New Skills and Knowledge for Digital Entrepreneurs in the Age of Artificial Intelligence

Authors

  • Daniela Orozova Department of Informatics and Mathematics, Faculty of Economics, Trakia University, Stara Zagora 6015, Bulgaria https://orcid.org/0000-0002-0279-8293
  • Nadezhda Angelova Trakia university, Stara Zagora, Bulgaria https://orcid.org/0000-0003-0695-5572
  • Zlatin Zlatev Department of Electrical Engineering, Automation, Computer Systems and Communications, Faculty of Technics and Technologies, Trakia University, Yambol 8600, Bulgaria

DOI:

https://doi.org/10.34190/ecie.19.1.2447

Keywords:

Artificial Intelligence, Machine Learning, Data Fusion, E-Learning, Entrepreneurship

Abstract

Digital technologies are becoming increasingly complex and integrated, leading to significant transformations in society and the economy. The article aims to explore and summarize the new opportunities and potential risks of the widespread use of artificial intelligence (AI) in all aspects of life, to define the new skills and necessary knowledge of digital entrepreneurs and to highlight the need for transformation in modern education. Recognizing that the relationship between technology and business is two-way and becoming stronger, revealing that well-prepared employees are a guarantee of success and prosperity of companies in various fields, we try to focus on the main groups of qualities, skills and basic knowledge of students in the age of artificial intelligence. The development of the Internet, expansion of connectivity through social networks, the advent of AI, 3D printing, and immersive technologies like Augmented Reality, and Virtual Reality, require new knowledge and skills, leading to new challenges in education. Qualified personnel in this modern world must have solid professional training and systemic thinking (knowledge, skills, accumulated information), developed cognitive abilities, and personal skills based on collecting and analyzing large amounts of diverse information from heterogeneous sources. Questions arise: how can multiple information sources be combined effectively, and how can the fusion of multiple sources provide additional information to support decision-making processes? Combining information obtained from the real world makes the results heterogeneous and more informative. It follows the need to develop machine learning methods to extract relevant information from increasingly complex data sets. The goal is to improve the accuracy of the applied classification algorithms by combining predictions from multiple models, as well as obtaining a more stable final classification evaluation, effective handling of noisy data, adaptation to changing conditions, and improving stability when solving problems. On the other hand, how to ensure that the enormous potential of artificial intelligence, virtual reality, connection with the physical world, machine learning, and pervasive networks of people and machines will be fully used to improve the quality of life and contribute to the building of stable societies. Changes must be subordinated to policy and investments for reliable artificial intelligence and based on an ethical and human-centered approach. All of these should be established as a fundamental principle of training in Higher education which imposes the need for transformation in modern education.

Author Biographies

Daniela Orozova, Department of Informatics and Mathematics, Faculty of Economics, Trakia University, Stara Zagora 6015, Bulgaria

Daniela Orozova graduated with a degree in "Informatics" from Sofia University "St. Kliment Ohridski". Her PhD was on intelligent databases and learning systems. She is a professor in Informatics and Computer Sciences at Trakia University. In 2023 she earned the "Doctor of Sciences" degree, in the area of “Application of data science in the virtual educational space.

Nadezhda Angelova, Trakia university, Stara Zagora, Bulgaria

Dr. Nadezhda Angelova is an Associate Professor at Trakia University, Bulgaria. She has a master degree in Mathematics, specialization in Informatics from Plovdiv University “Paisii Hilendarski. In 2015 she received her PhD degree in "Informatics” at the same university. Her research interests are Artificial Intelligence, Augmented reality, E-learning, LMS, IoT.

Zlatin Zlatev, Department of Electrical Engineering, Automation, Computer Systems and Communications, Faculty of Technics and Technologies, Trakia University, Yambol 8600, Bulgaria

Zlatin Zlatev is an Associate Professor at Trakia University, Faculty of Technics and Technologies, Yambol, Bulgaria. He holds a Bachelor’s degree in Automatics, Information and Control Technics at Trakia University and a Master and a Doctorate degrees in Process Automation at the University of Ruse "Angel Kanchev", Bulgaria. 

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Published

2024-09-20