Doktori iskolások

Lilla Vicsek has been researching the social and ethical dimensions of AI since 2018. Part of her work examines how visions of the future of work and automation are constructed across multiple arenas—media narratives, expert debates, and lay interpretations of one’s own prospects. She will present two studies within this thematic focus. The first investigates expert debates, showing that these discussions frequently frame technological change as an autonomous force, posing questions such as whether robots will replace human labour. Such technologically deterministic framings obscure the political, economic, and institutional choices through which technologies are shaped, diverting attention from issues of power, inequality, working conditions, and environmental sustainability. Forecasts often rest on problematic assumptions, extrapolate from transient hype cycles, and overlook uncertainty, societal dynamics, and the interests embedded in particular predictions. The second study explores individuals’ expectations about their personal futures in an automated labor market and the cognitive biases that inform these expectations. The findings demonstrate that the psychological patterns are stratified by education and income, suggesting unequal capacities to interpret and prepare for anticipated change. Taken together, the two lines of inquiry show that imagined futures of work are not neutral projections but socially produced visions shaped by institutions, interests, cognitive tendencies, and wider cultural narratives about technology and its role in society.

AI has great potential to revolutionize products, processes, and strategies across individuals, organizations, social entities, and the broader economy. The primary obstacle to this AI revolution is the lack of trustworthiness of AI solutions, mainly due to the absence of Precise, Explainable, and Provable (PEP) AI outcomes. Therefore, our goal is to introduce the PEP AI concept via three groundbreaking methodologies to achieve PEP principles in AI solutions. First, we would like to introduce a new AI computational paradigm, the Neural Mesh replacing current Neural Networks used in AI engines. This leads to greater power and precision in AI. Second, we would like to develop a fundamental methodology to provide mathematically provable evidence for the stability and performance of AI-driven control solutions, replacing unreliable experience-based evaluations that are unacceptable in control systems (e.g., flight control, medical applications). Third, we would like to propose a new research direction aimed at extracting linguistically interpretable and explainable AI decisions to better understand the reasoning behind them. In addition to theoretical research, we  deliver proof-of-concept implementations integrated into healthcare applications while addressing future technology acceptance and EU AI Act aspects to foster post-project innovation and exploitation. We strongly collaborate with the University of Washington (UW), and The Chinese University of Hong Kong (CUHK), ranked 12th and 36th, respectively, by QS in AI and Informatics subjects. The key scientists are Y. Nesterov (CUB), recipient of the World Laureates Association Prize, along with four globally renowned scientists (from CUB,

CUHK, UW) contributing to PEP AI with their inventions, published in numerous top 2% journal papers.

Impact of AI Tools on Learning Outcomes:

Decreasing Knowledge and Over-RelianceStudents at all levels of education are increasingly relying on generative artificial intelligence (AI) tools to complete assignments and achieve higher exam scores. However, it remains unclear how this reliance affects their motivation, their genuine understanding of the material, and the extent to which it substitutes for the process of knowledge acquisition. To investigate the impact of generative AI on learning outcomes, an experiment was conducted at Corvinus University of Budapest. In an operations research class, students were randomly assigned into two groups: one was permitted to use AI tools during classes and examinations, while the other was not. To ensure fairness, a compensation mechanism was introduced: students in the lower-performing group received point adjustments until the average performance of the two groups was equalized. Despite the organizers’ best efforts to explain the design and to create equal opportunities for all participants, many students perceived the experiment as a major disruption. Although the experiment was approved by every relevant university authority — including the Ethics Board, the Head of Department, the Program Director, and the Student Council — students escalated their concerns to the media and eventually to the State Secretary for Higher Education of Hungary. As a result, the experiment had to be substantially revised before completion: on the final exam the test group was merged with the control group. Still, the data allowed us to draw decisive conclusions regarding the students’ learning habits. Uncontrolled use of AI tools leads to disengaged students and low understanding of material. The extreme reactions of the students proved even more revealing than the data collected: generative AI tools have already become indispensable for students, raising fundamental questions about the validity of their learning process.

The article is available: https://arxiv.org/abs/2510.16019

This research examines the relationship between artificial intelligence (AI) and disinformation and seeks to answer whether AI is opening a new era in disinformation. Róbert Pintér have conducted a systematic investigation, introducing disinformation chain as a new concept. Using this theoretical framework, he describes the motivation, creation, dissemination, detection, reception and wider social impact of disinformation. He also describes the application of AI in these steps. The results show the role of AI is particularly significant in the dissemination and social impact of disinformation, while the emergence of generative AI has not proved to be decisive in the creation of disinformation, contrary to prior expectations. If we can talk about a new era, it is more related to social media algorithms and participatory propaganda with the active involvement of people, which has led to the emergence of a post-truth era since 2016. The research also proposes a set of actions for effective measures against disinformation along the disinformation chain. Finally, the researcher concludes by expressing his belief that the statement ‘we cannot believe our eyes and ears’ crystallises not as a fatalistic creed but as a healthy scepticism, since no society can function without human trust.

The article is available in Hungarian: https://m2.mtmt.hu/api/publication/36395201