New Skills and Knowledge for Digital Entrepreneurs in the Age of Artificial Intelligence
DOI:
https://doi.org/10.34190/ecie.19.1.2447Keywords:
Artificial Intelligence, Machine Learning, Data Fusion, E-Learning, EntrepreneurshipAbstract
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.
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Copyright (c) 2024 Daniela Orozova, Nadezhda Angelova, Zlatin Zlatev
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.