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Trustworthy AI
Also known as: Trustworthy artificial intelligence, trustworthy AI systems, Trustworthy AI, trustworthy neuro-symbolic AI systems, trusted AI systems
Facts (11)
Sources
A Comprehensive Review of Neuro-symbolic AI for Robustness ... link.springer.com Dec 9, 2025 3 facts
referenceMichel-Delétie, C. and Sarker, M.K. conducted a systematic review of neuro-symbolic methods for trustworthy AI.
claimRobustness is a critical component of trustworthy AI because it directly impacts the dependability and consistency of AI-driven decisions, particularly in high-stakes fields like healthcare, finance, and autonomous vehicles.
referenceGaur, M. and Sheth, A. outlined the requirements for building trustworthy neuro-symbolic AI systems, specifically focusing on consistency, reliability, explainability, and safety.
Neuro-symbolic AI - Wikipedia en.wikipedia.org 2 facts
claimAngelo Dalli presented a keynote at WAICF 2025 titled 'Why neurosymbolic AI is the future of trustworthy AI'.
referenceGary Marcus and Ernest Davis authored the book 'Rebooting AI: Building Artificial Intelligence We Can Trust', which discusses the development of trustworthy artificial intelligence.
[PDF] Neuro-Symbolic methods for Trustworthy AI: a systematic review neurosymbolic-ai-journal.com 1 fact
claimThe review titled "Neuro-Symbolic methods for Trustworthy AI: a systematic review" aims to explore the application of Neuro-Symbolic (NeSy) systems in addressing various trustworthiness issues in artificial intelligence.
Neuro-Symbolic AI: Explainability, Challenges & Future Trends linkedin.com Dec 15, 2025 1 fact
claimThe future of trustworthy AI systems involves hybrid models that combine interpretable systems with complex systems to enhance human-AI interaction.
Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org Nov 7, 2024 1 fact
claimHooshyar et al. (2023) argue that augmenting deep neural networks with symbolic knowledge can contribute to the development of trustworthy and interpretable AI systems for education.
Practices, opportunities and challenges in the fusion of knowledge ... frontiersin.org 1 fact
referenceD. Kaur, S. Uslu, K. J. Rittichier, and A. Durresi published 'Trustworthy artificial intelligence: a review' in ACM Computing Surveys in 2022.
Unknown source 1 fact
claimThe NeuroSymbolic AI approach is better suited for creating trustworthy AI systems.
Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org 1 fact
claimThe authors of the paper 'Building Trustworthy NeuroSymbolic AI Systems' argue that NeuroSymbolic AI is better suited for creating trusted AI systems than statistical or symbolic AI methods used in isolation, because trust requires consistency, reliability, explainability, and safety.