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Authors: Afef Awadid 1 ; Kahina Amokrane-Ferka 1 ; Henri Sohier 1 ; Juliette Mattioli 2 ; Faouzi Adjed 1 ; Martin Gonzalez 1 and Souhaiel Khalfaoui 1 ; 3

Affiliations: 1 IRT SystemX, France ; 2 Thales, France ; 3 Valeo, France

Keyword(s): AI-Based Systems, Trustworthiness Assessment, Trustworthiness Attributes, Metrics, State of the Art Review.

Abstract: Model-based System Engineering (MBSE) has been advocated as a promising approach to reduce the complexity of AI-based systems development. However, given the uncertainties and risks associated with Artificial Intelligence (AI), the successful application of MBSE requires the assessment of AI trustworthiness. To deal with this issue, this paper provides a state of the art review of AI trustworthiness assessment in terms of trustworthiness attributes/ characteristics and their corresponding evaluation metrics. Examples of such attributes include data quality, robustness, and explainability. The proposed review is based on academic and industrial literature conducted within the Confiance.ai research program.

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Paper citation in several formats:
Awadid, A.; Amokrane-Ferka, K.; Sohier, H.; Mattioli, J.; Adjed, F.; Gonzalez, M. and Khalfaoui, S. (2024). AI Systems Trustworthiness Assessment: State of the Art. In Proceedings of the 12th International Conference on Model-Based Software and Systems Engineering - MBSE-AI Integration; ISBN 978-989-758-682-8; ISSN 2184-4348, SciTePress, pages 322-333. DOI: 10.5220/0012619600003645

@conference{mbse-ai integration24,
author={Afef Awadid. and Kahina Amokrane{-}Ferka. and Henri Sohier. and Juliette Mattioli. and Faouzi Adjed. and Martin Gonzalez. and Souhaiel Khalfaoui.},
title={AI Systems Trustworthiness Assessment: State of the Art},
booktitle={Proceedings of the 12th International Conference on Model-Based Software and Systems Engineering - MBSE-AI Integration},
year={2024},
pages={322-333},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012619600003645},
isbn={978-989-758-682-8},
issn={2184-4348},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Model-Based Software and Systems Engineering - MBSE-AI Integration
TI - AI Systems Trustworthiness Assessment: State of the Art
SN - 978-989-758-682-8
IS - 2184-4348
AU - Awadid, A.
AU - Amokrane-Ferka, K.
AU - Sohier, H.
AU - Mattioli, J.
AU - Adjed, F.
AU - Gonzalez, M.
AU - Khalfaoui, S.
PY - 2024
SP - 322
EP - 333
DO - 10.5220/0012619600003645
PB - SciTePress

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