5 papers
SeNeDiF-OOD: Semantic Nested Dichotomy Fusion for Out-of-Distribution Detection Methodology in Open-World Classification. A Case Study on Monument Style Classification
Ignacio Antequera-Sánchez, Juan Luis Suárez-Díaz, Rosana Montes +1
Out-of-distribution (OOD) detection is a fundamental requirement for the reliable deployment of artificial intelligence applications in open-world environments. However, addressing…
Data Science: a Natural Ecosystem
Emilio Porcu, Roy El Moukari, Laurent Najman +2
This manuscript provides a systemic and data-centric view of what we term essential data science, as a natural ecosystem with challenges and missions stemming from the fusion of da…
Making Sense of the Unsensible: Reflection, Survey, and Challenges for XAI in Large Language Models Toward Human-Centered AI
Francisco Herrera
As large language models (LLMs) are increasingly deployed in sensitive domains such as healthcare, law, and education, the demand for transparent, interpretable, and accountable AI…
Aligning Trustworthy AI with Democracy: A Dual Taxonomy of Opportunities and Risks
Oier Mentxaka, Natalia Díaz-Rodríguez, Mark Coeckelbergh +5
Artificial Intelligence (AI) poses both significant risks and valuable opportunities for democratic governance. This paper introduces a dual taxonomy to evaluate AI's complex relat…
A Framework for Responsible AI Systems: Building Societal Trust through Domain Definition, Trustworthy AI Design, Auditability, Accountability, and Governance
Andrés Herrera-Poyatos, Javier Del Ser, Marcos López de Prado +3
Responsible Artificial Intelligence (RAI) addresses the ethical and regulatory challenges of deploying AI systems in high-risk scenarios. This paper proposes a comprehensive framew…