Introduction
Within the global context of accelerating digital transformation, Artificial Intelligence (AI) has emerged as a central driver in reshaping higher education. It has evolved beyond being merely a research topic or a technological discipline, becoming instead a transversal phenomenon that influences teaching, assessment, research, and academic governance. This essay focuses on how AI is integrated both as an academic tool and as an object of scholarly reflection, with some insights from practices at SNSPA. Particular attention is devoted to the opportunities, challenges, and ethical implications associated with this rapidly developing technology.
1. AI as an Integral Component of the Educational Process
AI is incorporated into the curriculum as a field of study across SNSPA. For instance, in the case of the MA programs of DRIIE, it is notably considered within the Security and Technology master’s programme through the course “Artificial Intelligence in the Cyber Era.” The course adopts a comprehensive approach, enabling students to distinguish
between narrow AI, general AI, and superintelligence, and to explore their applications in the fields of security and defence.
Its objectives are ambitious and multidimensional, such as:
- To assess the ethical, normative, and strategic risks and benefits of AI;
- To develop analytical instruments for understanding global technological trends;
- To cultivate critical and strategic thinking concerning the impact of AI on diplomacy, geopolitics, and international security.
Beyond theoretical exploration, AI is practically embedded in teaching practices through tools such as ChatGPT, Grammarly, Google Cloud, Presentations AI, and ZeroGPT. These are employed in:
- Designing presentations and simulations;
- Generating visual materials, translations, and comparative analyses;
- Conducting interactive seminar activities;
- Supporting formative and summative assessments.
An innovative pedagogical method involves comparing student-generated responses with AI-generated responses during classroom simulations. This technique promotes collaborative learning and enhances students’ critical awareness of AI’s limitations. Scenarios in which AI produces inaccurate information are also discussed, reinforcing the importance of human judgment in the validation of knowledge.
2. AI as a Tool for Research Support
In research activities, AI is primarily regarded as an instrument for improving the efficiency of documentation and preliminary analysis. ChatGPT and Grammarly are used for:
- Stylistic and conceptual revision;
- Identifying preliminary sources and analytical frameworks;
- Testing the viability of research ideas or hypotheses.
Faculty members, however, emphasize that AI cannot substitute human analytical reasoning and that AI-generated outputs must always be verified against established academic sources. To date, no instances of research papers primarily generated through AI have been reported, though scholarly interest in such practices is increasing. Identified advantages include:
- Reduced time spent on documentation and preparation;
- Support in formulating innovative hypotheses and research themes;
- Opportunities to examine the boundaries and limitations of AI as an object of study.
Nevertheless, certain limitations and risks are evident:
- AI-generated content may be inaccurate, incomplete, or biased;
- Responses may vary over time, undermining replicability;
- A lack of transparency persists regarding the processing of user data.
Consequently, the use of AI in research must be approached with methodological prudence and ethical responsibility, as a complement to, rather than a replacement for, rigorous scholarly inquiry.
3. Student Assessment and Academic Ethics in the AI Era
One of the most significant challenges in integrating AI into higher education concerns maintaining fairness and academic integrity in student evaluation. At DRIIE, for instance, faculty members employ tools such as ZeroGPT and ChatGPT to identify AI-generated content in written assignments, particularly within English-language programmes. Detection is more difficult in Romanian-language programmes, as many texts are initially produced in English and subsequently translated. To address these risks, several alternative assessment methods have been adopted:
- Oral defence of essays;
- All books on the table are open for examinations;
- Interactive and simulated evaluation exercises.
Nonetheless, a major institutional vulnerability persists: the absence of an officially assumed university policy regarding the use of AI. In the absence of a regulatory framework, inconsistencies and ambiguities arise, undermining evaluation coherence and eroding trust in academic processes. Furthermore, the lack of clear regulation regarding the legal and ethical status of AI-generated content (e.g., algorithmic plagiarism) underscores the need for an in-depth academic debate and the development of clear institutional guidelines.
4. AI as a Subject of Academic Reflection and International Regulation
A distinctive feature of academic activity lies in its treatment of AI as a strategic object of research and reflection. Postgraduate courses address the geopolitical, normative, and ethical implications of AI, preparing students to:
- Evaluate national and international AI policies;
- Understand the impact of AI on global governance;
- Develop strategic thinking regarding the use of AI in addressing global challenges such as climate change, cybersecurity, and diplomacy.
Significant attention is devoted to ethical considerations such as algorithmic bias, decision-making transparency, and the accountability of both developers and state actors. In this regard, DRIIE contributes to a mature educational vision grounded in responsibility and critical reflection on technological innovation. Simulation-based initiatives, including Model UN exercises and MAE DRI simulations, recreate international deliberations on AI regulation, engaging students in authentic debates concerning the global governance of emerging technologies.
Conclusion
The integration of Artificial Intelligence into the academic activities of SNSPA, reveals a dynamic and evolving process. AI is no longer a mere technological innovation but a systemic challenge that redefines educational practices, research methodologies, assessment criteria, and, fundamentally, the ethical architecture of higher education.
About the author
Ana Maria Costea is a Associate Professor at SNSPA, the Department of International Relations and European Integration (DRIIE). She holds a PhD is International Relations and European Studies and is currently teaching MA courses like: Cybersecurity, International regulations in the cyberspace and regional security. Having several articles already published, she was also the manager from SNSPA of the international project “Building an Innovative Network for Sharing of Best Educational Practices, Incl. Game Approach, in the Areas of International Logistics and Transport”(2019-1-BG01-KA203-062602). Among the results of the project we could name: publication of academic articles, development of courses for students and stakeholders, etc. She is also one of the two founders of “Security and Technology” MA program.
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