By Dr. Jasmin (Bey) Cowin
For years, artificial intelligence in education was discussed primarily as a future possibility. Policymakers debated ethical frameworks, technology companies promoted classroom transformation, and educators speculated about the impact of generative AI on teaching and learning. Yet between 1 and 17 May 2026, something significant occurred across Europe: AI in education ceased to be theoretical. Ministries, teachers, researchers, and school systems moved from discussion into implementation. What emerged across the European educational landscape was not a single “European model” of AI integration. Instead, a fragmented but highly revealing set of national responses emerged, shaped by local pedagogical traditions, political cultures, assessment systems, and anxieties about truth, labor, and educational authority.
Current developments in 2026 demonstrate that Europe is entering a new phase in which artificial intelligence is no longer treated merely as educational technology. It is increasingly understood as a governance issue, a curricular issue, a labor issue, and perhaps most importantly, a question about where human judgment should remain situated once systems capable of imitating aspects of reasoning and authorship enter ordinary institutional life.
Delegated Agency, Automata and the Game of Life
European societies have repeatedly imagined artificial forms of intelligence and delegated agency long before machine learning existed. Ancient Greek mythology described Talos, the bronze automaton said to guard Crete by circling the island and attacking approaching ships. Medieval Jewish traditions imagined golems animated through language and ritual. Renaissance engineers built mechanical automata designed to imitate life and movement. Twentieth-century computational theorists later approached similar questions through mathematics, cybernetics, and computation. John von Neumann explored the possibility of self-replicating automata and universal constructors, arguing that machines might eventually reproduce aspects of biological organization. Alan Turing proposed that machines could simulate human reasoning processes sufficiently well to make the distinction between human and artificial intelligence increasingly unstable in practice. Norbert Wiener’s cybernetics research examined feedback, control, and communication in both animals and machines, helping establish the conceptual foundations for later artificial intelligence research. By the late twentieth century, artificial life researchers such as Christopher Langton and systems like Conway’s Game of Life explored how complex and seemingly lifelike behavior could emerge from relatively simple computational rules. The technologies changed across centuries. The underlying fascination remains surprisingly consistent.
What distinguishes the present moment is not the existence of that ambition, but its robust movement into public institutions. Systems capable of generating language, evaluation, and synthetic knowledge are now entering schools at scale. Education has therefore become one of the first democratic institutions forced to negotiate questions that earlier centuries could largely leave to mythology, philosophy, and speculation.
Denmark and the Defense of Pedagogical Identity
One of the most intellectually important discussions emerged from Denmark, where researchers and school leaders convened in Søborg under the auspices of the Villum Foundation to discuss artificial intelligence in primary education (Villum Foundation, 2024). Rather than focusing narrowly on technical implementation, participants raised a deeper concern: whether imported AI systems align with Danish educational philosophy itself. Researchers argued that Denmark had spent disproportionate energy discussing AI-assisted cheating while devoting insufficient attention to AI’s pedagogical possibilities. More importantly, they advocated what they termed a “Danishification” of AI tools and teaching materials (Villum Foundation, 2024).
The Danish discussion implicitly rejects the assumption that AI systems are culturally neutral educational instruments. Instead, it recognizes that AI carries embedded pedagogical assumptions concerning efficiency, authority, cognition, and acceptable forms of knowledge production. Denmark’s response suggests that educational systems may increasingly seek to domesticate AI according to national educational traditions rather than passively adopting globally standardized technological models. The concern also reflects a deeper historical anxiety visible throughout European responses to artificial intelligence. Stories about artificial beings, from golems to automata, were rarely only about technical creation. They were often stories about control, delegated agency, and the fear that systems designed for human purposes might gradually reorganize the environments around them.
Greece: Accountability, Oversight, and Educational integrity
While many nations continue publishing broad ethical recommendations concerning AI, Greece took a more operational approach by issuing binding national rules governing AI use in schools (Athens Times, 2026). The framework, jointly developed by the Ministries of Education and Digital Governance, established one of Europe’s most concrete school-level AI governance structures to date. Every Greek school must now appoint an “AI Use Coordinator” responsible for oversight of AI implementation, student data protection, and institutional guidance. The framework also prohibits deepfake creation, fabricated citations, and fully automated assessment of students or teachers. AI use during written examinations is restricted unless specifically authorized by the teacher (Athens Times, 2026).
The prohibition against fully automated assessment deserves particular attention. At a time when educational technology companies increasingly market AI grading systems as scalable solutions to teacher workload, Greece’s framework articulates a fundamentally different position: assessment remains a human professional responsibility.
It would be excessive to describe this framework as a direct continuation of classical democratic philosophy. Greek policymakers themselves largely framed the issue in terms of accountability, oversight, and educational integrity. Nevertheless, the debate overlaps with older political concerns that have long existed within democratic societies: who exercises judgment, how authority remains accountable, and whether decisions affecting citizens can legitimately emerge from systems that remain difficult to scrutinize publicly.
Hungary’s National AI Rollout
Hungary adopted perhaps the most ambitious curricular implementation model during this period. Since January 2026, AI has become a compulsory subject in vocational secondary schools, and all primary and secondary schools are expected to introduce AI education before the end of the year. Educational forums across Hungary increasingly described AI as “unavoidable,” with teachers expected to evolve from knowledge transmitters into guides and coaches.
This rhetoric mirrors global conversations about the future role of educators in AI-mediated classrooms. Yet Hungary’s rapid implementation also exposes a critical tension visible across Europe: educational systems are attempting large-scale AI integration before many teacher preparation systems have adequately adapted. The transition from teacher-as-expert toward teacher-as-facilitator is often described rhetorically as innovation. However, it also requires substantial retraining, curricular redesign, assessment restructuring, and professional support systems. Without such structures, teachers risk being positioned inside expectations they were never institutionally prepared to meet.
Ireland and the Assessment Crisis
In Ireland, concerns about AI and educational assessment moved decisively into the policy arena. The government established its first national AI-in-schools advisory taskforce bringing together teachers’ unions, school management organizations, digital agencies, and AI specialists (Gov. ie, 2026). The immediate focus of the taskforce is state-certified assessment, particularly coursework contributing to Leaving Certificate grades. Irish teacher unions framed the current situation starkly, describing AI as potentially creating “a license to cheat” (Gov. ie, 2026).
Yet the Irish situation reveals a larger systemic problem extending well beyond plagiarism. Traditional educational assessment systems were built upon assumptions that written production reliably reflected individual cognition and authorship. Generative AI destabilizes that assumption. Consequently, institutions across Europe are increasingly reconsidering assessment itself. Oral defenses, process-oriented assignments, multimodal demonstrations, reflective metacognitive tasks, and AI disclosure statements are becoming more common because educators recognize that the assessment crisis is not temporary. It is structural.
Educational institutions developed during periods in which authorship, documentation, and cognition were more easily linked together. Generative AI complicates all three relationships simultaneously. Schools are now forced to reconsider what exactly they are evaluating once machines can imitate fluency, reasoning, and stylistic competence at scale.
Italy and the Teacher Preparedness Gap
Italy’s May 2026 survey data revealed one of the clearest disconnects in European education: students are adopting AI substantially faster than schools are preparing teachers. According to the survey, 81% of Italian students already use AI tools in their schoolwork, yet only 44% encounter formal AI integration within classrooms. Even more concerning, only 34% of teachers reported feeling adequately prepared to teach AI-related competencies, with preparedness levels dropping further in public schools. Italy’s €100 million PNRR-funded teacher training initiative represents a recognition that AI literacy cannot remain optional for teacher education programs and educational institutions.
However, the Italian case also illustrates a broader educational reality. Students increasingly encounter AI socially, informally, and algorithmically outside school systems. Educational institutions are no longer introducing AI into student life. Rather, they are attempting to respond to technological practices students have already normalized independently.
Malta’s AI Literacy as ‘Civic Infrastructure’
Perhaps the most internationally visible initiative emerged from Malta, where the government partnered with OpenAI to provide free one-year ChatGPT Plus access to all citizens and residents aged fourteen or older following completion of a national AI literacy course (Euronews, 2026). The initiative reframes AI literacy not as elite technical specialization but as a broad civic competency akin to digital literacy initiatives of previous decades. The literacy course, developed by the Malta Digital Innovation Authority together with the University of Malta, focuses on responsible AI use, limitations of AI systems, and practical understanding accessible to nontechnical users (Euronews, 2026).
Malta’s initiative may represent an early prototype for national AI citizenship models. Whether such approaches strengthen democratic AI literacy or deepen public dependence on proprietary platforms remains uncertain. Nevertheless, the symbolic significance is considerable: AI access is increasingly being framed as a matter of national competitiveness and social participation. Historically, democratic societies treated literacy as necessary for civic participation because citizens needed to navigate laws, bureaucracies, and public institutions. Malta’s initiative suggests that some governments increasingly view AI literacy in similar terms. Citizens are now expected to interact with systems capable of generating explanations, summaries, recommendations, and synthetic expertise as part of ordinary social life.
The Netherlands, Holocaust Disinformation and Synthetic Media
The Netherlands revealed perhaps the most disturbing educational development of the month. A survey of 190 history and social studies teachers found widespread exposure to AI-generated Holocaust disinformation within classrooms (Euronews, 2026). Teachers reported fabricated images, manipulated videos, and social media content undermining established historical evidence.
One classroom exercise proved especially revealing. Students shown two Auschwitz photographs frequently misidentified the authentic image as AI-generated (Euronews, 2026). This phenomenon reflects a profound epistemological challenge for education. AI-generated synthetic media increasingly destabilizes traditional assumptions concerning authenticity, documentation, and evidence itself. Media literacy can no longer be separated from AI literacy. The Dutch government responded with additional Holocaust education funding and museum-based programming. Yet the larger educational issue extends far beyond one historical topic. Schools now confront a generation of learners navigating digital ecosystems where truth itself is increasingly contested through synthetic media.
Europe has long imagined artificial representations capable of imitating reality, from automata and forged texts to mechanical simulacra and artificial beings. What generative AI changes is not the existence of synthetic representation, but its scale and accessibility. Fabricated authority no longer belongs primarily to myth, philosophy, or isolated deception. It increasingly enters classrooms through ordinary digital infrastructure.
Romania and the Defense of Teacher Authority
Romania’s formal position presented at the EU Education Council emphasized that AI should support teachers rather than replace them (Bursa. ro, 2026). Romanian policymakers endorsed AI for reducing administrative workload, enabling personalized learning, and stimulating creativity, while simultaneously insisting that teacher autonomy and professional authority remain central to education (Bursa. ro, 2026).
This position reflects a wider European educational philosophy that differs significantly from some technology-sector narratives emphasizing automation and scalability. Across many European contexts, the teacher is still viewed as a fundamentally human intellectual and ethical actor whose role cannot be replaced or mechanized by an algorithm .
Europe’s Emerging Educational AI Landscape
Taken collectively, the developments of May 2026 reveal several emerging continental patterns.
· First, Europe is moving from abstract AI ethics toward operational educational governance. Ministries are no longer merely publishing recommendations; they are building enforcement structures, training systems, and implementation frameworks.
· Second, educational assessment has become the central institutional pressure point. Questions surrounding authorship, originality, and human cognition now shape nearly every AI discussion within schools and universities.
· Third, teacher preparation systems are struggling to keep pace with student AI adoption. This gap may become one of the defining educational equity challenges of the next decade.
· Finally, Europe appears increasingly committed to preserving human oversight within AI-mediated educational systems. Even highly pro-AI initiatives continue emphasizing professional judgment, pedagogical autonomy, and institutional accountability.
In the author’s opinion, the educational sector exposes these tensions particularly clearly because schools sit directly at the intersection of cognition, development, institutional authority, and democratic accountability. These concerns also intersect with broader questions surrounding algorithmic influence, synthetic authority, and the growing role of AI systems in shaping human behavior and institutional life. The author has explored related themes elsewhere, including the psychological and behavioral implications of AI companions in The algorithmic metamorphosis: When AI companions transform into mental health predators (Cowin, 2025) and the cultural and ideological dimensions of AI development in “Narwhals, Unicorns, and Big Tech’s Messiah Complex: A transdisciplinary allegory for the age of AI” published in The Journal of Systemics, Cybernetics and Informatics (Cowin, 2025).
The European AI Act and Education
The European Union AI Act prohibits emotion recognition within educational institutions. Yet the practical boundaries quickly become unstable. In my policy brief “The European AI Act and its implications for New York State higher education institutions,” as a Richard
P. Nathan Public Policy Fellow (2024-25 ), I describe EU AI Act prohibited pracices and scenarios such as adaptive learning systems adjusting lesson difficulty according to inferred frustration or disengagement or language-learning software that changes pacing based on hesitation patterns or facial expression analysis. Consider examination proctoring systems using computer vision to identify “suspicious” behavior during assessments. Where exactly does pedagogical adaptation end and emotional inference begin? At what point does behavioral modeling become psychological surveillance?
The ambiguity is not simply regulatory. It emerges from the nature of the systems themselves. Many of the educational conflicts emerging across Europe appear to stem from this instability of categories. Assessment systems built around assumptions of individual authorship confront models capable of generating fluent synthetic text. Media literacy frameworks designed for older information environments confront AI-generated historical disinformation and synthetic imagery. Teacher training systems struggle to adapt while students normalize AI socially and informally outside institutional structures altogether. Even the distinction between support tool and cognitive authority increasingly becomes difficult to stabilize in practice. This may partly explain why European educational responses remain fragmented despite shared regulatory ambitions. Greece emphasizes institutional oversight and human accountability. Denmark focuses on preserving pedagogical traditions. Ireland confronts assessment legitimacy. Malta frames AI literacy as civic infrastructure. The Netherlands increasingly confronts epistemological instability surrounding evidence itself. These are not entirely separate problems. They are different institutional expressions of the same underlying transition.
The European Union AI Act attempts to create comprehensive governance structures around technologies whose capabilities continue evolving faster than the institutional categories designed to regulate them. The problem is not merely speed, although the velocity mismatch is real. It is that generative AI destabilizes assumptions educational institutions were built upon in the first place: stable authorship, interpretable reasoning, trustworthy documentation, and clearly bounded human judgment.
Ordinary Institutional Life vs AI
Earlier debates surrounding artificial intelligence often remained speculative because the systems themselves remained relatively distant from ordinary institutional life. That distance no longer exists. Schools, universities, ministries, and examination systems are now being forced to operationalize questions that until recently could remain largely philosophical.
· What counts as understanding?
· What counts as evidence?
· What counts as authorship?
· What forms of judgment remain meaningfully human once cognition itself becomes partially externalized into computational systems?
In the author’s opinion, the deeper tension emerging across European education is not simply whether AI can reproduce convincing language or competent performance. It is whether educational institutions built around human development can continue distinguishing between systems that statistically model patterns and human beings who learn through embodiment, intuition, social experience, failure, memory, unpredictability, and physical presence in the world.
Hector Levesque’s old concern remains relevant here: statistical learning can resemble understanding long before we know whether any underlying causal structure has actually been grasped. Yet education has never been reducible to prediction alone. Human learning is uneven, nonlinear, emotional, embodied, and deeply entangled with biological and social life. Students do not merely compress information. They improvise, misunderstand, intuit, imagine, hesitate, contradict themselves, and occasionally produce genuinely novel thought that exceeds the structures they inherited.
This may also explain why so many European educational systems continue insisting that teachers remain central even as AI integration accelerates. The teacher increasingly becomes not simply a transmitter of information, but a guide, facilitator, interpreter, and institutional guardrail within environments saturated by synthetic cognition. In classrooms where generated fluency can imitate expertise, teachers may become responsible for preserving distinctions between performance and understanding, information and judgment, simulation and lived experience.
Generative AI systems can reproduce fragments of reasoning and expertise with extraordinary effectiveness, yet they do so without biological experience, mortality, vulnerability, or physical participation in the world they describe. The outputs may increasingly resemble understanding while emerging from fundamentally different processes.
Douglas Adams once wrote that “a tautology is something that if it means nothing, not only that no information has gone into it but that no consequence has come out of it.” Modern AI training appears almost tautological in structure, systems learning from the accumulated traces of human culture and language to generate further synthetic traces. But the circle is not empty because human life itself is not empty. The data contains history, embodiment, conflict, imagination, intuition, error, and lived experience compressed into symbolic form.
In the author’s opinion, this may become the central educational question of the AI era. Not whether machines can imitate aspects of cognition, but whether educational systems can continue recognizing and cultivating forms of human creativity, judgment, and understanding that emerge precisely from the unpredictability, embodiment, and irreducibility of human life itself.
Contact me through LinkedIn www.linkedin.com/in/drjasminbeycowin – I explore the intersection of Nicomachean Ethics, artificial intelligence, and education, using a transdisciplinary approach to examine how educational systems may adapt to technological transformation while preserving human judgment, ethical reasoning, and democratic accountability.
References
Athens Times. (2026, May). AI in Greek schools: First national framework.
Bursa. ro. (2026, May 14). Romania supports the use of artificial intelligence in schools, but teachers remain irreplaceable.
Cowin, J. (2025, December 25). The algorithmic metamorphosis: When AI companions transform into mental health predators. Stankevicius.https://stankevicius. co/tech/the-algorithmic-metamorphosis-when-ai-companions-transform-into-mental-health-predators/
Cowin, J. (2025). Narwhals, unicorns, and Big Tech’s messiah complex: A transdisciplinary allegory for the age of AI. The Journal of Systemics, Cybernetics and Informatics, 23(7), 146–151. https://www. iiisci. org/journal/sci/Contents. asp?Previous=#/
Cowin, J. (2025, November 6). The European
AI Act and its implications for New York State higher education institutions. Rockefeller Institute of Government. https://rockinst. org/issue-area/the-european-ai-act-and-its-implications-for-new-york-state-higher-education-institutions/
Gov. ie. (2026, April). AI in schools external advisory taskforce to be established.
Levesque, Hector J. (2017). Common sense, the Turing test, and the quest for real AI. Cambridge, Massachusetts. ISBN 978-0-262-53520-5. OCLC 960940230.
OpenAI signs deal with Malta to give every citizen free ChatGPT Plus for one year.
