The rapid development of these capabilities underscores why we need a thoughtful approach

News reports from recent weeks also reflect this shift. In addition to presentations of new models and technological achievements, an increasing number of experts are discussing how artificial intelligence is changing the way we learn, create knowledge, and make decisions. This brings to the forefront questions such as how to prepare students for the future of work, what role teachers and researchers will play, and how to ensure that the development of artificial intelligence is directed toward the good of people and society.

One of the most significant developments in recent weeks was the Evolution.AI 2026 conference, which highlighted the shift from research and pilot projects to an increasing number of practical applications of AI. Among the central themes of the conference, which took place on September 11, were the practical application of artificial intelligence, the development of trustworthy solutions, the safe use of technology, and the question of how to ensure that the development of artificial intelligence benefits people, organizations, and society at large. The event’s key themes indicate that the discussion is increasingly shifting from technological capabilities to questions of practical, safe, and trustworthy use.

In higher education, there is a growing consensus that artificial intelligence is no longer a topic of the future, but part of the present. The author of the article “Now Is the Time to Plan and Prepare Your Students and Colleagues for Workplace AI” points out that the time to act is now, not only once the technologies have matured or when definitive guidelines for their use become available. In his view, educational institutions must begin incorporating artificial intelligence into curricula, assignments, and activities today, as students will be working in an environment where AI literacy will become an increasingly important part of professional competence. He places particular emphasis on developing creative and critical problem-solving skills and on reflecting on how artificial intelligence is changing the ways people work and make decisions across a wide range of professions.

A similar perspective is offered by the author of the article “Beyond Policing AI: Reflections on Teaching, Assessment, and Pedagogy in Social Science Education”, published in the journal Frontiers in Education. She points out that the issue of artificial intelligence in higher education is not merely a matter of controlling its use, but above all an opportunity to rethink what students should develop during the educational process. She emphasizes competencies such as critical thinking, reflexivity, analytical thinking, dialogue, and collaboration, which artificial intelligence cannot simply replace. In her view, teachers should pay more attention to pedagogical approaches that encourage active student participation, deep learning, and the development of more complex skills. Artificial intelligence can also serve as a starting point for analysis, critical evaluation, and further exploration, rather than merely as a tool for obtaining quick answers. 

That said, it is important to distinguish between expectations and the actual effects of artificial intelligence on education. The article “The ‘Nonexistent’ Research on AI’s Benefits for Education” points out that despite the rapid adoption of artificial intelligence tools in higher education, there is still a lack of sufficient high-quality, independent research on their impact on teaching and learning outcomes. Research conducted to date paints a mixed picture, with experts noting that many claims about the effectiveness of artificial intelligence cannot yet be reliably confirmed. Due to the rapid development of the technology, researching its effects is particularly challenging; therefore, some researchers advocate for smaller-scale, faster studies that would monitor and evaluate the use of these tools as they are being implemented. For higher education institutions, this means that when deciding on the use of artificial intelligence, it is important to consider the available evidence and to approach individual use cases thoughtfully, rather than uncritically accepting promises of effectiveness.

A similar reflection on the responsible use of artificial intelligence in research is also offered in the article “We’re asking the wrong question about AI in research”. The author points out that the debate often focuses on whether artificial intelligence was used in research, rather than on how it was used and whether the risks were adequately managed. Artificial intelligence is already integrated into numerous everyday research tools—from literature searches and data analysis to writing code and preparing and editing texts. However, not all uses carry the same level of risk: using artificial intelligence to improve readability or organize information differs significantly from its use in formulating interpretations, evaluations, or research conclusions. The author therefore emphasizes the importance of transparency, accountability, human oversight, and academic judgment. For researchers and higher education institutions, this means that when establishing rules for the use of artificial intelligence, it is not enough to simply define what is permitted and what is prohibited; rather, it is also necessary to understand the purpose of the application, its consequences, and to ensure appropriate mechanisms for responsible conduct.

The UNESCO publication “The Algorithm in the Room: Seeing and Confronting the Implications of AI for the Future of Education” brings together 26 contributions from experts in various fields and raises broader questions about the future of education in the age of artificial intelligence. The publication emphasizes that AI is not merely a new tool, but a technology that influences the way we learn, teaching, assessing knowledge, and critical thinking. In this context, it highlights the importance of critical thinking, reasoned debate, dealing with ambiguity, and the role of the teacher—a role that cannot simply be automated. Special attention is also given to the question of how to preserve human judgment and autonomy at a time when algorithms are increasingly involved in the creation, evaluation, and transmission of knowledge. UNESCO therefore calls for the thoughtful guidance of artificial intelligence use in line with educational goals and for teachers and students not to remain mere users of technology, but to actively participate in shaping its future.

The article “Three Pathways for Your Teaching: GenAI, Active Learning, and Large Classes” emphasizes that artificial intelligence alone will not improve teaching. The authors present three areas in which educators can develop their teaching: the thoughtful use of generative artificial intelligence, the promotion of active learning, and effective approaches for working with larger groups of students. They note that none of these approaches represents a one-size fits-all solution but rather requires thoughtful adaptation to the specific learning environment, subject matter, and students’ needs. The key message of the article is that technology should support pedagogical goals, not replace them.

Similarly practical in its approach is the handbook “The AI Activities Guide for Teachers”, which offers concrete activities for integrating artificial intelligence into the learning process. The emphasis is not merely on the use of technology, but on active student participation, the exploration of different perspectives, and the critical evaluation of results generated by artificial intelligence. AI is thus presented as a starting point for discussion, exploration, and creation, rather than as a source of definitive answers. The guide offers numerous examples of learning activities that can help teachers plan meaningful and inclusive uses of artificial intelligence in the classroom.

The study “Predictors of the Ethical Use of Generative Artificial Intelligence in Higher Education”, conducted among 980 students, shows that the ethical use of generative artificial intelligence is linked to both individual competencies and the institutional environment. Key factors include academic integrity and transparency, AI literacy, critical evaluation of content, data protection, and institutional guidelines and ethics education. The authors therefore emphasize the importance of clear institutional rules, the systematic integration of ethics into education, and the development of a critical and responsible attitude toward the use of artificial intelligence.

In September 2026, UNESCO launched a global consultation on education in the age of artificial intelligence. In it, UNESCO invites experts, researchers, government representatives, and other stakeholders to discuss draft documents addressing key issues related to the governance of artificial intelligence in education. The feedback collected will contribute to the development of future policy UNESCO policy recommendations in this area. The consultation will run through October 2026, with the final set of recommendations expected in 2027.

Another interesting initiative for developing teachers’ competencies is Google’s AI Educator Series, which offers teachers new training on the use of artificial intelligence in education. The series includes practical content and use cases designed to help teachers understand and integrate artificial intelligence into their work. The initiative thus represents yet another example of the growing emphasis on the systematic development of teachers’ competencies for the meaningful, critical, and responsible use of artificial intelligence.

In Slovenia, a case involving the use of artificial intelligence during brain tumor surgery also attracted attention. The technology served as an additional “set of eyes” for doctors in analyzing data and as a decision-making aid during the complex procedure. The final decisions were still made by the medical team, but the case clearly illustrates how artificial intelligence can support experts in challenging tasks without replacing their knowledge, experience, and professional judgment. 

In the field of drug development, network biology and artificial intelligence are becoming increasingly intertwined. Such approaches enable the analysis of large-scale biomedical data and can help identify therapeutic targets, predict treatment responses, and improve our understanding of complex biological processes. The author emphasizes that the integration of these two fields could make a significant contribution to future drug development and a more precise understanding of diseases. At the same time, he cautions that artificial intelligence predictions cannot replace experimental and clinical validation but should be viewed as a support for the research process.

Similarly, researchers at Cardiff University are developing new artificial intelligence approaches for analyzing complex biological data. As the volume and complexity of data continue to grow, such methods can help researchers identify patterns and better understand biological processes. The researchers emphasize that artificial intelligence can significantly accelerate data analysis and the discovery of new connections that would be more difficult to identify using traditional methods. This example illustrates how artificial intelligence is increasingly being integrated into research as a tool for data analysis and to support scientific discoveries.

These examples show that the greatest value of artificial intelligence does not necessarily lie in replacing experts, but rather in supporting the analysis of complex data and decision making. Precisely for this reason, the rapid development of capabilities also raises the question of whether appropriate safety mechanisms are keeping pace.

Also of interest is the analysis of the impact of artificial intelligence on the labor market, which so far does not indicate a massive reduction in the number of jobs due to AI. At the same time, new jobs are emerging in certain sectors, along with a growing need for skills related to the use of artificial intelligence. Rather than a simple disappearance of jobs, the question of how requirements for knowledge, competencies, and work methods will change is increasingly coming to the forefront. For educational institutions, this is yet another reminder that adapting study programs and developing new competencies will be an important part of preparing graduates for the future.

In the field of self-driving vehicles, the release of the first Slovenian footage of Tesla’s Full Self-Driving system also attracted attention. The footage shows the system in action on Slovenian roads, even in more challenging traffic and weather conditions, and offers concrete insight into the use of artificial intelligence in automated driving. Although the system still requires constant driver supervision—as the driver remains responsible for controlling the vehicle—this example demonstrates how rapidly practical applications of artificial intelligence in transportation are advancing. 

OpenAI has unveiled a new version of its image-generation system, ChatGPT Images. According to the company, the new version brings improvements in accuracy, understanding of instructions, and the quality of the generated visual content. This example demonstrates how rapidly the capabilities of generative artificial intelligence are evolving, even in the field of image creation and editing, and how the boundaries between text-based and visual AI tools are increasingly blurring.

Another significant development is the introduction of the GPT-6 Astra model. OpenAI presents it as its most powerful model to date, with enhanced capabilities for computer science, programming, scientific research, and other demanding professional tasks. The model is also designed to perform complex tasks more independently, signaling a further shift from systems that merely answer questions to systems that can more autonomously assist in getting work done. This news therefore raises questions once again about how work, research, and the everyday use of artificial intelligence will change in the coming years.

Calls for a more cautious approach to the development of artificial intelligence are becoming increasingly common, even among leading figures in the technology industry. Dario Amodei, CEO of Anthropic, has warned in recent days that the development of artificial intelligence capabilities is advancing faster than the development of the safety mechanisms needed to understand and control them. He has advocated for slowing down the development of the most powerful systems and for significantly more independent verification of their safety and reliability. Similar points are highlighted in a report by The New York Times, which raises the question of how to ensure that the rapid development of artificial intelligence capabilities is accompanied by the corresponding development of safety mechanisms, verification methods, and independent oversight. The debate is thus no longer focused primarily on whether artificial intelligence will advance, but rather on how to ensure that technological progress proceeds responsibly and in accordance with broader societal interests.

News reports thus indicate that the initial enthusiasm for artificial intelligence is increasingly giving way to a more mature consideration of when its use makes sense, how to verify its results, and who retains responsibility for final decisions. For higher education, this means, above all, the need for the thoughtful integration of AI, the development of appropriate competencies, and the preservation of human and professional judgment.

As in previous issues of the AI-Newsletter, we invite you to share your experience through a short form if you are experimenting with thoughtful uses of AI in your course, have changed an assignment because of AI or have encountered a dilemma that could also benefit others.

We also invite you to strengthen your AI-literacy competencies through the (currently) four online workshops, which allow you to work independently, at your own pace and at a time that suits you, through topics that have also featured prominently in today’s AI-Newsletter.

Authors: Mateja Bevčič, Eva Kern Nanut, Eva Škraba, Maja Kosmač and Sanja Jedrinović Čufer, University of Ljubljana Center for the Use of ICT in the Pedagogical Process