niche audiences it caters to. This content overload poses significant challenges for two crucial players in the scientific publication lifecycle: researchers and practitioners. The repercussions are profound, affecting individual careers and society at large, as funding is squandered on unrealized benefits. We have many examples on predatory journals, papermills and unethical practices in the academia that pose a significant damage.

Regardless of the publishing model, the rise of AI has highlighted the essential role of journal publishers in the ecosystem, particularly in curating valuable information through meticulous peer review. While AI tools may boost content production, they also risk increasing the volume of low-quality content creating a strain in the research publication pipeline. This surge in content necessitates a more rigorous editorial review process, which is both costly and labor-intensive. The entire ecosystem must collaborate and embark on a journey of discovery to address the challenges and potential short- or long-term threats that are emerging as we begin to uncover the full potential of AI.

Future with AI in Scholarly Communication

This exploration into AI within scholarly publishing not only highlights technological advancements but also raises critical questions about ethical considerations. It underlines the need for a balance between innovation and responsibility, urging the academic community to lead with foresight and ethical rigor. The article ‘AI & Machine Learning in Scholarly Publishing: Services, Data, and Ethics’ offers an interesting starting point on tackling these challenges and ensuring the integrity of scholarly communication. The path forward remains uncharted, reflecting the true essence of scholarship in this domain. It emphasizes the importance of finding solutions to issues affecting society at large, underscoring the role of academia in navigating unexplored territories and contributing to global knowledge.