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The rapid development of these capabilities underscores why we need a thoughtful approach
In recent years, artificial intelligence has moved from research laboratories and technology companies into nearly every aspect of our work and lives. Initially, the focus was primarily on its capabilities: how quickly it can generate text, prepare a summary, write program code, or assist with data analysis. Today, we are entering a new phase in which technological enthusiasm is increasingly accompanied by questions about responsible use and the impact on education, research, work, and society.
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What Should We Do When Humans and Artificial Intelligence Disagree?
On the final Monday in August, just before the beginning of the school year and, soon afterwards, the academic year, our desks are covered with timetables, course delivery plans and reflections on how to assess students’ knowledge. This year, these considerations have probably been joined by the question of how to proceed in the age of generative artificial intelligence. Are the higher grades awarded to students actually justified? Are suspicions raised by AI-content detectors sufficient grounds for further action? What should we do when AI reaches a different conclusion from ours—for example, about teaching methods or feedback? Who has the final say?
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Increasingly Capable AI, Increasingly Demanding Evaluation
AI is becoming increasingly capable in learning, research, employment, and the independent execution of tasks, which brings to the forefront the question of how to evaluate its results and maintain human accountability. This newsletter presents new approaches to evaluation and AI literacy, the use of AI as a research collaborator, and its impact on the labor market. It also raises questions about identifying content created by AI and the risks posed by increasingly autonomous systems. Finally, it highlights a somewhat different use of AI—in the reinterpretation of works of art.
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AI in the context of university practices, youth protection and the issue of supervision
Artificial intelligence in education is no longer simply a question of using tools. Rules, trust, security, institutional accountability and the question of who controls the systems that are having an ever-greater impact on learning, work and decision-making are coming to the fore.
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The latest issue of PublIKaTor has been released
This summer, we are once again publishing a new issue of PublIKaTor, in which we have compiled key information about the operations of the UL Digital Center during the first half of the year and begun planning activities for the second half of the year.
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Four new microMOOCs on the use of AI for higher education educators will be available from July 20th
The Digital UL Centre is launching four standalone online micro-MOOCs on the pedagogically sound, safe and responsible use of artificial intelligence. They are aimed at university lecturers, research staff, teaching assistants and other staff involved in teaching, preparing teaching materials or assessing students’ knowledge.
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From the classroom to the laboratory: AI takes on new roles
AI is increasingly becoming part of learning, research, decision-making and everyday life, but its benefits are accompanied by significant questions regarding responsibility, fairness and trust. This newsletter explores how students are using AI, how universities are developing guidelines and new pedagogical approaches, and how AI is transforming academic work. It also highlights linguistic and global inequalities, the potential for biased or misleading results, and privacy concerns. Examples of AI’s use in healthcare and sport are also presented.
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The RE:ABCD method for thoughtful planning and redesign of teaching
For many higher education lecturers, the summer months are a time to review their courses, prepare new versions and consider which teaching activities it would be sensible to adapt before the start of the new academic year. RE:ABCD – a method for planning individual teaching activities, revamping a teaching module or comprehensively updating a course, which we have developed at the UL Digital Centre – can assist them in this.
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There is not yet a magic orb to solve all the issues surrounding the use of AI in education
News reports from the past two weeks suggest that the debate on artificial intelligence in education is still moving away from individual tools. The focus is on questions such as what pupils and students should know, how institutions should set limits on permissible use, how to deal with the burden of testing and assessment, and whether schools and universities have sufficient staff, expertise and infrastructure to make informed decisions.
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AI and a balance between comfort, judgement and responsibility
Artificial intelligence is increasingly moving from individual tools into the infrastructure of everyday decision-making. It is no longer simply a question of whether it can help us write a text, summarise material or find an answer. A more difficult question is coming to the fore – what happens when we start to rely on it in situations where we should be developing our own judgement, understanding and responsibility? Below is a round-up of news from the last two weeks regarding the use of AI in education and beyond.
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AI Between Trust, Evaluation and Human Judgement
In recent days, news about artificial intelligence in education has centred on a question that universities can no longer put off: how to use AI in a way that helps students learn, without losing sight of what a university education is meant to develop – independent thinking, professional judgement, an understanding of sources, the ability to argue a case, and responsibility for one’s own work.
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Artificial intelligence is changing the way we think, learn and work
In this edition of the AI Newsletter, we present the latest news on how artificial intelligence is transforming the ways in which research, learning, assessment and work are carried out in higher education and wider society. Among other things, we highlight concerns regarding the impact of AI on research habits and critical thinking, changes in assessment and academic integrity, the growing importance of AI literacy, and the shift by universities from individual trials towards systematic policies on the use of AI. We also present examples of AI integration into course redesign, discussions on future skills and working in the age of AI, and current social and technological trends – from robotaxis in Ljubljana to the development of autonomous AI systems and smaller, specialised language models.
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AI between regulation, new tools and questions about the value of knowledge
Over the past two weeks, developments in the field of artificial intelligence in higher education have intensified at the intersection of three forces. On the one hand, universities are testing new tools that promise personalisation and a reduction in the workload of teaching staff; on the other hand, they are facing increasingly vocal concerns from teaching staff. At the same time, the final trilogue on the AI Omnibus has collapsed at European level, meaning that the deadline of 2 August 2026 for the full implementation of the AI Act remains in force and will also have a direct impact on higher education practice. In Slovenia, reflection continues on what AI means for the quality of knowledge and competences; at the same time, visitors can view an interesting exhibition on five decades of AI development in the country, which concluded on 3 May with guided tours in English.
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Artificial Intelligence in Higher Education: From Specific Practices to Systemic Changes
Artificial intelligence (AI) in higher education is increasingly acting as a catalyst for change that extends beyond the use of individual tools. It raises broader questions about the nature of learning, teaching, and knowledge, and is gradually transforming pedagogical practices, the role of the teacher, and expectations of students. Questions of responsibility, meaningful use, and the development of competencies that will enable high-quality education in the long term are coming to the forefront. This newsletter features a selection of current reflections and concrete examples—ranging from pedagogical and research practices to the functioning of the academic community and broader social and political contexts—which together illustrate how UI is gradually establishing itself within the university landscape.
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Decision-making regarding GenAI is shifting to the systemic level through questions of rules, responsibilities, and the significance of knowledge
On Easter Monday, which symbolically opens the door to new beginnings, we are publishing an overview of the latest developments in the field of generative artificial intelligence. Over the past two weeks, developments in AI in education have shifted from the use of individual tools to systemic changes that directly impact higher education. We no longer view (Gen)AI merely as a tool for writing or summarizing, but rather as a set of systems, business models, energy requirements, and rules (both pedagogical and legal) that are dictating how universities must reorganize their work.
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When AI Becomes Part of Everyday Life: What Does This Mean for Learning and Teaching?
In higher education, artificial intelligence has evolved from an intriguing novelty to an everyday tool for students and educators in a very short time. Consequently, questions that go beyond technology are increasingly coming to the forefront: how does AI influence the understanding of knowledge, how does it change the ways of learning and teaching, and how should universities respond to it in terms of policies, practices, and values? Recent publications indicate that the higher education sector is undergoing a period of intense reflection and adaptation.
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How Artificial Intelligence Is Being Integrated into Higher Education Curricula, Infrastructure, and Academic Culture Around the World and in Slovenia
Over the past two weeks, it has become even clearer in the field of artificial intelligence in higher education that the focus is shifting from the question of whether to use AI to the question of how to integrate it into the curriculum, infrastructure, and academic culture. Internationally, three trends stand out: the institutionalization of AI literacy, the transformation of assessment, and an increasing emphasis on critical use. In Slovenia, however, the primary focus is on strategically positioning AI within the national development framework and gradually introducing concrete solutions into the university support environment.
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AI in Advertising, Education, and Academic Evaluation
Over the past two weeks, the issue of stability and critical use has come to the forefront of AI usage, as new developments and changes have forced us to recognize that behind every AI model there are companies and people.
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Artificial Intelligence in Education: From Pedagogical Decisions to Social Consequences
Today’s AI Newsletter provides an overview of current discussions, research, and initiatives that shed light on how educational institutions, teachers, and students are responding to these changes. Special attention is given to pedagogical decisions, institutional responsibility, and the development of competencies for the future. We also broaden our perspective to include broader societal examples that help us understand the impact of artificial intelligence beyond the classroom.
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Artificial intelligence in education is putting us through a pedagogical stress test
Over the past two years, artificial intelligence has entered higher education with a intensity that goes beyond typical technological shifts. Not merely as a new tool, but as a force that challenges established pedagogical practices, power dynamics, and implicit expectations about what we even consider knowledge in the academic sphere. The articles collected in this newsletter show that the debate is shifting away from the question of whether AI is good or bad, and increasingly toward what it reveals about our own educational models.
