Aims & Scope

Aims & Scope

Articles published in this journal highlight advances in the uses of AI systems for introducing novel solutions in management, industry, engineering, health, administration, and education; evaluations of existing AI systems and tools, emphasizing comparative studies and user experiences; and the economic, social, and cultural impacts of AI. We welcome papers on key applications, highlighting methods, time schedules, person-months needed, and other relevant material.

The high level scope of the journal encompasses a wide range of high-level topics related to AI, including but not limited to:

  • Educational Sciences and Artificial Intelligence
  • Science and Mathematics and Artificial Intelligence
  • Philology and Artificial Intelligence
  • Fine Arts and Artificial Intelligence
  • Law and Artificial Intelligence
  • Theology and Artificial Intelligence
  • Architecture, Planning, and Design and Artificial Intelligence
  • Engineering and Artificial Intelligence
  • Health Sciences and Artificial Intelligence
  • Social, Human, and Administrative Sciences and Artificial Intelligence
  • Agriculture, Forestry, and Aquatic Products and Artificial Intelligence
  • Sports Sciences and Artificial Intelligence

The scope of the journal encompasses a wide range of topics related to AI, including but not limited to:

  • Applied Artificial Intelligence and Machine Learning: Investigating the applications of AI and machine learning techniques and methods within impactful scenarios.
  • Natural Language Processing and its applications: Exploring the state-of-the-art applications of Natural Language Processing, including novel frameworks and theories to enable impactful applications.
  • Generative AI: Advancing the use of Generative AI within various multidisciplinary fields and topics, such as business analytics, text, audio, and image-related applications.
  • AI applications to Digital Health: Investigating impactful applications to Digital Health, including methods and techniques for reduce inefficiencies and cost whilst improving medical related systems, enhance patients’ care access, as well as medicine personalisation.
  • Engineering applications of AI, such as robotics, smart manufacturing, and smart agriculture: Exploring the applications of AI to the advancement of Industry 4.0, such as smart manufacturing and agriculture, as well as automated decision and cognitive systems applied.
  • Health applications of AI, such as: AI Applications in Healthcare: Medical Imaging and Diagnosis, Hospital and Clinical Management, Personalized Medicine and Treatment, Healthcare Data Analytics and Big Data , Healthcare Policies and Governance.
  • Ethical and Social Implications of AI: Exploring the ethical, societal, and cultural implications of AI technologies, including issues of bias, fairness, transparency, accountability, and privacy.
  • AI for Sustainable Development: Investigating the use of AI to address global challenges related to sustainability, including environmental conservation, climate change mitigation, resource management, and sustainable development goals.
  • Human-Centered AI: Advancing AI technologies that prioritize human well-being, safety, and inclusivity, with a focus on human-centered design, user experience, and human-AI interaction.
  • AI Policy and Governance: Examining legal, regulatory, and policy frameworks governing AI development, deployment, and use, including issues of regulation, standards, intellectual property, and international cooperation.
  • AI and Economic Impacts: Analyzing the economic implications of AI adoption, including effects on labor markets, job displacement, productivity, innovation, and economic inequality.
  • AI for Social Good: Showcasing innovative applications of AI for societal benefit, including healthcare, education, poverty alleviation, public safety, humanitarian aid, and social justice.
  • AI and Security: Addressing challenges and opportunities related to AI in the context of cybersecurity, national security, defense, and risk management.
  • Interdisciplinary Perspectives on AI: Encouraging interdisciplinary research that integrates insights from fields such as computer science, engineering, psychology, sociology, economics, philosophy, law, and public policy to advance understanding and development of AI technologies.

Featured contributions fall into several categories: Original Articles, Review Articles, Book Reviews and Announcements. The Original Articles will be high-quality contributions, representing new and significant research, developments or applications of practical use and value.  They will be reviewed by at least two referees.

All submissions to AIPA's International Journal on AI undergo rigorous peer review to ensure academic rigor, methodological soundness, and relevance to the journal's aims and scope. The journal welcomes original research articles, review papers, case studies, and perspectives that contribute to advancing knowledge and understanding at the intersection of AI, society, and policy.

Please note that this journal only publishes manuscripts in English.

Please note to AIPA's International Journal on AI does not allow changes to authorship lists post-submission.

AIPA's International Journal on AI: Bridging Technology, Society and Policy aspires to be at the forefront of disseminating high-quality research and discourse on artificial intelligence and its vast implications on society. The journal's scope is meticulously designed to embrace a wide array of topics, ensuring technical rigor and social relevance are included.

Technical Research Areas
● Foundational Machine Learning Research: Studies focusing on novel algorithms, theoretical analysis, and innovative machine learning frameworks that push the boundaries of AI
capabilities.
● Deep Learning: Cutting-edge research in deep neural networks, convolutional neural networks, recurrent neural networks, and their applications across diverse domains.
● Reinforcement Learning: Innovative work on agent-based learning, decision-making models, and reinforcement learning strategies for complex problem-solving.
● Unsupervised and Supervised Learning: Advanced methodologies and applications in both supervised and unsupervised learning paradigms, including feature extraction,
clustering, classification, and regression analysis.
● AI for Health: Research dedicated to AI's application in healthcare, including predictive analytics, medical imaging, health informatics, and personalized medicine.
● Quantum Machine Learning: Explorations at the intersection of quantum computing and machine learning, highlighting how quantum algorithms can revolutionize AI's future.
● Neuromorphic Computing: Studies on brain-inspired computing systems and architectures that mimic the neural structure of the human brain for enhanced AI processing.
● Big Data and Data Science: Research on handling, analyzing, and extracting valuable insights from large datasets, emphasizing AI's role in data science innovations.
● Machine Learning Operations (MLOps): Insightful analysis and methodologies on the lifecycle management of machine learning models, focusing on automation, scalability, and
deployment efficiency.
● Generative AI: Innovative research in generative models, including Generative Adversarial Networks (GANs), for applications in art, design, synthetic data generation, and beyond.


Non-technical and Social Science-Based AI Research
● AI Ethics and Governance: In-depth discussions on ethical frameworks, policies, and governance models to guide the responsible development and deployment of AI technologies.
● Societal Impact of AI: Analyses of how AI influences various aspects of society, including economy, education, healthcare, and social equity, providing insights into mitigating
negative impacts while amplifying benefits.
● Cultural and Philosophical Perspectives on AI: Explorations of AI's role in culture, art, and philosophy, examining how AI reshapes human creativity, identity, and existential
questions.
● AI in Environmental Sciences: Studies on leveraging AI to address environmental challenges, such as climate change mitigation, biodiversity conservation, and sustainable resource
management.
● Public Policy and AI: Research on how AI technologies intersect with public policy, including discussions on regulation, international collaboration, and the role of AI in shaping future
societal norms.
● AI and Education: Investigations into AI's transformative potential in education, from personalized learning experiences to the automation of administrative tasks

The journal aims to present developments and innovations in applied research and artificial intelligence (AI) applications. The journal also has an important mission in terms of providing original contributions to the literature on the multidisciplinary impacts of artificial intelligence research based on new methods, techniques, and frameworks. The articles published in this journal attempt to present advances in the use of artificial intelligence systems to deliver original solutions in a wide range of fields, including management, industry, engineering, healthcare, management, and education. In this context, it includes main topics such as Applied Artificial Intelligence and Machine Learning, Natural Language Processing, and its applications, Generative Artificial Intelligence, Artificial Intelligence Applications in Digital Health, engineering applications of artificial intelligence such as Robotics, smart production, smart agriculture, as well as the following specific application areas: adaptive computing, algorithms, applicable neural networks theory, applied statistics, architects, artificial intelligence, benchmarks, case histories of innovative applications, fuzzy logic, genetic algorithms, hardware implementations, hybrid intelligent systems, intelligent agents, intelligent control systems, intelligent diagnostics, intelligent forecasting, machine learning, neural networks, neuro-fuzzy systems, pattern recognition, performance measures, self-learning systems, software simulations, supervised and unsupervised learning methods, system engineering and integration.