Artificial intelligence in the editorial management of scientific journals: an analysis applied to the Revista Digital de Direito Administrativo (RDDA)

ABSTRACT

Introduction:  the management and publishing of scientific journals, as well as any area that deals with information, is undergoing transformations and innovations due to the constant adoption of new technologies as tools for optimizing and automating human work.

Objective:  this article analyzes the use of artificial intelligence (AI) in the editorial management of the Revista Digital de Direito Administrativo (RDDA), with an emphasis on its potential, limitations, and ethical implications.

Methodology:  a qualitative and exploratory approach is adopted, based on a literature review, case study, and documentary analysis of interactions with AI tools (ChatPDF).

Results:  the results indicate that AI can support stages such as manuscript thematic screening, reviewer assignment, and plagiarism detection, contributing to editorial efficiency. However, variations in automated responses and challenges related to algorithmic transparency, human oversight, and compliance with ethical-legal principles were observed.

Conclusion:  it is concluded that the responsible adoption of AI, combined with appropriate regulation and editorial team training, can strengthen scientific governance and improve the quality of legal publications.

KEYWORDS:
Artificial intelligence; Editorial management; Scientific journals; Administrative law; Research ethics

RESUMO

Introdução:  a gestão e editoração dos periódicos científicos, assim como de qualquer área que lida com informação, está passando por transformações e inovações devido à adesão constante de novas tecnologias como ferramentas de otimização e automação de trabalhos humanos.

Objetivo:  este artigo analisa o uso da inteligência artificial (IA) na gestão editorial da Revista Digital de Direito Administrativo (RDDA), com ênfase em suas potencialidades, limitações e implicações éticas.

Metodologia:  adota-se uma abordagem qualitativa e exploratória, fundamentada em revisão bibliográfica, estudo de caso e análise documental de interações com ferramentas de IA (ChatPDF).

Resultados:  os resultados indicam que a IA pode apoiar etapas como triagem temática de manuscritos, indicação de pareceristas e detecção de plágio, contribuindo para a eficiência editorial. Contudo, observamse variações nas respostas automatizadas e desafios quanto à transparência algorítmica, à supervisão humana e à conformidade com princípios ético-jurídicos.

Conclusão:  conclui-se que a adoção responsável da IA, aliada à regulamentação adequada e à capacitação das equipes editoriais, pode fortalecer a governança científica e a qualidade das publicações jurídicas.

PALAVRAS-CHAVE:
Inteligência artificial; Gestão editorial; Periódicos científicos; Direito Administrativo; Ética na ciência

1 INTRODUCTION

Significant transformations have occurred in various sectors of society, including information science and academic publishing, due to advances in artificial intelligence (AI) technologies. In the context of scientific journals, natural language models developed from the GPT (Generative Pre-trained Transformer) architecture have been explored as a means of automating and optimizing various stages of the editorial process. These stages include the initial thematic screening, assignment of reviewers, checking for compliance with editorial standards, and detection of plagiarism.

The adoption of artificial intelligence (AI) in everyday life is transforming all informational environments and areas that deal with information. Whether in the production, dissemination, or organization of information, AI is generating a new perspective on the information environment, including in the academic context. The scientific publishing market is no exception. Changes and opportunities for optimization and automation have opened new horizons and established AI as a valuable asset when employed ethically and under supervision.

In the legal field, in particular, there is a growing interest in using intelligent technologies to make editorial processes more efficient, transparent, and ethical. However, adopting AI in scientific law journals still presents specific challenges due to the field's conceptual rigor and need for contextual and normative analysis. Therefore, it is crucial to understand how to incorporate AI tools in a manner that is ethical, regulated, and effective in legal journals to improve the quality of scientific production.

This article uses a case study involving the application of the ChatPDF tool for thematic screening of manuscripts to analyze the use of artificial intelligence in the editorial process of the Digital Journal of Administrative Law (Revista Digital de Direito Administrativo, RDDA). The study seeks to identify the technology's potential and limitations in supporting editorial management and discuss the resulting ethical and regulatory impacts of its adoption. This research is justified by the increasing demand for innovation in legal journals and the necessity of critically reflecting on the role of AI in curating and evaluating academic work.

This study takes a qualitative, exploratory approach based on a literature review, document analysis, and an empirical study applied to the RDDA. The goal is to contribute to the debate on editorial governance in the age of artificial intelligence and propose guidelines for responsibly using this technology in Administrative Law.

Thanks to AI, various applications and automation processes are possible. It is also worth highlighting the promotion of greater interoperability, or the ability of different systems to interact. This increases the potential for information exchange and facilitates collective work (Brazil, 2020). The journal Múltiplos Olhares em Ciência da Informação (2024) reports on the use of AI for standardized document formatting and PDF/A conversion to keep publications available long-term. Therefore, clarifying this type of AI use favors the editorial communication process and ensures access to information for a longer period. Additionally, using AI to promote Open Science leads to greater scientific dissemination through AI-generated recommendations of academic publications (Silva; Lima, 2024).

Thus, using AI as an editing tool helps maintain editorial consistency. Its potential application extends to the submission, review, and publication processes, ensuring large volumes of submissions can be evaluated and selected for publication in scientific journals. This is particularly beneficial when the editing team is small, as is the case with RDDA. Editorial overload can lead to errors, but with the help of AI, these errors can be prevented, and content can be managed more quickly and efficiently.

2 ARTIFICIAL INTELLIGENCE AND EDITORIAL MANAGEMENT: POTENTIAL, LIMITATIONS, AND ETHICAL IMPLICATIONS

Artificial intelligence (AI) has established itself as a strategic tool in multiple fields, including information science, document management, and justice systems. It is capable of optimizing tasks that were previously the exclusive domain of humans, such as knowledge organization, information retrieval, and decision-making. Its application in editorial environments, such as scientific journals, opens up new possibilities for process automation while raising important ethical and technical questions.

According to Alves (2020), AI can be understood from two main perspectives: empirical and theoretical. In the former, systems seek to simulate human thinking by learning from experience. In the latter, priority is given to executing logical actions based on deduction and inference. These fundamentals underpin the development of applications such as machine learning, which is used for content recommendations and pattern detection, and deep learning, a technology found in assistants such as Siri®, Google Now, and Google Translate (Alves, 2020).

Fontoura and Villalobos (2022) studied the use of AI in automating tasks related to content curation by analyzing a chatbot developed to mediate user access to procedural information. The authors emphasize that the experience prioritized not only the technical improvement of the solution but also user demands and the quality of their interactions. This highlights the importance of integrating human aspects into the development and application of intelligent systems.

Despite recent advances, the use of artificial intelligence (AI) in information environments remains limited in many contexts. Pinheiro and Oliveira (2022) examined twenty years of Brazilian scientific production on the subject in the field of information science and noted that there is still a limited amount of research dedicated to AI applications in this field. The authors emphasize the need to intensify studies focused on information organization and machine learning to promote technical and scientific development in practices such as editorial management.

Similarly, Dorneles (2022) investigated the use of AI in document management and found that although technologies such as natural language processing and deep learning have been successfully applied in areas like health and education, studies on their application to fundamental activities like document classification, processing, and archiving are scarce. This information is relevant to the editorial environment, which relies on the proper organization and traceability of academic records.

In more structured environments, such as justice systems, Bermejo (2021) reported the application of AI in tasks such as automatic case distribution and conflict resolution. He emphasized that these technologies require information professionals to acquire interdisciplinary knowledge in technology and management. Experience shows that, even in highly regulated institutions, AI can significantly contribute to the efficiency and transparency of workflows.

Editorial management involves the organization and distribution of content and a dedication to the scientific integrity of publications. In this context, Jesus (2022) notes that technologies are not value-free because they reflect cultural and social influences. This requires caution when incorporating automated systems into sensitive processes such as peer review and plagiarism detection. Similarly, Kaufman (2022) notes that although human-machine interaction can promote inclusion, instances of discrimination still occur in practice, underscoring the need for ongoing ethical and technical oversight. Regarding this issue, the IFLA (2020) emphasizes that the use of artificial intelligence in information environments must be anchored in well-defined ethical standards. This principle also applies to the editorial context and requires transparency in algorithms and respect for the copyright and intellectual autonomy of those involved.

In his analysis of the prospects for information unit management, Neves (2023) emphasizes that the strategic use of artificial intelligence (AI) will be central to this process. Thus, it is crucial to invest in the training and capacity building of information professionals so they can navigate such transformations. Previously, Neves (2020) observed that expert systems are the first effective AI applications, demonstrating that well-trained algorithms can play a significant role in activities such as manuscript screening and reviewer recommendation. Morandin and Moura (2024) identified a significant increase in interest in AI-based technologies in Brazil, particularly in the health and agribusiness sectors, based on a patentometric study. The authors also point out that patent filings are mostly made by individuals, often in collaboration, revealing an active and diverse environment of innovation around the development of artificial intelligence.

2.1 Contextualization of the history of scientific publishing with technological advances

Pinheiro and Oliveira (2022) conducted a study on the use of and research on artificial intelligence (AI) in information science, analyzing Brazilian scientific production over the last two decades. They observed that although there was an increase in publications during the past three years of the analyzed period, scientific production on AI applications in the field is still in its infancy. They also emphasized the need for further research on topics such as information organization and representation, as well as the application of machine learning techniques. Vizoso (2022) briefly discusses advances in AI in information science and notes challenges related to its use, such as bias and a lack of transparency in systems. These limitations raise important questions about information ethics, access to and development of free software, and implications for academic research, particularly regarding the explainability of the models used.

Evidently, the integration of AI in information science is not well established and requires more in-depth research. Nevertheless, AI has proven to be a highly promising tool for disseminating information and has significantly transformed the ways in which knowledge is produced, organized, and accessed. In this context, information professionals must act as agents of research and adaptation, developing the skills necessary to incorporate and experiment with new technologies in a critical and strategic manner.

In the Brazilian context, the development of scientific publishing has historically been slow, particularly compared to Europe. Rosa (2009) notes that the limited presence of the press during the colonial period was a deliberate strategy by the Portuguese Crown to control the colonial population by restricting access to information. It was only with the arrival of the royal family in Brazil in the early 19th century that publishing received greater impetus. Nevertheless, the publishing market only consolidated later, driven mainly by private initiative.

Unlike the European model, where university publishing originated the publishing industry, Brazil did not follow this path. According to Rosa (2009), 'the Brazilian publishing industry did not emerge from universities, nor was it a tradition for these institutions to have their publishing houses.' It was European immigrants, mainly French and Portuguese, who settled in São Paulo and Rio de Janeiro that boosted this sector in the late 19th and early 20th centuries. The first Brazilian university press, linked to the Federal University of Pernambuco, was established in 1955.

This milestone represented a fundamental step towards the institutionalization of scientific publishing in Brazil, following the consolidation of the publishing market. This development enabled the expansion of academic production and strengthened formal scientific communication in Brazil.

According to Rosa (2009), several publishers targeting higher education audiences developed specialized collections. Editora Nacional, for example, was responsible for publishing series such as Brasiliana, Biblioteca Médica Brasileira, and Biblioteca Pedagógica Brasileira. Livraria Martins, created in 1937, emerged in the context of cultural renewal in São Paulo driven by the founding of the University of São Paulo (USP), initially focusing on the publication of legal works. Over time, it began to develop relevant academic collections, such as the Biblioteca Histórica Brasileira, the Biblioteca de Literatura Brasileira, and the Biblioteca do Pensamento Vivo.

This process of editorial expansion paved the way for the consolidation of scientific publishing in Brazil, enabling the growth of research, academic training, and the qualified circulation of knowledge. The modernity and technological advances inherent in society also reached and transformed the editorial environment. According to Santana and Francelin (2016), one of the major changes for scientific journals was the transition in the type of support that occurred in recent decades, which led to the popularization of digital magazines and facilitated access to academic production, in this sense: “the electronic scientific journal, by its nature, modifies aspects of form, enhances the dissemination of content, and renews editorial issues” (Santana; Francelin, 2016, p. 7).

These reflections are based on the publishing landscape that emerged in the early 2000s with the advent and popularization of digital media. The Brazilian Institute of Technology and Information (IBICT) began providing the academic community with access to technologies for preserving electronic periodicals (BDTD) and the Electronic Journal Publishing System (SEER) (Freire & Freire, 2013).

However, the intensified development and widespread accessibility of artificial intelligence technologies since mid-2020 have raised concerns and created new possibilities for improving the performance of the scientific publishing medium in an even more innovative way.

Artificial intelligence uses the Big Data system in its operations. This technological tool enables the analysis of large amounts of data quickly and offers various services based on the extracted data, such as decision-making assistance, information management, and personalized responses (Silva, 2024). The ability to personalize responses according to the user's profile is advantageous for RDDA publishing. RDDA uses artificial intelligence to analyze whether the content of articles aligns with the journal's scope. As AI iteratively learns from customization patterns, it progressively identifies the types of articles most aligned with RDDA's editorial profile. This promotes thematic consistency and optimizes editors' time.

2.2 Applications and challenges of artificial intelligence in scientific editorial management

The use of AI has grown within the editorial workflows of scientific journals, encompassing tasks such as manuscript preparation, review, content curation, and evaluation. The most frequent applications include writing support, editorial workflow automation, plagiarism detection, authorship verification, and publication trend analysis (Lima, 2024).

AI-based tools have improved scientific writing by providing grammatical corrections, enhancing vocabulary, and offering machine translation. These technologies benefit authors facing language barriers, including non-native English speakers (Lima, 2024; Oliveira & Braida, 2024). Additionally, the automation of repetitive tasks, such as formatting articles and checking references, has accelerated editorial processes and increased publication efficiency (Lima, 2024).

In the study "AI-Assisted Peer Review," Checco et al. (2021) developed and tested a machine-learning model that was trained using approximately 3,300 manuscripts and their respective evaluations. The model extracted only textual information, readability metrics, and formatting to predict peer review scores. The results revealed that the system could reproduce human decisions with high accuracy, showing strong correlations between text's superficial characteristics and editorial decisions. This AI can save time by assisting with initial screening and identifying formatting or readability issues before the full review.

The article "AI in Peer Review: A Recipe for Disaster or Success?" (Chaturvedi, 2024), published by the American Society for Microbiology (ASM), critically analyzed the role of artificial intelligence (AI) as a support tool in the peer review process. AI is primarily used for the initial screening of manuscripts, ensuring compliance with editorial guidelines, identifying data inconsistencies, and generating automatic abstracts, thereby facilitating the work of editors and reviewers. However, the ASM emphasizes that these applications should complement, rather than replace, human judgment. The organization also warns of ethical and practical risks, such as confidentiality breaches when uploading manuscripts to external platforms, limitations in the contextual interpretation of scientific texts, and the possibility of reproducing algorithmic biases.

The stage of appointing reviewers revealed potential for improvement with AI. Kreutz and Schenkel (2021) present an intelligent system developed to improve the selection of reviewers for scientific articles from a fixed set of candidates. Unlike traditional methods that rely on manual profiles or basic recommendations, RevASIDE uses semantic analysis techniques to understand the content of manuscripts and cross-reference it with data from registered reviewers. It considers their areas of expertise, experience, and interests. The system also seeks to ensure diversity and complementarity among the selected reviewers to promote a more complete and qualified evaluation. The authors demonstrate that this approach can increase the efficiency and accuracy of reviewer selection, reducing editors' manual effort and improving the quality of the peer review process.

Systems of this nature are already used by international journals and could be adapted to RDDA's reality while respecting the legal-administrative field's epistemological and terminological specificities.

However, significant ethical challenges arise. The lack of clear AI usage guidelines in most Brazilian scientific journals remains an obstacle. Research by Oliveira and Braida (2024) involving 84 communication journals reveals that only four had formal AI usage guidelines. The main concerns are authorship, plagiarism risk, and transparency in tool use, all of which are essential elements of scientific integrity.

The Committee on Publication Ethics (COPE) clarifies that AI tools cannot be considered authors because they lack the capacity to assume intellectual responsibility for the content they generate. Thus, COPE (2023) recommends explicitly stating the use of AI tools in manuscripts, with the human author remaining fully responsible for the produced content.

Lima (2024) also addressed the ethical use of AI, emphasizing the need to interpret automated results, protect the privacy of the involved data, and mitigate algorithmic biases. The author notes that the absence of consistent regulations could lead to improper or inconsistent practices within the scientific community.

Additionally, organizations such as UNESCO (2024) and SciELO (2023) have made recommendations regarding the responsible use of these technologies. For example, the SciELO guide states that authorship should be restricted to humans and those editors and reviewers should avoid using AI to analyze manuscripts. Failure to do so constitutes an ethical breach.

Despite these challenges, authors such as Sampaio, Sabbatini, and Limongi (2024) emphasize that AI presents valuable opportunities to advance scientific communication. However, this requires adequate training of editorial agents, transparent regulations, and practices based on responsibility and integrity.

3 METHODOLOGY

An exploratory and qualitative approach based on a literature review and document analysis was adopted to understand the use of AI in RDDA editorial management and its implications for scientific journals. According to Gil (2008), exploratory research is recommended when a problem has not yet been studied. This approach allows for the formulation of hypotheses and preliminary guidelines for future investigations.

3.1 Literature Review

The first methodological step was a literature review in which national and international studies addressing the use of AI in academic publishing were selected. The search was conducted in the Scopus, SciELO, and Google Scholar databases and covered publications from 2018 to 2024. The review aimed to identify the primary tools employed in automating the editorial process and to address the ethical, regulatory, and operational challenges associated with adopting this technology. According to Bardin (2011), documentary analysis allows one to explore written content that provides valuable information about the phenomenon under study, especially in an emerging field such as the application of AI to scientific publishing.

3.2 Case study Digital Journal of Administrative Law (RDDA)

In the second stage, a case study of the RDDA was conducted to map potential applications of AI in its editorial process. RDDA is a scientific journal founded in 2013 and published twice yearly. It is affiliated with the Ribeirão Preto Law School of the University of São Paulo (FDRP-USP). The journal aims to disseminate scientific research in Administrative Law and its branches, focusing particularly on studies demonstrating the relationship between Law, Public Administration, and Development. It publishes research in Administrative Law and administrative procedure, as well as related areas such as Environmental, Urban, Health, and Competition Administrative Law. (RDDA, n.d.).

The different stages of the journal's editorial process were analyzed at this stage, such as the initial screening that identifies whether articles are within the journal's scope. Additionally, the practices adopted by academic journals that have implemented AI-based solutions were compared to identify patterns, challenges, and best practices (Lópezosa, 2023). This comparative methodological strategy is essential for assessing the feasibility of implementing AI in RDDA and for proposing appropriate solutions for the journal.

3.3 Analysis of ChatPDF responses

The third stage is a critical and proactive analysis of the impact of AI on the editorial governance of RDDA. This analysis considers aspects such as the transparency, impartiality, and reliability of scientific evaluation processes. Additionally, normative issues related to the use of AI in legal publishing are addressed, given the need for compliance with academic guidelines and ethical principles. According to Flick (2009), qualitative analysis enables interpretation of the social and institutional implications of complex phenomena, such as the integration of AI into editorial processes.

Chart 1
Systematization of AI responses (ChatPDF) regarding the thematic suitability of articles submitted to RDDA

Article	Version	IA Response	Evidenced Criterion	Final Classification	Observations
1	version 1	Not directly	Lack of clear connection to the scope, although there are possible approximations	NO (with reservations)	Suggested adaptation of the text
1	version 2	Y es	Emphasis on the social impact of government intervention	YES	Variation in response to the same article
2		No	Philosophical topic, without a legaladministrative focus and outside the Brazilian context	NO	Detailing in three exclusion criteria
3		Yes	Reforms in Administrative Law with an Impact on Data Protection	YES	Direct alignment with the thematic axes of RDDA
4		It looks like	Loose connection with legal deficiencies in Public Administration	UNCERTAIN	Absence of abstract and keywords hindered analysis
5	version 1	It looks like	Relevance to Public Administration and social impacts	UNCERTAIN /ALMOST YES	AI initially uncertain but recognizes relevance
5	version 2	Yes	Discussion of theories, criticism of dogmas, impact on public management	YES	AI takes a more assertive stance
6		No / adjustments needed	Incomplete thematic alignment, but with suggestions for improvement	PARTIALLY SUITABLE	Recommends restructuring to comply with RDDA

• Source: The authors.
• Note: The prompt used was “Please indicate whether this article is suitable for publication in RDDA, considering its scope: RDDA aims to promote the publication of texts that, explicitly or implicitly, highlight the relationship between law, public administration, and the development process [...]”.

Thus, the research is structured around three main areas: (1) a literature review on AI in the publishing context, (2) an RDDA case study, and (3) a critical analysis of the challenges and benefits of adopting AI in legal publishing. This combination of approaches allows for an in-depth examination of the topic and contributes to the debate on technological innovation and its repercussions on administrative law.

3.4 Note on ethical transparency and access to data

One of the authors of this study is part of the editorial team of the Digital Journal of Administrative Law (RDDA), coordinating and monitoring the editorial process. This is made explicit to ensure transparency and avoid any potential conflicts of interest.

The other authors have no formal connection with the journal and participated only in the academic research. Data access was obtained exclusively from published articles in the public domain. No unpublished manuscripts, opinions, or internal documents from the Open Journal Systems (OJS) were consulted.

Interactions with the ChatPDF tool were based on open, publicly available files and respected the principles of scientific integrity, confidentiality, and research ethics. No sensitive, unpublished, or identifiable information was used.

This study adheres to the guidelines of the Committee on Publication Ethics (COPE, 2023) and the UNESCO guidelines (2024), promoting transparency, accountability, and human oversight in the application of artificial intelligence tools to scientific publishing.

4 RESULTS AND DISCUSSION

The following are the main findings of the empirical research on the use of artificial intelligence (AI) in the RDDA editorial process, focusing on its practical applications, as well as its ethical and regulatory implications. The results are organized into two complementary sections. The first section (4.1) discusses the practical applications of AI in RDDA based on concrete examples of the tool's responses regarding the thematic suitability of manuscripts. This stage aimed to verify the potential of AI to support the editorial team, particularly in the preliminary analysis of compliance with the journal's scope. The second section (4.2) addresses the ethical and regulatory implications identified throughout the process. Special attention is given to transparency, human supervision, and regulatory compliance requirements in the use of automated technologies in scientific publishing. The results reveal the potential of AI to innovate editorial management and the technical and regulatory limits that must be addressed to ensure its responsible use.

4.1 Practical applications of AI in RDDA

The editorial team has used the tool to analyze the thematic suitability of articles submitted to the journal. To accomplish this, the .doc (Word) file corresponding to each article, obtained from the Open Journal Systems (OJS) submission platform, is inserted into the system. The following text, adapted from the "About" section of the Revista Digital de Direito Administrativo (RDDA) website and presenting the publication's focus and scope, is used as the basis for the analysis:

Text used as a command in ChatPDF:

Please indicate whether this article is suitable for publication in RDDA, considering its scope. RDDA aims to promote the publication of texts that highlight the relationship between law, public administration, and the development process. These texts should address one of the following central issues: How do deficiencies in the legal treatment of public administration (in organizational, procedural, and contractual terms, for example) generate negative impacts for the state and society? Conversely, how do new institutions and reforms of administrative law contribute to the proper functioning of public administration and ultimately improve living conditions?

Below are eight examples of responses from ChatPDF.

Figure 1
Analysis Article 1, version 1 - NOT DIRECTLY

In this first case, it is clear that ChatPDF classifies the study as not directly related to the scope of RDDA. Artificial intelligence highlights the requirements of the command given to it and detects the lack of these requirements in the content of the article examined. The tool also delves deeper and produces an analysis of the dialogue that could exist between the proposed theme and other topics in Public Administration, addressing the possibility that the issue of state intervention is a common point. This AI feedback demonstrates an ability to associate and identify broader contexts. After all, despite admitting reservations about the theme and giving a predominantly negative response in relation to the article when viewed from the perspective of the journal's guidelines, it was still able to establish a degree of connection while recommending reconsideration and adaptation of the proposal.

Figure 2
Analysis Article 1, version 2 - YES

However, when the same text was submitted to ChatPDF, the response changed completely. It established that the article had an appropriate theme for RDDA content. This new position taken by artificial intelligence is supported by part of the operating command it received, which implies that the magazine should include topics that could have a positive or negative impact on society. ChatPDF also concluded that the article addresses legal aspects of state intervention, which could contribute to improvements in society. Thus, this second analysis is broader and more generic than the first.

Figure 3
Analysis Article 2 - NO

The analysis of ChatPDF in this article is divided into three topics that discuss reasons why it should not be admitted to the RDDA. Thus, artificial intelligence denotes a detailed approach in following the requirements of the initial command, which explains the scope of the magazine. In this sense, according to ChatPDF, the main theme does not focus on the legal area of interest to RDDA; the connection with Public Administration made by the article does not propose positive or negative aspects for society, as it is a more philosophical field; and it emphasizes that the journal's publications seek the contemporary Brazilian context, something that is not present in the theme of the text. In short, the artificial intelligence response highlights that the philosophical line adopted by the article does not dialogue with the publications intended by RDDA.

Figure 4
Analysis Article 3 - YES

The AI tool deems the article relevant to the RDDA theme and relates it to the magazine's central issue. It highlights the initial command's requirements and emphasizes that the article elaborates on reforms in administrative law and their societal impact, particularly regarding data protection. Thus, the AI tool produced a wholly favorable response, emphasizing that the article aligns with RDDA's interests.

Figure 5
Analysis Article 4 - OPINION

ChatPDF provides an uncertain analysis of the article, indicating that the text appears to align with the scope of the RDDA. It makes an association with deficiencies in the legal treatment of public administration, suggesting that this theme could transform life and society. However, the tool does not specify the context in which these changes would occur or their potential effectiveness. Since the text has no summary or keywords, artificial intelligence has difficulty determining its theme and the likelihood of its inclusion in the journal.

Figure 6
Analysis of Article 5, version 1 - IT SEEMS

In this case, ChatPDF initially adopts an uncertain stance, indicating that, while the article 'seems to fit' the RDDA guidelines, it may require reservations or adjustments. However, the tool also recognizes that the text is relevant to the themes of public administration and its social impacts - aspects that were highlighted in the original prompt as central to the journal's scope. Thus, while the analysis initially begins with hesitation, it evolves into a more affirmative interpretation, signaling that the article's theme substantially aligns with the editorial profile that RDDA seeks to preserve.

Figure 7
Analysis Article 5, version 2 - YES

The same article from the previous item applies in this case, and ChatPDF's response adapts and renews itself. This demonstrates that there are several reasons why it is valid to add it to the scope of the RDDA. The tool emphasizes issues of public administration and the approaches of public and private law. It highlights issues of criticism and reflection and the relationship with social and state impact mentioned in the command given to AI. It contributes to contemporary debate and generates insights into various fields. In line with the previous three reasons, ChatPDF indicates that discussions of new theories and critical reflections on established dogmas influence public administration in general.

Figure 8
Analysis Article 6 - NO/NEEDS ADJUSTMENTS

In this case, ChatPDF determines that the article does not align with RDDA's scope, recommending a broader analysis to align with the journal's guidelines. With this in mind, ChatPDF presents three points from the given command, drawing a parallel with the text and justifying why these points do not align with RDDA. In conclusion, the tool acknowledges that there are topics relevant to Law and Public Health but explains why this article does not align with RDDA. It suggests linking the topic to a discussion of Public Administration and social conditions to demonstrate what is missing for the article to fully align with RDDA's editorial scope. In this case, artificial intelligence acts not only as a filtering tool but also as a mediator of conceptual adjustments. It indicates ways to adjust the theme of texts that, although relevant, lack direct alignment with the journal's guidelines. This action reinforces AI's potential as a reflective support tool when it is part of a supervised editorial process committed to quality and scientific coherence.

Below is a summary of ChatPDF's responses:

• Analysis of Article 1, Version 1: NO, directly. ChatPDF acknowledges that the article is not directly related to the scope of the RDDA but recognizes possibilities for thematic approximation and suggests adaptation.

• Analysis of Article 1, Version 2: YES. Upon reanalyzing the same article, ChatPDF changes its response, indicating thematic adequacy and highlighting issues related to state intervention.

• Analysis of Article 2: NO. The AI details reasons for rejection, including a lack of legal and administrative focus, philosophical bias, and decontextualization in relation to contemporary Brazil.

• Analysis of Article 3: YES. The response acknowledges adherence to the journal's scope, particularly regarding administrative law reforms and data protection.

• Analysis of Article 4: IT SEEMS. The AI indicates possible thematic relevance, but there is insufficient evidence for confirmation.

• Analysis of Article 5, Version 1: IT SEEMS. Initially uncertain, the analysis evolves into a positive assessment by identifying its relevance to public administration.

• Analysis of Article 5, Version 2: YES. The repetition of the text results in an affirmative response without the previous tone of uncertainty.

• Analysis of Article 6: NO/NEEDS ADJUSTMENTS: The AI considers the text suitable with thematic adaptations.

Analyzing interactions with the ChatPDF tool provided insight into the use of artificial intelligence in the initial stage of screening articles for the Digital Journal of Administrative Law (Revista Digital de Direito Administrativo, RDDA). Although the AI responses were relevant, they showed significant variations when faced with the same text submitted at different times. This behavior indicates the technology's potential to support editorial decisions and the need for critical interpretation by the editorial team.

Overall, the tool was found to be capable of identifying key terms, conceptual relationships, and general alignments with the journal's scope, thereby optimizing the screening process. However, inconsistent responses-sometimes favorable and sometimes negative for the same content-demonstrate that AI cannot replace human judgment when in-depth contextualization, interdisciplinary analysis, and scientific relevance assessment are required.

Additionally, the quality and completeness of metadata (abstract, keywords, and textual structure) directly influence the accuracy of the AI response, underscoring the importance of adhering to best practices when submitting manuscripts. While the responses generated by the tool demonstrated some associative and argumentative reasoning, they still lacked clearly defined objective criteria, which reinforces the importance of qualified human editorial supervision.

In conclusion, artificial intelligence can serve as an auxiliary technology for thematic screening and improving editorial workflow efficiency. However, it must be associated with well-defined human and ethical criteria to ensure that editorial decisions align with the principles of quality, integrity, and scientific responsibility that govern academic journals. Thus, responsible and critical use of AI can strengthen editorial governance and increase the social relevance and reach of scientific publications.

4.2 Ethical and regulatory implications

The document analysis and case study conducted with RDDA revealed concrete opportunities and relevant challenges associated with incorporating AI tools into the editorial workflow.

The initial screening of manuscripts can be significantly optimized by using language models that are trained to assess thematic adherence and verify compliance with minimum formal criteria. Using these resources would save editors time and standardize objective aspects such as length, textual structure, and compliance with the journal's standards.

However, national and international research (Prudencio, 2024; Felix et al., 2024; Quintino et al., 2024; Checco et al., 2021; Chaturvedi, 2024; Pearson, 2024; Schintler, McNeely, & Witte, 2023) warns of ethical challenges, particularly algorithmic biases, and emphasizes the necessity of continuous human supervision to prevent adverse outcomes. These studies highlight the potential and risks of adopting AI in all stages of scientific publishing, reinforcing the importance of an approach that combines computational efficiency with expert human judgment. These studies also advocate for the responsible and transparent use of AI with clear disclosure policies and continuous human supervision. They reinforce the idea that the value of the peer review process lies in the critical evaluation made by human experts.

Regarding plagiarism detection, widely available tools have been found to increase the security and reliability of evaluation processes by mitigating the risks of textual duplication and poor academic practices through their automated and systematic integration into the editorial workflow (Santos & Oliveira, 2022; Hesselmann, 2022).

However, Wang (2022) discusses how advancements in artificial intelligence text generation tools, such as GPT-3, are challenging the concept of plagiarism. Wang argues that these systems violate fundamental principles of authorship and originality because they generate content based on third-party data, even though they do not directly copy excerpts from other authors. As the AI director for Turnitin software, Wang points out that AI-powered plagiarism is harder to detect because the texts produced are unique even though they're based on existing patterns. He warns that the non-transparent use of these tools can undermine academic integrity, emphasizing the need to redefine plagiarism in an era where students and researchers have access to technologies capable of generating cohesive and convincing texts in seconds.

From an ethical and normative perspective, the adoption of AI technology should be grounded in principles such as transparency, fairness, explainability, and continuous human supervision. These principles are especially important in legal journals, where rigorous argumentation, author responsibility, and editorial integrity are essential. The research highlights that indiscriminately using AI tools without clear normative guidelines can compromise a journal's impartiality, scientific quality, and institutional credibility.

Therefore, while AI's role in RDDA is still evolving, its gradual, critical, and regulated implementation could significantly advance the modernization of editorial management. This process strengthens the scientific governance of publications and contributes to improving academic production in Administrative Law.

5 CONCLUSION

AI has established itself as a promising resource in scientific publishing by offering technological solutions that optimize processes such as manuscript screening, reviewer suggestions, and plagiarism detection. However, as Schmidt (2025) pointed out, most professionals in the field continue to perceive tasks requiring critical judgment, contextual sensitivity, and strategic decision-making, such as predicting trends, selecting journals for publication, choosing reviewers, managing editorial processes, and seeking funding opportunities, as essentially human competencies.

This study investigated the impact of AI use in the RDDA editorial process by focusing on its practical applications, operational limitations, and ethical implications. Using a qualitative, exploratory approach based on literature reviews, document analyses, and case studies, we mapped key points in the editorial flow amenable to automation and technological improvement.

The results show that using AI-based tools can significantly improve the initial thematic screening of manuscripts, standardize formal verification stages, and increase the evaluation process's efficiency. However, these benefits only materialize with continuous human supervision, well-defined ethical criteria, and transparent policies regarding the use of these technologies.

Although the discussion on the role of AI in the field of legal journal publishing is still in its infancy, this study indicates that its strategic adoption can strengthen the RDDA's position as a journal committed to scientific quality, methodological innovation, and effective contribution to the debate on Public Administration and Administrative Law. By improving the journal's internal processes, it also creates the possibility of greater institutional and social impact through the dissemination of evidence-based knowledge.

However, it is recognized that the responsible incorporation of AI requires investments in digital infrastructure, training of editorial teams, and the establishment of clear regulatory guidelines to mitigate risks related to algorithmic opacity, the reproduction of biases, and the loss of human control over sensitive decisions. In this sense, this research contributes to the emerging debate on technological innovation in scientific communication, offering theoretical and practical support so that legal journals-such as RDDA-can integrate artificial intelligence in an ethical and effective manner, aligned with the fundamental values of open science, academic integrity, and social responsibility.

Acknowledgments:

We thank the collaboration of the student and Library Science intern, Laura Cruz Galdiano.

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• 

  
  
• 

  
  
• Financing:
  Not applicable.
• Ethical approval:
  Not applicable.
• Data and material availability:
  Not applicable.
• Image:
  Extracted from the Lattes platform.
• JITA:
  LP. Intelligent agents | Artificial inteligence
• ODS:
  16. Peace, justice and effective institutions

Edited by

• Editor guest:
  Gildenir Carolino Santos https://orcid.org/0000-0002-4375-6815

Data availability

Not applicable.

Publication Dates

• Publication in this collection
  27 Apr 2026
• Date of issue
  2026

History

• Received
  22 July 2025
• Accepted
  01 Sept 2025
• Published
  14 Nov 2025