The 7th International Conference on Modern Management based on Big Data (MMBD 2026)

Abstract: The expanding role of artificial intelligence in organizations has reshaped strategic planning, performance management, and operational decision-making. While advanced machine learning models deliver high predictive accuracy, many operate as opaque systems that offer limited insight into the reasoning behind their outputs. From a management perspective, decision quality extends beyond statistical performance; it encompasses transparency, accountability, governance, and stakeholder trust.
This presentation positions Explainable Artificial Intelligence (XAI) within the broader context of responsible and data-driven management. It argues that interpretability strengthens managerial rationality by clarifying how analytical results are generated, thereby supporting informed judgment under uncertainty. In environments characterized by risk exposure, regulatory oversight, and strategic complexity, explainability becomes a critical mechanism for aligning algorithmic outputs with organizational objectives and ethical standards.
By integrating statistical reasoning with interpretable machine learning approaches, organizations can develop decision-support frameworks that balance analytical power with managerial responsibility. Rather than treating explainability as a purely technical enhancement, the study conceptualizes it as a governance-oriented capability that reinforces legitimacy and long-term sustainability. In the era of big data, building trustworthy AI-enabled management systems requires not only accuracy, but also clarity, accountability, and strategic coherence.

Biography: Prof. Dr. Filiz Ersöz commenced her professional career in 1989 as a Statistician at the Turkish Statistical Institute. Between 2001 and 2006, she served as an Operational Research Expert at the Turkish Land Forces Command, where she also undertook responsibilities as NATO NAAG Force Coordinator and Coordinator for Defense Industry Cooperation. From 2006 to 2012, she held a specialist position in Probability and Stochastic Processes at the Turkish Military Academy, contributing to the development of analytical and decision-support methods in military systems.
In 2012, she joined the Department of Industrial Engineering at Karabük University, where she served as a faculty member until 2023. In the Spring semester of 2023, she taught Data Mining as a part-time lecturer at Özyeğin University. From September 2023 to September 2024, she was a visiting professor at the Artificial Intelligence Research & Development Group (AI-DII) within the Department of Information Engineering at the University of Pisa, contributing to interdisciplinary research in artificial intelligence and machine learning. Since October 2024, she has continued her academic work at OSTİM Technical University.
Prof. Dr. Ersöz is the author of several academic books, including Statistics I, Statistics II, Data Mining Techniques and Applications, Statistical Data Analysis with IBM SPSS, Statistics with Python and Simulation and Modeling. Her research interests include Big Data Analytics and Statistical Learning; Computational Statistics and Statistical Software Applications; Data Mining and Predictive Analytics; Machine Learning and Artificial Intelligence; System Simulation Modelling; Operations Research and Optimization; Statistical Quality Control and Six Sigma; Stochastic Processes and Reliability Engineering.