Integrating LLM Usage in Gamified Systems

In his work, Prof. Carlos Costa uses a mathematical framework for formalize an approach that allows incorporating Large Language Models (LLMs) into gamified systems is presented with an emphasis on improving task dynamics increasing user engagement, and improving reward systems.

Personalized feedback adaptive learning and dynamic content creation are all made possible by the integration of LLMs and are crucial for improving user engagement and system performance. Carlos uses a simulated environment to test the framework’s adaptability and demonstrate its potential for real-world applications in a variety of industries including business healthcare and education. According to Dr. Costa, his findings demonstrate how LLMs can offer customized experiences that raise system effectiveness and user retention. His study also examines the difficulties this framework aims to solve highlighting its importance in maximizing involvement and encouraging sustained behavioral change in a range of sectors.

Costa, Carlos J. 2025. “Integrating LLM Usage in Gamified Systems.” WSEAS Transactions on Mathematics 24:258–67. doi: 10.37394/23206.2025.24.25.

The Democratization of Artificial Intelligence: Theoretical Framework

The democratization of artificial intelligence (AI) involves extending access to AI technologies beyond specialized technical experts to a broader spectrum of users and organizations. This paper provides an overview of AI’s historical context and evolution, emphasizing the concept of AI democratization.

Current trends shaping AI democratization are analyzed, highlighting key challenges and opportunities. The roles of pivotal stakeholders, including technology firms, educational entities, and governmental bodies, are examined in facilitating widespread AI adoption. A comprehensive framework elucidates the components, drivers, challenges, and strategies crucial to AI democratization. This framework is subsequently applied in the context of scenario analyses, offering insights into potential outcomes and implications. The paper concludes with recommendations for future research directions and strategic actions to foster responsible and inclusive AI development globally.

Costa, C. J., Aparicio, M., Aparicio, S., & Aparicio, J. T. (2024). The Democratization of Artificial Intelligence: Theoretical Framework. Applied Sciences, 14(18), 8236. https://doi.org/10.3390/app14188236