Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Deokar, Ruchira; Nanjundan, Preethi; George, Jossy; Gershenson, Carlos Title A name given to the resource Reducing Systemic Bias in Behavioral Targeting Using Explainable AI: The HARMONIA Complex Systems Approach Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Northeast Journal of Complex Systems;Volume;8;Issue;1;Article No.;1; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.63562/2577-8439.1151" target="_blank" rel="noreferrer noopener">https://doi.org/10.63562/2577-8439.1151</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105035087314?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105035087314?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Deokar R., Department of Data Science, Christ University, India; Nanjundan P., Department of Data Science, Christ University, India; George J., Department of Computer Science, Christ University, India; Gershenson C., State University of New York at Binghamton, Binghamton, United States Description An account of the resource Behavioral targeting is a key part of the modern advertising web's algorithmic engine. However, it is unclear whether optimization processes worsen bias, promote unchecked spread in filter bubbles or lower overall users' trust levels. This paper introduces HARMONIA (Holistic Adaptive Regulatory Model for Optimizing Non-transparent Intelligent Advertising), a comprehensive, data-driven Explainable Artificial Intelligence (XAI) framework aimed at transforming behavioral targeting via transparency, interpretability, and adaptive ethical regulation. This paper conducted a comprehensive Explorative Data Analysis (EDA) on the public Criteo Display Advertising Dataset, which contains over 45 million records, to identify patterns in high-dimensional user-ad interaction space. This analysis uncovered latent behavioral signals that affect the relevance of ads based on users' online behavior. The analysis identified four interrelated behavioral dynamics: ad fatigue attenuation, diurnal engagement oscillations, device-driven preference divergence, and category-affinity dominance. These dynamics served as the foundational architectural principles for HARMONIA's design. The method uses gradient boosted prediction models and a multilayer explainability stack that includes SHAP for global interpretability, LIME for local surrogate approximation, and counterfactual reasoning for causal transparency. Quantitative evaluation indicates that HARMONIA maintains relevance accuracy (approximately 1.2% CTR), achieves a 31% enhancement in transparency metrics, and a 27% improvement in user-trust indices, while concurrently reducing systemic entropy by nearly one-third. This research redefines personalization to be self-explanatory and ethically sound AI by incorporating explainability as a regulatory mechanism in the adaptive ecosystem of complex digital advertising. This system takes explainable computational marketing from an idea to a full-scale implementation. 2026 Binghamton University Libraries. All rights reserved. Subject The topic of the resource Behavioral Targeting; Complex Adaptive Systems (CAS); Explainable Artificial Intelligence (XAI); Interpretable Recommender Systems; Transparency and User Trust Publisher An entity responsible for making the resource available Binghamton University Libraries Relation A related resource ISSN: 25778439; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access Format The file format, physical medium, or dimensions of the resource online