2025
FLUXAI: Layered Explainability for Human-Centered Understanding via Feynman’s Approach
Fatih Bildirici
4th Eurasian Conference on Human-Computer Interaction 2025
The need for explanations that are both technically correct and cognitively meaningful to a wide range of users has been highlighted by the rapid spread of Artificial Intelligence (AI) in high-stakes fields like healthcare, finance, and law. The current Explainable AI (XAI) techniques, such as saliency maps, feature importance scores, and counterfactuals, are still primarily model-centered and frequently fall short in bridging the gap between technical transparency and human comprehension.
FLUXAI: Layered Explainability for Human-Centered Understanding via Feynman’s Approach
Fatih Bildirici
4th Eurasian Conference on Human-Computer Interaction 2025
The need for explanations that are both technically correct and cognitively meaningful to a wide range of users has been highlighted by the rapid spread of Artificial Intelligence (AI) in high-stakes fields like healthcare, finance, and law. The current Explainable AI (XAI) techniques, such as saliency maps, feature importance scores, and counterfactuals, are still primarily model-centered and frequently fall short in bridging the gap between technical transparency and human comprehension.
2024
Open-source AI: An approach to responsible artificial intelligence development
Fatih Bildirici
Jurnal Sosiologi Reflektif (JSR) 2024 Spotlight
This paper comprehensively addresses the risks, problems, and ethical issues for the responsible development of artificial intelligence (AI) technologies. It demonstrates the critical importance of this approach to the future of AI by addressing both technological innovation and societal values in a balanced manner.
Open-source AI: An approach to responsible artificial intelligence development
Fatih Bildirici
Jurnal Sosiologi Reflektif (JSR) 2024 Spotlight
This paper comprehensively addresses the risks, problems, and ethical issues for the responsible development of artificial intelligence (AI) technologies. It demonstrates the critical importance of this approach to the future of AI by addressing both technological innovation and societal values in a balanced manner.
Optimizing Microservice Performance: A Software Configuration Management Changes and Time Series Analysis Framework
Fatih Bildirici
El-Cezeri Journal of Sciences 2024
This study provides a comprehensive framework for analyzing and optimizing the performance impacts of configuration and release management processes in microservice-based software systems. Through advanced methodologies, including time-series modeling, regression analysis, anomaly detection, and optimization techniques, the research emphasizes the critical influence of configuration parameters.
Optimizing Microservice Performance: A Software Configuration Management Changes and Time Series Analysis Framework
Fatih Bildirici
El-Cezeri Journal of Sciences 2024
This study provides a comprehensive framework for analyzing and optimizing the performance impacts of configuration and release management processes in microservice-based software systems. Through advanced methodologies, including time-series modeling, regression analysis, anomaly detection, and optimization techniques, the research emphasizes the critical influence of configuration parameters.