Aims and Scope

Bridging the gap between theoretical AI development and its practical, ethical, and societal applications across diverse domains.

Our Aims

The Journal of Artificial Intelligence in Interdisciplinary Studies (JAIIS) aims to serve as a premier international forum for high-quality, peer-reviewed research at the intersection of artificial intelligence and diverse academic disciplines. Our primary objective is to cultivate a sophisticated understanding of intelligent systems by bridging the gap between computational innovation and domain expertise.

We seek to foster a holistic synergy between AI developers and experts in education, social sciences, and applied human studies. Our goal is to publish research that not only advances AI methodologies but also addresses real-world challenges, ethical considerations, and the sustainable evolution of our digital society. By prioritizing interdisciplinary collaboration, JAIIS aims to be the leading resource for scholars dedicated to the human-centric and transformative potential of artificial intelligence.

Our Scope

JAIIS welcomes original research articles, comprehensive reviews, short communications, and visionary perspectives. Our scope is strategically designed to capture the transformative and pervasive nature of artificial intelligence within education, social sciences, and applied human studies.

We are particularly interested in submissions that demonstrate true interdisciplinary synergy—where AI techniques provide novel insights into a specific domain, or where domain-specific challenges inspire the development of new AI methodologies. We highly value research that critically examines the societal, psychological, and ethical impacts of AI deployment, ensuring a human-centric approach to the evolution of intelligent systems. By prioritizing high-impact studies that bridge the gap between computational innovation and professional expertise, JAIIS aims to be the definitive platform for interdisciplinary excellence.

Topics & Fields

JAIIS welcomes original research and interdisciplinary studies within, but not limited to, the following core areas and their sophisticated intersections:

AI Foundations in Human-Centric Systems

Focusing on the methodologies that power human-oriented AI, including Machine Learning, Deep Learning, Natural Language Processing (NLP), and Explainable AI (XAI) applied to social and educational data.

AI in Education & Adaptive Pedagogy

Exploring the future of learning through intelligent tutoring systems, adaptive curriculum design, educational data mining, and learning analytics that personalize the educational experience.

Digital Material Design & Teacher Education

Focusing on the integration of AI, VR, and AR in instructional design, the development of digital educational materials, and the enhancement of AI literacy among educators and teacher candidates.

AI in Applied Sciences & Global Industries

Innovating global service industries through smart destination management, tourism demand forecasting, culinary AI applications, and food waste optimization through intelligent systems.

Smart Management & Business Intelligence

Bridging data science and corporate strategy through AI-driven ERP (Enterprise Resource Planning) solutions, predictive organizational analytics, and automated decision-making frameworks.

Computational Social & Behavioral Sciences

Analyzing human behavior in digital societies through affective computing, social network analysis, human-AI interaction (HCI), and the psychological impacts of intelligent environments.

AI in Digital Humanities & Communication

Preserving and analyzing human culture through AI-driven linguistic analysis, digital heritage preservation, and the evolution of communication and media in the age of algorithmic content.

AI Ethics, Policy & Digital Society

Critically examining the societal implications of AI, including algorithmic bias, data privacy, digital governance, and the ethical transformation of labor markets and social structures.