Call for Chapters: Language and Hermeneutics in Temporal Ontologies for Predictive Explainable AI Systems

Editors

Mihaela Meresi, UAIC Iasi Romania, Belgium

Call for Chapters

Proposals Submission Deadline: June 10, 2026
 Full Chapters Due: August 12, 2026
 Submission Date: August 12, 2026

Introduction

An interdisciplinary bridge between hermeneutics, language and predictive AI. Recent advances in artificial intelligence (AI) and machine learning (ML) have significantly expanded the capacity of computational systems to process and generate language. However, despite these developments, a fundamental limitation persists: most AI systems continue to rely on static and context-reduced representations of meaning, with limited capacity to account for the temporal, interpretative and evolving nature of human understanding. Language is not a fixed encoding system but a dynamic and situated process in which meaning emerges through interpretation, context and temporal development. Philosophical traditions in hermeneutics and epistemology have long pledged that understanding is inherently temporal, revisable and dependent on interpretative frameworks. In contrast, contemporary AI systems, particularly those deployed in predictive and decision-support contexts, often operate through statistical pattern recognition that abstracts away from the evolving nature of meaning. At the same time, predictive Explainable AI (XAI) systems are increasingly used in domains where interpretation, uncertainty and context are central to decision-making. In such environments, outputs are not sufficient on their own; they require explanation, justification and interpretability across changing conditions and evolving data streams. This creates an urgent need for frameworks that integrate language, interpretation and temporal structure into computational models of intelligence. This edited volume addresses this need by exploring the intersection of language, hermeneutics and temporal ontologies in predictive Explainable AI systems. It aims to develop interdisciplinary foundations for understanding how meaning can be represented, interpreted and formalised within dynamic and uncertain environments, and how such representations can support the design of more transparent, context-aware and responsible AI systems.

Objective

This volume invites high-quality chapter proposals that investigate the theoretical, methodological and applied dimensions of language, interpretation and temporal structures in predictive Explainable AI systems. It seeks to establish a productive dialogue between computational approaches and philosophical traditions, with a particular focus on how meaning is constructed, interpreted and transformed over time. Contributions may engage with foundational questions in philosophy of language, epistemology and hermeneutics, exploring how they can inform contemporary artificial intelligence. Of particular interest are works that address the temporal nature of interpretation, the role of context in meaning formation and the limits of current explainability approaches in dynamic and uncertain environments. The volume further encourages methodological and computational contributions, including natural language processing, semantic modelling, knowledge representation, temporal ontologies and hybrid symbolic–neural architectures. Submissions may also explore predictive modelling, uncertainty quantification (UQ), narrative reasoning and probabilistic interpretation in language-based AI systems. In addition, the scope includes studies on model adaptation, contextual evolution and interpretability under changing conditions, as well as the interaction between human and machine processes of meaning-making. Applied contributions are welcomed in domains where language plays a critical role in decision-making, such as healthcare, policy, risk analysis, security and complex socio-technical systems. The volume also addresses ethical, legal and societal implications, including issues of bias, interpretative error, transparency, accountability and the responsible deployment of predictive AI systems. Interdisciplinary approaches combining conceptual, empirical and computational perspectives are strongly encouraged. The volume aims to foster cross-disciplinary dialogue and advance the development of AI systems that are more interpretable, context-aware and aligned with human processes of meaning-making and understanding.

Target Audience

Intended for an interdisciplinary audience of researchers, academics and practitioners working at the intersection of artificial intelligence, computational linguistics, philosophy, cognitive science and the social sciences. It is particularly relevant to scholars in hermeneutics, philosophy of language and epistemology, as well as researchers in natural language processing, explainable AI (XAI) and knowledge representation. The volume also addresses professionals involved in the design, implementation and governance of predictive and language-based AI systems, including those working in healthcare, law enforcement, policy development, risk analysis and complex decision-support environments.

Recommended Topics

Topics of interest include, but are not limited to: 1. Current challenges in language-based AI and decision-support systems 2. Language as a temporal and interpretative process in AI 3. Philosophy of language and hermeneutics in AI system design 4. Interpretation, context and evolving semantics in AI systems 5. Semantic modelling, knowledge representation and context-aware systems 6. Temporal ontologies and the structural representation of time and meaning in dynamic contexts 7. Natural language processing for temporal reasoning and decision support 8. Explainable AI (XAI) and interpretability in language-based and predictive models 9. Uncertainty, ambiguity and probabilistic interpretation in language-based AI 10. Predictive modelling, inference and narrative reasoning in AI systems 11. Human–AI interaction and the co-formalization of meaning 12. Integration of language-based AI with real-time data systems, digital twins and simulation environments 13. Model drift, contextual adaptation and evolving interpretative frameworks 14. Ethical, legal and societal implications of predictive XAI systems.

Submission Procedure

Researchers and practitioners are invited to submit on or before June 10, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by June 24, 2026 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by August 12, 2026, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Language and Hermeneutics in Temporal Ontologies for Predictive Explainable AI Systems. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing, an international academic publisher of the "Information Science Reference", "Medical Information Science Reference", "Business Science Reference", and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2027.

Indexing Information for Prospective Authors

IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus; however, it is important to note that all indexing decisions are made independently by these services. IGI Global Scientific Publishing books are selectively indexed by the indexing organization after publication. Indexing cannot be guaranteed for any book prior to publication, and the indexing organization has complete control over the final selection and timeline.

Important Dates

June 10, 2026: Proposal Submission Deadline
June 24, 2026: Notification of Acceptance
August 12, 2026: Full Chapter Submission
September 16, 2026: Review Results Returned
October 14, 2026: Final Acceptance Notification
October 21, 2026: Final Chapter Submission

Inquiries

Dr. M. Meresi
meresi.mihaela@gmail.com
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