Ethical Challenges of AI in Academia: Impact and Implications for Higher Education
Ana M.ª Porto Castro (Volume editor)
Eva M.ª Espiñeira Bellón (Volume editor)
M.ª Josefa Mosteiro García (Volume editor)
Summary
Excerpt
Table Of Contents
- Cover
- Halftitle Page
- Title Page
- Dedication
- Contents
- Figures
- Tables
- Acknowledgements
- Prologue
- Introduction
- Educational Personalisation in the Age of Artificial Intelligence: Opportunities and Ethical Challenges
- Identity and Human Destiny in the Algorithmic Age: Educational Challenges in the Face of the Technodigital Revolution
- Artificial Intelligence in Education: Opportunities and Ethical Challenges
- Integration of AI in Higher Education: Cultivating Entrepreneurial Potential as a Path to Educational Personalisation
- The Use of Artificial Intelligence in Higher Education Institutions in Portugal – Ethical Challenges and Opportunities
- The Use of AI in Higher Education: Between Challenges and Opportunities
- AI – a Question of Purpose, Not Intentionality
- AI as a Tool to Support Research, Not a Substitute for Human Thinking
- The Use of AI in Higher Education Institutions in Portugal: What Reality? International Framework
- AI and the Portuguese Higher Education Reality – What Has Been Done?
- Final Considerations
- Artificial Intelligence in the Literature Review: Ethical Issues
- Introduction
- The Importance of the Literature Review
- Integrating AI Tools into the Literature Review
- Ethics and Integrity in the Use of AI Tools for Literature Reviews
- Conclusion
- IAgiarism: Ethical and Academic Challenges in the Age of Artificial Intelligence
- Introduction
- Objectives
- Method
- Population and Sample
- Instruments
- Data Collection Procedure
- Technical Analysis of the Instruments
- Data Analysis
- Results
- Conclusions
- Scientific Retractions: Historical Evolution, Ethical Challenges and the Role of Artificial Intelligence
- Scientific Retractions and Artificial Intelligence (AI)
- Impact of Retractions on the Scientific Community and Scientific Integrity
- Evolution of Scientific Retractions and Their Relation to the Use of Artificial Intelligence
- Main Causes of Misbehaviour Leading to Retraction
- Scientific Misconduct
- Unintentional Errors
- Contextual Factors
- Inappropriate Use of AI
- Conclusions
- AI Use Declaration
- Acknowledgements
- Excellence and Academic Integrity in the Age of Artificial Intelligence: An Ibero-American Perspective
- Introduction
- The State of Academic Integrity in Higher Education Institutions in Ibero-America
- Literature Review
- Generative Artificial Intelligence Tools
- Detection Tools for AI-generated Text
- Concept and Functionality
- Culture of Academic Integrity
- Analysis of Policies for AI Usage in Higher Education
- Sample
- Methodology
- Results and Findings
- Conclusions and Future Work: A Critical Review of Institutional Responses
- Institutional Response and Regulatory Frameworks
- Faculty: Expectations and Support
- Student Responsibilities and Ethical Considerations
- Institutional Commitment to Academic Integrity
- Recommendations for Moving Forward
- Acknowledgement
- Generative AI as a Catalyst for Innovation and Teaching Improvements: Challenges and Opportunities
- Introduction
- New Epistemological, Normative and Practical Scenarios
- Transformation of the Teaching Role as Both a Challenge and an Opportunity
- GenAI Tools for Establishing New Teaching and Innovation Models in University Classrooms Through Co-Intelligence
- Elements for Reflection and Improvement: Opportunities for Innovation with GenAI
- Conclusion
- Statement on Use of AI
- The Impact of Generative AI on Academic Texts: Changes in Scholarly Communication and Integrity
- Introduction: Academic Publishing, Setting a Definition
- Phase 1. Pre-1940s: Learned Societies and the Gentlemanly Ethos
- Phase 2. 1940s–1980s: Expansion, Professionalisation, and the Rise of Commercial Publishing
- Phase 3. 1980s–Present: Digital Transformation, Open-access, and the Commercial Oligopoly
- Ethics in Scientific Communication: A Historical Analysis
- Seventeenth and Eighteenth Centuries: The Foundations of Scientific Publishing and Early Ethical Concerns
- Nineteenth Century: Institutionalisation of Science and Ethical Dilemmas
- Twentieth Century: Fraud, Conflicts of Interest, and Replication Crises
- Twenty-first Century: Open Science, Retractions, and New Challenges
- A New Era: Opportunities and Perils of AI in Academic Publishing
- Opportunities in Academic Publishing
- Perils of AI in Academic Publishing
- Policies on AI Use in Academic Publishing
- Norms and Guidelines for AI in Academic Publishing
- Undeclared and Unethical Use of AI in Academic Publishing: Evidence and Research
- Prevalence of Undeclared AI Use in Academic Publishing
- Detection Challenges and AI-assisted Writing Patterns
- Ethical Implications of Undeclared AI Use
- Commercial Exploitation and Paper Mills
- Conclusions
- AI Use Declaration
- Acknowledgements
- Criteria for Assessing the Impact of Generative AI on Students’ Dissertation Defences
- Introduction
- Literature Review
- Study Approach and Methodological Framework
- Reflections and Rationale for Assessment Criteria
- Our Proposal
- Discussion
- Conclusions and Prospective
- Acknowledgements
- Spanish Early Career Researchers and Research Integrity: Main Controversies and Artificial Intelligence
- Introduction
- Objectives and Methodology
- Results Analysis
- Controversial Behaviours and Practices in the Process of Scientific Communication
- Artificial Intelligence (AI): The Last Disruptor
- Conclusion
- Artificial Intelligence in Higher Education: Limitations and Potential in the Teaching-Learning Process
- Introduction
- Methodology
- Informants, Inclusion and Exclusion Criteria
- Data Collection Instrument
- Validation of the Instrument
- Data Collection Procedure
- Data Analysis
- Results Analysis
- Discussion and Conclusion
- Artificial Intelligence in Music Composition: Ethical and Academic Challenges in the Classroom
- Theoretical Framework
- Objectives
- Methodology
- Research Approach and Design
- Instrument
- Participation
- Data Processing and Analysis
- Results
- Perceptions and Challenges of AI in Musical Composition
- Educational Applications of AI in Music Teaching
- Challenges and Dilemmas in Music Education: Creativity and Digital Literacy
- Discussion and Conclusions
- Academic Integrity or Artificial Intelligence? Towards a Preventive Culture in Sweden
- Introduction
- Background
- Previous Studies and Theoretical Framework
- Data and Method
- Findings
- Discussion
- Limitations of the Study
- Conclusion
- AI-assisted University Training for Educators: Plagiarism, Ethics, and Research Skills Development
- Introduction
- Working Hypotheses, Research Questions, and Objectives
- Method
- Results
- Research Skills in Initial Educator Training
- The European Framework for Researchers: ResearchComp
- Proposals of AI-driven Research Skills in University Training
- Ethical and Plagiarism Implications of the Use of AI in Research Skills Training
- Conclusions
Acknowledgements
The content of this book is the result of the effort and collaboration of researchers from different parts of the world who have dedicated their time, knowledge, and experience to reflecting on the ethical and academic challenges posed by artificial intelligence in higher education.
Our deepest gratitude goes to the authors of this collective work, whose commitment to research and academic integrity has made it possible to build a volume with a global perspective. The diversity of approaches, institutions, and countries represented in these pages reflects the international dimension of a debate that transcends borders and educational systems, providing a rich and nuanced vision of the impact of artificial intelligence on teaching, learning, and research.
We would also like to express our appreciation to the Secretaría Xeral de Universidades of the Consellería de Cultura, Educación e Universidade of the Xunta de Galicia, and particularly to its Secretary General, Dr José Alberto Díez de Castro, for his strong support of research within the Galician University System (SUG). His leadership has been instrumental in developing in-depth studies on academic plagiarism and integrity in higher education, fostering the consolidation of an inter-university research team.
This effort has enabled collaboration among scholars from universities in Spain, Portugal, Brazil, Mexico, Paraguay, Sweden, the United Kingdom, the United States, and other countries. Thanks to their contributions, this work offers a comparative analysis of ethical and academic dilemmas across different educational contexts, identifying common challenges and diverse strategies to address the use of artificial intelligence in academia.
Finally, we would like to highlight that the preparation of this book has been a process of academic dialogue and exchange, integrating different disciplinary and cultural perspectives. We hope that this collaborative effort will serve as a significant contribution to the debate on academic integrity and the ethical use of artificial intelligence, providing valuable insights and tools for the future of higher education in a globalised context.
Prologue
The illiterate of the 21st century will not be those who cannot read or write, but those who cannot learn, unlearn, and relearn.
ALVIN TOFFLER
We live in a time of radical change. Artificial intelligence (AI) has burst into our lives with the force of a wave that cannot be stopped. It is not a recent invention, but its impact certainly is. In just a few years, it has gone from being a technical curiosity to becoming a constant presence in our daily lives. It speaks to us from our mobile phones, suggests what to watch or buy, assists us in our searches, even makes decisions on our behalf, often without us realising it. And although it fascinates us, it also makes us uneasy. In the field of higher education, this concern becomes particularly acute: What is the point of teaching certain content if a machine can generate it? How do we assess learning if students can delegate their tasks to an AI?
This technology is advancing steadily, and often imperceptibly. It is already with us, present in the simplest of actions such as requesting a song or writing a message. Its usefulness is undeniable. It saves us time, simplifies processes, and automates tasks. Yet it also compels us to stop and ask ourselves: Are we truly prepared to live with it without losing control?
The uncertainty of the future should not paralyse us. As with previous technological revolutions, fear is understandable, but not inevitable. The key lies in our attitude: we can resign ourselves to being mere spectators, or we can embrace the challenge of becoming protagonists of change. AI can be a powerful tool, but it must be guided by robust principles. Otherwise, its development may follow paths that we have not consciously chosen.
We cannot predict everything that is to come, but we can start to shape it. The decisions we make today will set the direction for the years to come. That is why it is urgent to establish clear ethical criteria. If we do not set limits, we run the risk of giving in too much. AI already influences our consumption decisions, our opinions, our habits, sometimes without us even realising it. We cannot allow the wires to become our veins, nor AI our brain. We must learn to look carefully, and to distinguish between when we are making choices and when we are being guided.
Learning to live with AI is not only a technical issue but also a cultural and ethical one. It involves understanding its logic but also about recognising our responsibility. Amid so many promises of efficiency and speed, there are aspects we must not neglect: intellectual property, originality, and honesty. Many students already use programmes such as ChatGPT to write papers. Can we still speak of authorship in the same terms? What happens to the creator’s rights if the content has been generated by a machine?
Current laws barely address these issues. They are designed for a previous era. Although they recognise the author’s right simply by the act of creation, they do not offer clear answers about what happens when the creation comes from software. Who, then, is the author? The person who gave the instructions? The company that developed the algorithm? No one? The lack of regulation opens fertile ground for confusion and conflict. If we do not address it in time, it will be too late.
AI is here to stay, and we still do not know its full scope. It is like an expanding ocean, full of currents whose destinations remain unknown. Yet the truth is that we are already navigating it. We cannot turn our backs on this reality or anchor ourselves to old paradigms. We need a new perspective, an open, critical, and constructive attitude.
This book, which I have the privilege to introduce, brings together expert voices that explore this issue from the context of higher education. Each chapter is an invitation to think, to debate, and to imagine, because universities, now more than ever, need to rethink and reimagine themselves. Not to lose their essence, but to defend it with intelligence, ethics, and honesty.
We are moving between two eras: one in which knowledge was almost exclusively the result of human effort, and another in which technology multiplies our capabilities but also blurs our boundaries. It is up to us to ensure that this transition does not mean giving up, and that we do not forget what is essential: the value of free thought, the integrity of knowledge, and the dignity of education.
Pilar Martínez Clares
Professor at the University of Murcia
26 June 2025
Introduction
In recent years, artificial intelligence (AI) has evolved from a technical innovation to a transformative force across all areas of society. Higher education, as a cornerstone of knowledge and innovation, is strongly impacted, facing both challenges and opportunities. Universities face the task of integrating AI into their systems while preserving core educational values like academic integrity, ethics, and equity. This book, Ethical Challenges of AI in Academia: Impact and Implications for Higher Education, brings together experts from diverse backgrounds to explore how AI is changing education on both global and local levels, often referred to as ‘glocal impact’.
This book provides a comprehensive exploration of AI’s impact on higher education. It addresses topics such as personalised learning and the ethical dilemmas surrounding AI-assisted plagiarism, highlighting key issues for both students and educators. Through case studies, theoretical insights, and research, the chapters invite readers to engage with the challenges and opportunities presented by this technology.
The book opens with a focus on the transformative potential of AI in higher education. In Educational Personalisation in the Age of Artificial Intelligence: Opportunities and Ethical Challenges, Jorge Soto Carballo, Antonio Bernal Guerrero, and Antonio R. Cárdenas Gutiérrez explore how AI-powered personalised learning can support critical thinking, creativity, and student autonomy. Their contribution highlights the need for a humanistic and ethically grounded approach that reinforces the educator’s role.
This is followed by The Use of Artificial Intelligence in Higher Education Institutions in Portugal – Ethical Challenges and Opportunities, where Ana Pedro and Lucília Nunes examine how Portuguese universities are responding to the rapid emergence of AI. They reflect on institutional strategies, the impact of new European legislation, and the role of critical thinking in shaping ethical academic practices.
The following chapters focus on AI’s impact on ethics and integrity in academia, particularly in areas such as authorship, plagiarism, and academic standards. Silvana Stremel and Jefferson Mainardes, in Artificial Intelligence in the Literature Review: Ethical Issues, discuss the growing use of AI tools in literature reviews, stressing the importance of transparency, human oversight, and the development of ethical guidelines. Meanwhile, in IAgiarism: Ethical and Academic Challenges in the Age of Artificial Intelligence, Eva María Espiñeira-Bellón and María Cristina Pérez-Crego analyse the phenomenon of AI-assisted plagiarism. Drawing on research conducted in a Galician university, they propose preventive strategies including student training, detection tools, and pedagogical reform.
In Scientific Retractions: Historical Evolution, Ethical Challenges and the Role of Artificial Intelligence, Jesús Miguel Muñoz Cantero, Ana M.ª Porto Castro, M.ª Josefa Mosteiro García, and Enelina Mª Gerpe Pérez explore how AI is reshaping the retraction process in academic publishing. They highlight its role in detecting misconduct and improving transparency while addressing broader systemic challenges.
This analysis is followed by Excellence and Academic Integrity in the Age of Artificial Intelligence: An Ibero-American Perspective, where Jean G. Guerrero-Dib, Luz H. Godina-Silva, and Ana C. Muñiz-Pérez examine institutional policies across Ibero-American universities and propose strategies to strengthen academic integrity in the digital era.
As the book progresses, it explores how AI is transforming teaching innovation, academic communication, and evaluation. In Generative AI as a Catalyst for Innovation and Teaching Improvement: Challenges and Potentialities, Eva María Olmedo Moreno and Jorge Expósito López highlight how GenAI is influencing curriculum design, pedagogical approaches, and regulatory adaptation in university classrooms. Rubén Comas-Forgas, Alex Glynn, and Carmen Touza Garma, in The Impact of Generative AI on Academic Texts: Changes in Scholarly Communication and Integrity, analyse how generative technologies are reshaping academic writing, balancing democratisation with concerns over linguistic standardisation and ethical authorship.
A complementary perspective is offered in Criteria for Assessing the Impact of Generative AI on Students’ Dissertation Defences, by Cinta Gallent-Torres, Mercè Morey López, and Pilar Ezpeleta-Piorno. The authors propose criteria to detect the influence of AI in students’ oral presentations and promote strategies to safeguard authenticity in academic discourse.
Details
- Pages
- XXVIII, 352
- Publication Year
- 2026
- ISBN (PDF)
- 9783631941270
- ISBN (ePUB)
- 9783631941287
- ISBN (Hardcover)
- 9783631941263
- DOI
- 10.3726/b23085
- Language
- English
- Publication date
- 2026 (March)
- Keywords
- Artificial intelligence academic integrity higher education ethics authorship educational innovation teaching digital transformation
- Published
- Berlin, Bruxelles, Chennai, Lausanne, New York, Oxford, 2026. xxviii, 352 pp., 15 fig. b/w, 23 tables.
- Product Safety
- Peter Lang Group AG
Biographical notes
Jesús Miguel Muñoz Cantero (Volume editor)
Ana M.ª Porto Castro (Volume editor)
Eva M.ª Espiñeira Bellón (Volume editor)
M.ª Josefa Mosteiro García (Volume editor)
Jesús Miguel Muñoz Cantero is a Professor of Education at the University of A Coruña. His research focuses on academic integrity, digital ethics, and educational innovation. Ana M.ª Porto Castro is a Professor of Education at the University of Santiago de Compostela and the coordinator of the IDEA research group "Investigation, Educational Diagnosis and Evaluation". Eva M.ª Espiñeira Bellón is a Professor of Education at the University of A Coruña. Her research focuses on evaluation and educational quality, academic plagiarism, and academic integrity. M.ª Josefa Mosteiro García is a Professor of Education at the University of Santiago de Compostela. Her main lines of research are academic integrity, gender and diversity, and equity and inclusion in education.
