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Evaluation methods and metrics towards trustworthy AI: literature review with expert knowledge

https://doi.org/10.2139/ssrn.6160607
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10462-024-10824-0openalex-snapshot
A survey of safety and trustworthiness of large language models through the lens of verification and validation
inferredcites →https://doi.org/10.1007/s10462-024-11005-9openalex-snapshot
Robustness in deep learning models for medical diagnostics: security and adversarial challenges towards robust AI applications
inferredcites →https://doi.org/10.1007/s43681-023-00258-9openalex-snapshot
From ethical AI frameworks to tools: a review of approaches
inferredcites →https://doi.org/10.1007/s44204-023-00063-5openalex-snapshot
Trustworthy artificial intelligence
inferredcites →https://doi.org/10.1016/j.eswa.2023.123066openalex-snapshot
Evaluation of trustworthy artificial intelligent healthcare applications using multi-criteria decision-making approach
inferredcites →https://doi.org/10.1038/nature14539openalex-snapshot
Deep learning
inferredcites →https://doi.org/10.1080/1364557032000119616openalex-snapshot
Scoping studies: towards a methodological framework
inferredcites →https://doi.org/10.1097/js9.0000000000001583openalex-snapshot
Advancing generative artificial intelligence in medicine: recommendations for standardized evaluation
inferredcites →https://doi.org/10.1109/jiot.2023.3300845openalex-snapshot
A Trusted Cloud–Edge Decision Architecture Based on Blockchain and MLP for AIoT
inferredcites →https://doi.org/10.1109/jiot.2024.3357705openalex-snapshot
A Trustworthiness Evaluation Mechanism Based on Principles–Assumptions Model
inferredcites →https://doi.org/10.1109/mis.2022.3197950openalex-snapshot
From Features Engineering to Scenarios Engineering for Trustworthy AI: I&I, C&C, and V&V
inferredcites →https://doi.org/10.1109/tccn.2024.3412394openalex-snapshot
Trusted and Efficient Task Offloading in Vehicular Edge Computing Networks
inferredcites →https://doi.org/10.1109/tdsc.2024.3382321openalex-snapshot
VeriFi: Towards Verifiable Federated Unlearning
inferredcites →https://doi.org/10.1145/3491209openalex-snapshot
Trustworthy Artificial Intelligence: A Review
inferredcites →https://doi.org/10.1145/3555803openalex-snapshot
Trustworthy AI: From Principles to Practices
inferredcites →https://doi.org/10.1145/3721976openalex-snapshot
Towards a Better Understanding of Evaluating Trustworthiness in AI Systems
inferredcites →https://doi.org/10.1186/s13326-023-00293-9openalex-snapshot
Automatic transparency evaluation for open knowledge extraction systems
inferredcites →https://doi.org/10.3233/ais-210602openalex-snapshot
A trust evaluation model for secure data aggregation in smart grids infrastructures for smart cities
inferredcites →https://doi.org/10.3389/fdata.2024.1467222openalex-snapshot
Establishing and evaluating trustworthy AI: overview and research challenges
inferredcites →https://doi.org/10.3389/fdgth.2024.1474692openalex-snapshot
Establishing trust in artificial intelligence-driven autonomous healthcare systems: an expert-guided framework
inferredcites →https://doi.org/10.3390/jsan11020021openalex-snapshot
Sensitivity of Machine Learning Approaches to Fake and Untrusted Data in Healthcare Domain
inferredcites →https://doi.org/10.3390/rs16234529openalex-snapshot
Ethical Framework to Assess and Quantify the Trustworthiness of Artificial Intelligence Techniques: Application Case in Remote Sensing
inferredcites →https://doi.org/10.5220/0012619600003645openalex-snapshot
AI Systems Trustworthiness Assessment: State of the Art
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.