AI-Based Behavioral Competency Assessment Tool to Enhance Navigational Safety

Liu, Li‐Li; Singh, Virdi Satinder; Hon, Samuel; Le, Diem Duy; Tan, Kelvin; Zhang, Dongke; Chai, David

doi:10.1109/iceccme52200.2021.9590891

Cited by 2 publications

(1 citation statement)

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“…Behavior Competencies (BC): Originally, the term "behavior competency" refers to measuring and assessing human performance in specific applications, such as evaluating navigational competence ( [35]) or understanding factors influencing high-performing system engineers [36]. The versatility of this concept in categorizing human performance makes it an intriguing candidate for describing the capabilities of AIS.…”

Section: B the Concept Of Odd And Its Related Behavior Competenciesmentioning

confidence: 99%

Trustworthiness Assurance Assessment for High-Risk AI-Based Systems

Stettinger,

Weissensteiner,

Khastgir

2024

IEEE Access

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This work proposes methodologies for ensuring the trustworthiness of high-risk artificial intelligence (AI) systems (AIS) to achieve compliance with the European Union's (EU) AI Act. Highrisk classified AIS must fulfill seven requirements to be considered trustworthy and human-centric, and subsequently be considered for deployment. These requirements are equally important, mutually supportive, and should be implemented and evaluated throughout the AI lifecycle. The assurance of trustworthiness is influenced by ethical considerations, amongst others. Hence, the operational design domain (ODD) and behavior competency (BC) concepts from the automated driving domain are utilized in risk assessment strategies to quantify different types of residual risks. The methodology presented is guided by the consistent application of the ODD and its related BC concept throughout the entire AI lifecycle, focusing on the trustworthiness assurance framework and its associated process as the main pillars for AIS certification. The achievement of the overall objective of trustworthy and human-centric AIS is divided into seven interconnected sub-goals: the formulation of use restrictions, the trustworthiness assurance/argument itself, the identification of dysfunctional cases, the utilization of scenario databases and datasets, the application of metrics for evaluation, the implementation of the proposed concept across the AI lifecycle, and sufficient consideration of human factors. The role of standards in the assurance process is discussed, considering any existing gaps and areas for improvement. The work concludes with a summary of the developed approach, highlighting key takeaways and action points. Finally, a roadmap to ensure trustworthy and human-centric behavior of future AIS is outlined.

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Section: B the Concept Of Odd And Its Related Behavior Competenciesmentioning

confidence: 99%