AI’s Societal Impact explored by Marco Rossi (Mathworks) and Dr. habil. Mihály Héder (BME GTK) on Faculty Science Day

The Faculty of Economic and Social Sciences held the Faculty Science Day in the framework of the “Day of Hungarian Science” in November.  The main theme of this year’s event was the societal impact of artificial intelligence development, explored through captivating presentations by our invited speakers.

Dr. Tamás Koltai, the dean of the faculty, opened the event, emphasizing that the Faculty Science Day traditionally addresses current scientific issues or matters of scientific public life, and this year’s event focuses on the prominent role of artificial intelligence. He highlighted that the theme would be examined from both practical and philosophical perspectives. The program was the first official event in the recently inaugurated Ladó László Hall.

The first speaker, Marco Rossi, PhD, an education customer success engineer at MathWorks, presented the educational tools of the MATLAB platform, with a particular emphasis on exploring AI-based use cases. He emphasized the importance of computational thinking in the 21st century and demonstrated how MATLAB could support its integration into curricula.

MATLAB is a low-code program that allows users to solve various problems without extensive programming. The platform contains over 100 useful tools, including image processing and text analysis, and offers different training options to enhance the user experience. The presentation was especially valuable as all our university’s educators, researchers, and students are entitled to use MATLAB, Simulink, and the entire toolbox through an open licence. The representative from Gamax Laboratory Solutions, the official regional partner of MATLAB, also participated in the event, fostering local collaborations.

In his presentation, Dr. habil. Mihály Héder introduced the audience to the philosophy of artificial intelligence, emphasizing the distinction between the mathematical models of computers and the actual physical systems they represent. He presented arguments against making absolute statements about what computers can or cannot do based on the limitations of their models. The presentation covered historical perspectives on AI limitations, such as language translation and creativity, and highlighted the importance of understanding the physical nature of computers for ethical considerations and testing. The speaker encouraged a nuanced approach to discussing AI capabilities, urging against confusing the mathematical models with the actual physical systems.