Special issue on comprehensive evaluations of AI and ML techniques across interdisciplinary fields

This special issue of the Journal of Economy and Technology (JET) seeks to assemble a rigorous collection of scholarly articles that critically examine the efficacy and impact of artificial intelligence (AI) and machine learning (ML) across a range of disciplines. The aim is to promote interdisciplinary research that evaluates advanced AI technologies, offering insights into their practical applications and theoretical implications.

Contributions are invited in the following key areas:

Extensive AI/ML Evaluations Across Disciplines: Papers should focus on in-depth analyses of AI applications, assessing their integration, usability, and impacts on various fields.

Synergy of Advanced and Traditional AI Techniques: Research detailing the integration of state-of-the-art AI technologies with established informatics practices to solve complex real-world challenges is particularly welcome.

Reliability and Interpretability of Emerging AI Technologies: Submissions should evaluate the trustworthiness and explainability of new AI models, incorporating discussions on regulatory landscapes, policy implications, and strategic frameworks for future AI research in interdisciplinary contexts.

This issue welcomes comprehensive reviews of current literature, regulatory standards, and best practices, with the aim to encourage discussions on the strategic integration of AI into research and practice across multiple domains.

Topics covered

1. Prompt Engineering and Domain-Specific Fine-Tuning of Large Language Models (LLMs): Evaluating customization techniques for LLMs tailored to specific industry/research needs.
2. Application of Domain-Specific Vector Databases, Embeddings and LLMs: Analyzing the use of advanced data structures and models for enhancing semantic search and data retrieval.
3. Integration of Traditional AI/ML/NLP Techniques with Large Language Models: Investigating the synergistic effects of combining traditional AI/ML/NLP methods with cutting-edge LLMs in solving complex tasks.
4. Retrieval Augmentation Generation in Information Systems: Exploring how retrieval-enhanced generative models improve information accuracy and user interaction in various domains.
5. The novel enhancements of deep learning architectures (e.g., CNN, RNN, GPT, BERT, other Semantic Embeddings and etc.) and their applications: Assessing the broad impacts and specific use cases of deep learning models in fields such as healthcare, finance, and autonomous systems.
6. Development and deployment of intelligent computation systems: Evaluating the design, implementation, and real-world utility of systems that leverage AI for enhanced computational capabilities.
7. Advanced applications and innovations of traditional AI/ML/NLP Techniques: Exploring novel applications and innovations in AI/ML/NLP to address real-world challenges across different sectors.
8. AI and ethics (building trustworthy AI systems): Examining the methodologies and frameworks needed to ensure ethical considerations are integrated into AI development, with a focus on accountability, transparency, and fairness.
9. AI and privacy (Enhancing data security in AI operations): Investigating methods and technologies to safeguard personal and sensitive information in AI-driven applications, focusing on emerging challenges and solutions in data privacy.
10. AI and human creativity (exploring AI's role in artistic and creative processes): Examining how AI tools and techniques are transforming traditional creative industries, including art, music, writing, and design, and their implications for human creativity.

Important deadlines

• Submission deadline: Submissions are open until 30 December 2025.
• Publication date: Will be assessed on a rolling basis as they are received.

Submission instructions

Please read the [Guide for Authors] before submitting. All articles should be [submitted online ], please select [SI: AI/ML Advances] on submission.

The special issue welcomes all types of articles accepted by the journal. However, submissions must align with the scope of the special issue.

Guest editor

• Dr. Cheng Ye, Associate Scientist, Vanderbilt University Medical Center, The United States.Email: cheng.ye.1@vumc.org