The spread of artificial intelligence is reshaping what society regards as valuable knowledge: as AI provides fast and plausible answers, memorized information becomes less important while judgment and decision-making gain value. This perspective was presented by Dr. Dietz Ferenc, president of Gábor Dénes Egyetem, in a recent interview.
Educational response: AI literacy from the start
Dietz argues that schools should develop a common AI literacy from the earliest stages of education. He does not advocate an outright ban on AI in classrooms; rather, students must learn to use these tools and also periodically demonstrate core knowledge without AI assistance. He offered a vivid example: a surgeon constantly consulting ChatGPT during an operation would be unacceptable, but a surgeon who ignores AI-based diagnostics or robotic surgery possibilities would be undesirable as well.
What should universities prepare students for?
The role of universities must change fundamentally: conveying rote information is no longer sufficient. Employers expect graduates to apply knowledge in unexpected situations, define problems, make decisions and continuously update their skills. A diploma is not a final report card; universities should prepare students to work with technologies that may not yet exist years after graduation. Instead of teaching specific software, adaptability, critical thinking and collaboration should become core competencies.
Labor market shift toward task- and problem-based thinking
The labor market is also shifting: traditional job descriptions give way to task- and problem-oriented roles. As large language models deliver quick, reasonably good answers broadly, the intrinsic value of raw information declines while the ability to judge whether an AI output is reliable increases. For young people this is both risk and opportunity: AI can automate many junior tasks that previously served as entry points into work, but it can also accelerate learning and experience accumulation by providing background support.
What counts as independent work today?
Independence once meant solving a task without any help. Today, using various tools including AI can be acceptable; the key is that the worker understands the process, recognizes errors and can make informed decisions. Dietz emphasizes that it is not enough to supply technical tools: education systems, institutions and the world of work must be rethought at a societal level, because AI no longer only aids physical labor but now supports aspects of the human mind.
Verification, understanding and internalizing AI outputs
The question is becoming less about whether we use AI and more about whether we can understand, verify and truly make AI outputs part of our own knowledge. Accordingly, redesigning assessment methods is essential: how do we measure competencies in an environment where AI use may be mandatory in the workplace?
Topics covered in the conversation (with timestamps)
- What kinds of AI professionals are there in Hungary? (00:56)
- AI literacy: how should education change? (05:39)
- What skills are needed in the AI labor market? (09:52)
- Disappearing job roles, young people and automation (13:54)
- AI at university: what can students use and what must they know unaided? (20:26)
- Does AI dumb people down or teach them? (27:21)
- How should assessments be redesigned? (31:30)
- Hungary and the AI era: do we need to rethink everything? (36:40)
In the full episode Dr. Dietz Ferenc and Aczél Petra, communication researcher and professor at Széchenyi István Egyetem, discuss these issues in greater detail.
