Editor: Nicholas Vretos

Artificial Intelligence in Social Science, Humanities and Health: A Path Towards Trustworthy AI and Human-AI Symbiosis

eBook: US $59 Special Offer (PDF + Printed Copy): US $109
Printed Copy: US $79
Library License: US $236
ISBN: 979-8-89881-817-3 (Print)
ISBN: 979-8-89881-816-6 (Online)
Year of Publication: 2026
DOI: 10.2174/97988988181661260101

Introduction

This edited volume explores AI's transformative reach across healthcare, the social sciences, and the humanities, centered on two guiding ideas: Human-AI Symbiosis, where AI amplifies rather than replaces human insight, and Trustworthy AI, emphasizing transparency, fairness, accountability, and robustness in intelligent systems.

Nine interdisciplinary chapters trace AI's evolving role — from foundational machine learning and deep learning concepts, to AI-powered healthcare platforms and multimodal clinical decision support, to breakthroughs in biomedical microscopy. The collection also tackles pressing ethical and legal frameworks for responsible AI, collaborative innovation in protein interaction research, AI's growing influence on political discourse, privacy-by-design architecture, agent-based modelling in archaeology, and AI's expanding footprint in literature and the arts.


Key Features

  • - Bridges technical AI advances with real-world human impact across diverse fields.
  • - Balances theoretical depth with practical, applied case studies.
  • - Addresses urgent ethical, legal, and societal questions shaping AI's future.
  • - Showcases cross-disciplinary collaboration between technology, science, and the humanities.

This book is a timely, multidisciplinary resource for anyone invested in building AI that works with humanity — not apart from it.


Target Readership :

Primary readers: Scholars, researchers, and practitioners in AI, data science, healthcare, and the humanities/social sciences seeking rigorous, interdisciplinary perspectives.

Secondary readers: Graduate students and policymakers interested in the ethical, legal, and societal dimensions of emerging AI technologies.

Foreword

- Pp. i
Petros Daras
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Preface

- Pp. ii-iii (2)
Nicholas Vretos
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List of Contributors

- Pp. iv-v (2)

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Machine Learning and Deep Learning within the Context of Artificial Intelligence

- Pp. 1-41 (41)
Nicholas Vretos*

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AI-Driven Insights for Enhanced Healthcare: Leveraging Multimodal Data Analysis in e-Health Platforms

- Pp. 42-78 (37)
Damianos Charcharidis, Vassilis Solachidis*, Nicholas Vretos

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Current Trends, Innovations and Challenges in Multi-Modal AI-Powered Assistants for Pathology

- Pp. 79-107 (29)
Anestis Kastellos*, Kosmas Dimitropoulos, Yiannis S Boutalis, Petros Daras

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Data Science and Artificial Intelligence Under Ethics and Legal Perspectives for the Detection of Chronic Respiratory Diseases

- Pp. 108-126 (19)
Zoheir Sabeur*, Timothy Albiges, Banafshe Arbab-Zavar, Audrey Dequesness, Tilak Ginige

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AI-Promoted Protein-Protein Interaction Site Identification as a Powerful Tool for the Development of Personalized Therapies: A Survey on Recent Advances

- Pp. 127-147 (21)
Angelos-Michael Papadopoulos*, Apostolos Axenopoulos, Anastasia Iatrou, Antonia Zoi Kouroutzidou, Stamatia Laidou, Kostas Stamatopoulos, Federico Alvarez, Petros Daras

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AI and Politics

- Pp. 148-180 (33)
Anestis Kaimakamidis, Eirini Kondyli, Ioannis Mademlis, Ioannis Pitas*

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Privacy-by-Design AI

- Pp. 181-208 (28)
Vasileios Mygdalis, Ioannis Pitas*

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Agent-Based Modelling (ABM) in Archaeology: A Classical Vision

- Pp. 209-229 (21)
Giorgos Sanidas*

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Recent Advances in AI for Literature and Art

- Pp. 230-256 (27)
Konstantinos Marthoglou*, Nicholas Vretos

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Subject Index

- Pp. 257-262 (6)
Nicholas Vretos
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