Human-Centered AI: Explainability, Fairness, and Social Impact

Dear Colleagues,

As artificial intelligence becomes increasingly embedded in daily life and decision-making, the need for innovative methodologies and interdisciplinary approaches to design, evaluate, and govern human-centered AI systems has become increasingly critical. Explainability and fairness stand at the forefront of this transformation, offering new pathways for building trust and ensuring accountability in algorithmic processes. Meanwhile, the proliferation of AI applications across sectors presents both unprecedented opportunities for social benefit and significant challenges in mitigating bias, protecting human rights, and maintaining meaningful human oversight.

This special issue aims to explore the intersection of human-centered AI, explainability, fairness, and societal impact. It seeks to highlight cutting-edge research, technological innovations, and ethical frameworks that enhance the development, deployment, and responsible governance of AI systems aligned with human values. Topics of interest include:

• Explainable AI (XAI) techniques and interpretable machine learning models

• Fairness metrics, bias detection, and mitigation strategies in AI systems

• Equity, access, and digital inclusion in AI deployment across diverse communities

• The evolving role of human oversight and human-AI collaboration in critical domains

• Ethical considerations and value alignment in autonomous decision-making systems

• Data governance, privacy protection, and individual agency in AI-driven environments

• Comparative studies on AI fairness and explainability across cultural and regulatory contexts

• Policy frameworks and capacity-building for responsible AI innovation and governance

We welcome original research articles, case studies, and reviews that contribute to advancing the dialogue and practice in this dynamic and evolving field.