Technological developments, particularly in the form of artificial intelligence (AI) tools and processes, are rapidly reshaping the academic publishing industry. This is creating many opportunities, but also challenges, for publishers.

Given that MDPI is at the forefront of open science, it is therefore leading the way in innovative solutions to strengthen its editorial process.

Ethicality was developed in-house by MDPI’s Technology Innovation team to ensure quality and resolve ethical concerns before publication, comprising a suite of tools and human-in-the-loop validation. It represents a key example of how leveraging new technologies helps in maintaining research integrity.

In this article, we explore Ethicality and why it is an important tool in the present scholarly publishing landscape, speaking to Dr Miloš Čučulović, Head of Technology Innovation, and Dr Enric Sayas, Product Owner of Ethicality, throughout.

Changing technological landscape

MDPI regularly attends various conferences, such as the Society for Scholarly Publishing (SSP) in Baltimore in 2025. Earlier in 2026, MDPI presented Ethicality at the Researcher to Reader (R2R) conference in London in February 2026.

After attending, Dr Miloš Čučulović reflects on the changes the publishing industry is experiencing:

One of the takeaways from both R2R and SSP is that the publishing industry is going through a fundamental shift driven by scale and technology. The number of submissions continues to grow, while expectations around speed, transparency, and quality are higher than ever. At the same time, the rise of GenAI is creating both opportunities and new risks, from improving workflows to introducing challenges such as synthetic content, manipulated data, or questionable authorship practices.

This creates a tension: how do we maintain rigorous research integrity while keeping the publishing process efficient and scalable? Many of those challenges were discussed across the community, with publishers, institutions, and researchers.

What is becoming clear is that traditional, manual processes are no longer sufficient. The industry needs to move from reactive approaches, resolving issues after publication, to proactive systems that can support editors earlier in the workflow.

AI, when used responsibly, can act as a set of guardrails rather than a replacement for human judgment. The future lies in combining automation with strong editorial oversight to ensure consistency, transparency, and trust at scale.

What is Ethicality?

Ethicality serves as an end-to-end research integrity ecosystem, providing internal teams with everything they need to assess and safeguard a manuscript’s ethical compliance.

It was developed alongside the Editorial and Research Integrity teams, enabling the developers to gather examples to analyse and build detection tools.

How Ethicality was developed

Dr Miloš Čučulović outlines the nature of this collaboration:

Ethicality was designed from the collaborative effort between technology, editorial, and research integrity teams. This collaboration is essential because research integrity is not purely a technical problem; it requires deep domain expertise and clear editorial standards.

The Editorial and Research Integrity teams played a central role in defining the scope of the system: types of ethical concerns, how those should be evaluated, and where human validation is required. In many cases, they helped translate real-world editorial challenges into structured rules, signals, and workflows that could be supported by AI.

At the same time, we were careful to ensure that Ethicality does not replace editorial decision-making. Instead, it acts as a support layer integrated into the editorial workflow, providing signals and recommendations that are always reviewed by editors and integrity specialists. This human-in-the-loop approach is a must.

Ultimately, this collaboration allows us to combine the scalability of AI with the expertise and judgment of our editorial teams. It ensures that integrity is maintained not only through detection but through consistent, transparent, and well-informed decision-making across MDPI’s publishing process.

Integration into MDPI’s editorial process

Ethicality is directly integrated into the editorial process, therefore strengthening MDPI’s approach to proactive correction. This enables seamless detection of integrity risks at submission and as it advances through each processing step, checking for changes and updates at each stage.

MDPI editorial process with Ethicality integration, which shows how the tool is used by internal staff who can also share information with Academic Editors and reviewers.

How Ethicality works

Firstly, the text is parsed into different parts, i.e., title, abstract, authors, body, etc. Then, it goes through a series of checks conducted by several AI tools that look for signals of potential ethical malpractice. These include the following:

• Paper mills
• AI-generated content, such as fake papers and reviews
• Duplicate submissions
• Citation manipulation
• Image manipulation
• Author manipulation
• Plagiarism

These are flagged using AI and investigated by trained in-house staff, ensuring that human expertise is always at the core.

Why Ethicality is necessary in workflows

Dr Enric Sayas, Product Owner of Ethicality, explains why AI solutions are necessary in workflows:

In my opinion, integrating AI into scholarly publishing workflows has become a necessity rather than an option. This transition is driven by a primary factor: research integrity at scale.

The primary value of AI is its ability to handle certain time-consuming aspects of manuscript processing, allowing editors and reviewers to focus on high-level scientific evaluation: tasks such as reference validation, formatting checks, and basic technical triage are crucial but tedious. AI can perform an initial screen of these elements, flagging problematic cases for the editor to review. This ensures that the editor’s time is spent on decision-making rather than administrative oversight.

We are at a “technological race.” As generative AI makes it easier to produce sophisticated plagiarism and high-quality “fake papers” (ie: paper mills), traditional detection methods are no longer sufficient. The obvious solution is to fight fire with fire: publishers need to integrate Large Language Models (LLMs) and specialized AI tools to detect manipulated images, data inconsistencies, and AI-generated text. Without these AI-driven safeguards, the sheer volume of fraudulent submissions could overwhelm the peer-review system, potentially compromising the credibility of scholarly records.

Collaboration and sharing expertise

As well as attending conferences to participate in industry-wide conversations, MDPI is an active participant in the STM Integrity Hub to address issues that may affect the integrity of the scholarly record.

The STM Integrity Hub provides publishers with a cloud-based environment to check submitted articles for research integrity issues, consistent with industry best practice and fully respecting the laws and ethics of data privacy.

Dr Enric Sayas outlines the nature of MDPI’s relationship with STM:

MDPI is a member of the STM Integrity Hub, a cross-publisher initiative spearheaded by the STM Association. This collaboration is designed to provide a unified defence against several types of research misconduct—such as paper mill operations and duplicate submissions—that often remains invisible to publishers working in isolation.

By pooling resources, we gain a holistic view of the publication landscape; this is essential for detecting sophisticated misconduct that is intentionally diversified across multiple publishers to evade individual detection.

STM Integrity Hub is about to be integrated into Ethicality, therefore ensuring that its benefits are extended beyond MDPI journals, strengthening integrity across the publishing landscape.

MDPI’s commitment to advancing scientific publishing extends beyond delivering research results openly; MDPI shares expertise and tools that empower others to maintain integrity and advance knowledge.

Optimising the publishing process for research integrity

Ethicality strengthens MDPI’s approach to proactive correction. The hub leverages a suite of tools that enables internal and external stakeholders to identify, evaluate, and resolve ethical concerns in academic publishing.

This is part of MDPI’s mission to develop innovative AI solutions with human-in-the-loop validation that help maintain research integrity.

If you want to learn more about a specific tool within Ethicality, click here for a Conference Paper published by the Technology Innovation team which outlines the technology behind and applications of Cite Lens.