The Fundamental Principles of Machine Learning and Its Role in Technological Transformation

Session

Computer Science and Communication Engineering

Description

The rapid development of technology has significantly increased the use of Machine Learning (ML) across various social and economic domains. Advanced algorithms such as neural networks, support vector machines, random forests, and deep learning techniques have revolutionized the way information is analyzed and utilized. However, a key challenge lies in understanding their impact on professions and society. This thesis is developed along two parallel dimensions: addressing the theoretical concepts and applications of ML in different industries, and empirically evaluating the “Substitution vs. Augmentation” hypothesis, which explores whether ML replaces traditional human roles or enhances them. Through a comprehensive literature review and data analysis, ML models and applications in sectors such as healthcare, finance, e-commerce, and communication were examined. The study’s findings reveal that although there is a risk of replacing certain professions, in most cases ML functions as a tool that complements and enhances human capabilities—boosting productivity and creating new opportunities. The thesis is structured into six chapters, including a literature review, methodology, and research findings. The final conclusions underscore the importance of integrating ML in an ethical and balanced manner, with the goal of using it as a tool for development rather than replacement. This thesis contributes to the scientific literature by offering a blend of theoretical insight and empirical analysis on the transformative role of ML, serving as a foundation for shaping more effective strategies for the future of technology.

Keywords:

Artificial Intelligence (AI), Machine Learning (ML), Federated Learning (FL), Human–Machine Collaboration, Ethical Integration.

Proceedings Editor

Edmond Hajrizi

ISBN

978-9951-982-41-2

Location

UBT Lipjan, Kosovo

Start Date

25-10-2025 9:00 AM

End Date

26-10-2025 6:00 PM

DOI

10.33107/ubt-ic.2025.91

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Oct 25th, 9:00 AM Oct 26th, 6:00 PM

The Fundamental Principles of Machine Learning and Its Role in Technological Transformation

UBT Lipjan, Kosovo

The rapid development of technology has significantly increased the use of Machine Learning (ML) across various social and economic domains. Advanced algorithms such as neural networks, support vector machines, random forests, and deep learning techniques have revolutionized the way information is analyzed and utilized. However, a key challenge lies in understanding their impact on professions and society. This thesis is developed along two parallel dimensions: addressing the theoretical concepts and applications of ML in different industries, and empirically evaluating the “Substitution vs. Augmentation” hypothesis, which explores whether ML replaces traditional human roles or enhances them. Through a comprehensive literature review and data analysis, ML models and applications in sectors such as healthcare, finance, e-commerce, and communication were examined. The study’s findings reveal that although there is a risk of replacing certain professions, in most cases ML functions as a tool that complements and enhances human capabilities—boosting productivity and creating new opportunities. The thesis is structured into six chapters, including a literature review, methodology, and research findings. The final conclusions underscore the importance of integrating ML in an ethical and balanced manner, with the goal of using it as a tool for development rather than replacement. This thesis contributes to the scientific literature by offering a blend of theoretical insight and empirical analysis on the transformative role of ML, serving as a foundation for shaping more effective strategies for the future of technology.