AI Systems Trustworthiness Assessment: State of the Art

Afef Awadid, Kahina Amokrane-Ferka, Henri Sohier, Juliette Mattioli, Faouzi Adjed, Martin Gonzalez, Souhaiel Khalfaoui, Souhaiel Khalfaoui

2024

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.

Paper Citation

in Harvard Style

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 - Volume 1: MBSE-AI Integration; ISBN 978-989-758-682-8, SciTePress, pages 322-333. DOI: 10.5220/0012619600003645

in Bibtex Style

@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 - Volume 1: MBSE-AI Integration},
year={2024},
pages={322-333},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012619600003645},
isbn={978-989-758-682-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Model-Based Software and Systems Engineering - Volume 1: MBSE-AI Integration
TI - AI Systems Trustworthiness Assessment: State of the Art
SN - 978-989-758-682-8
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