Journal of Artificial Intelligence
in Interdisciplinary Studies
Advancing AI Research Across Disciplines. A premier peer-reviewed open-access journal dedicated to the intersection of artificial intelligence and diverse academic fields.
Bridging the Gap Between Algorithms and Humanity
The Journal of Artificial Intelligence in Interdisciplinary Studies (JAIIS) is a international, peer-reviewed open-access journal. We provide an advanced forum for studies related to the application, implications, and development of AI across all academic disciplines.
Our mission is to foster a high-level synergy between computational innovation and domain expertise in education and social sciences, promoting a holistic understanding of AI's transformative potential. By bridging the gap between algorithmic development and human-centric disciplines, we provide a global platform for research that shapes the future of our digital society.
Read our full aim & scopeScope & Disciplines
We publish high-quality original research, comprehensive reviews, and visionary perspectives focusing on the integration of artificial intelligence within human-centric and applied fields.
AI in Education
This domain explores the transformative power of intelligent systems in pedagogical landscapes. We prioritize research on adaptive learning environments, intelligent tutoring systems, and AI-driven curriculum design. Our scope includes innovative approaches to educational material design, VR/AR integration, and the advancement of learning analytics through automated assessment and educational data mining.
AI in Social Sciences
This section focuses on the interaction between computational advancements and human behavior. We seek research on affective computing, human-AI interaction (HCI), and the sociological modeling of digital societies. The scope also encompasses the role of natural language processing (NLP) in modern communication, social media analysis, and the psychological impacts of AI-driven environments.
AI in Applied Sciences
JAIIS provides a specialized platform for AI applications that redefine global service experiences. This integrated field covers smart destination management and tourism demand forecasting alongside culinary innovation and food waste optimization. We welcome studies on autonomous service agents, personalized nutrition systems, and the digital transformation of the hospitality and food industries.
AI in Smart Management & Business Intelligence
Focusing on the strategic application of AI in organizational structures, this area covers smart ERP (Enterprise Resource Planning) solutions, predictive analytics, and automated decision-making. We seek studies that explore how intelligent systems enhance productivity, resource management, and digital leadership, bridging the gap between data science and corporate strategy.
AI in Digital Humanities & Arts
This category examines the intersection of AI with cultural and creative expressions. The scope encompasses AI-driven linguistic analysis, cultural heritage preservation, and data mining in historical or literary studies. We encourage research on generative AI in arts, digital archiving, and the ways intelligent technologies help us understand and preserve human culture.
AI Ethics, Policy & Digital Society
Reflecting on the societal implications of intelligent systems, this area covers the ethical frameworks surrounding algorithmic bias, data privacy, and moral accountability. Instead of purely legalistic views, we focus on the impact of AI on labor markets, social structures, and the evolving rights of individuals within an increasingly automated and algorithmically governed world.
Latest Articles
Recently published peer-reviewed research.
Generative AI in Higher Education: A Systematic Review of Pedagogical Impacts
Dr. Sarah Jenkins, Prof. Michael Chen
This paper explores the integration of generative artificial intelligence tools in university curricula, analyzing both the pedagogical benefits and ethical challenges...
Predictive Modeling of Urban Heat Islands Using Deep Learning and Satellite Imagery
Elena Rodriguez, David Kim, et al.
We present a novel deep learning architecture for predicting urban heat island effects with high spatial resolution, combining meteorological data with multi-spectral satellite imagery...
Algorithmic Bias in Healthcare Triage Systems: A Cross-Demographic Analysis
Dr. James Wilson, Dr. Amina Patel
An investigation into the disparate impacts of machine learning algorithms used for patient triage across different demographic groups in metropolitan hospitals...