Foundation Models and Generative AI for Human-Centric Intelligent Systems

AIM AND SCOPE

Foundation models, including Large Language Models, vision-language models, and domain-specific foundation models, have catalyzed a paradigm shift in Artificial Intelligence, enabling unprecedented capabilities in natural language understanding, multimodal reasoning, and content generation. Concurrently, agentic AI—systems that take autonomous actions to achieve user-specified goals—has transitioned from research pilots to early production deployment across industries. The intersection of these transformative technologies with human-centric intelligent systems presents both extraordinary opportunities and fundamental challenges. From personalized AI assistants and intelligent decision-support
systems to creative co-production tools and autonomous agents, foundation models and generative AI are reshaping how
users, organizations, and communities interact with computing systems.

Despite the remarkable capabilities of foundation models and generative AI, their integration into human-centric systems still faces critical gap: trustworthiness, transparency, and responsible deployment are often treated as afterthoughts rather than design priorities. Foundation models are prone to hallucinations, bias amplification, and opaque reasoning processes, raising fundamental concerns about their reliability in human-facing applications. Agentic AI compounds these risks by introducing autonomous decision-making without adequate human oversight or accountability frameworks. Furthermore, data privacy, model governance, resource efficiency, and adaptability across diverse user contexts remain unresolved challenges that directly impact user trust and adoption. Existing research predominantly focuses on model architecture and performance benchmarks, leaving a substantial gap between what these models can do and what they should do when deployed for human-centric systems where fairness, explainability, privacy, and alignment with human values are paramount.

This Special Issue aims to advance the theory and practice of foundation models and generative AI specifically tailored to human-centric intelligent systems, with a rigorous focus on trust, adaptability, and responsible deployment. By bringing together interdisciplinary contributions at the intersection of foundation models, generative AI, humancomputer interaction, and responsible AI, this Special Issue seeks to establish a consolidated knowledge hub that bridges technical innovation with user-centered principles. It aims to inspire the development of foundation-modelpowered systems that are not only powerful but also transparent, fair, privacy-respecting, and aligned with human
needs.

TOPICS:

- Trustworthy foundation models for human-centric decision support with explainability and faithfulness
- Fairness-aware generative AI and bias mitigation strategies for human-centric intelligent systems
- Privacy-preserving fine-tuning and federated learning of language models for personalized services
- Multimodal foundation models for enhancing human-AI collaboration in complex task environments
- Human evaluation frameworks for foundation model alignment beyond benchmark metrics
- Energy-efficient and resource-aware deployment of foundation models on edge and mobile devices
- Generative AI for personalized content creation, adaptive interfaces, and assistive technologies
- Continual learning and domain adaptation of foundation models to dynamic user needs
- Human-controllable text-to-image and text-to-video generation with safety constraints
- Case studies and deployment experiences of foundation-model-powered systems in healthcare, education, creativity, and public services

HOW TO SUBMIT:

Deadline: June 30, 2027

Before submission authors should carefully read the Instructions for Authors -www.degruyterbrill.com/publication/journal_key/JISYS/downloadAsset/JISYS_Instruction%20for%20Authors.pdf

All submissions to the Special Issue must be made electronically via the online submission system https://mc.manuscriptcentral.com/jisys

All manuscripts will undergo the standard peer-review process (single-blind, at least two independent reviewers).


When entering your submission via the online submission system please choose the category: "SI Fundation models".


Submission of a manuscript implies that the work described has not been published before and is not under consideration for publication anywhere else.

We are looking forward to your submission!

In case of any further questions please contact:
Editorial Office – JISYS_Editorial@degruyterbrill.com