FASTER-AI: A Comprehensive Framework for Enhancing the Trustworthiness of Artificial Intelligence in Web Information Systems

Christos Troussas, Christos Papakostas, Akrivi Krouska, Phivos Mylonas, Cleo Sgouropoulou

2024

Abstract

With increasing embedding of artificial intelligence (AI) in web information systems (WIS), the maximum assurance on the reliability of such AI systems is solicited. Although this aspect is gaining importance, no comprehensive framework has yet been developed to ensure AI reliability. This paper aims to bridge that gap by proposing the AI FASTER framework to enhance the reliability of AI in WIS. The key dimensions of concern within the framework are FASTER-AI: Fairness/bias mitigation, explainability/transparency, security/privacy, robustness, and ethical considerations/accountability. Each one guides in precisely the area where trust shall be accomplished: a decrease in bias, model interpretability, protection of data, resilience of models, and ethics in governance. The implementation methodology for these dimensions involves preliminary assessment, planning, integration, testing, and continuous improvement. Validation of proof for FASTER-AI was created based on in-depth case studies across different verticals: e-commerce, finance, health, and fraud detection. This work has demonstrated how FASTER-AI is applied through illustrative case studies showing promising performance. From the initial results of high improvement in terms of fairness, transparency, security, and robustness, it may be effectively inferred that FASTER-AI can be successfully applied.

Paper Citation

in Harvard Style

Troussas C., Papakostas C., Krouska A., Mylonas P. and Sgouropoulou C. (2024). FASTER-AI: A Comprehensive Framework for Enhancing the Trustworthiness of Artificial Intelligence in Web Information Systems. In Proceedings of the 20th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST; ISBN 978-989-758-718-4, SciTePress, pages 385-392. DOI: 10.5220/0013061100003825

in Bibtex Style

@conference{webist24,
author={Christos Troussas and Christos Papakostas and Akrivi Krouska and Phivos Mylonas and Cleo Sgouropoulou},
title={FASTER-AI: A Comprehensive Framework for Enhancing the Trustworthiness of Artificial Intelligence in Web Information Systems},
booktitle={Proceedings of the 20th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST},
year={2024},
pages={385-392},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013061100003825},
isbn={978-989-758-718-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST
TI - FASTER-AI: A Comprehensive Framework for Enhancing the Trustworthiness of Artificial Intelligence in Web Information Systems
SN - 978-989-758-718-4
AU - Troussas C.
AU - Papakostas C.
AU - Krouska A.
AU - Mylonas P.
AU - Sgouropoulou C.
PY - 2024
SP - 385
EP - 392
DO - 10.5220/0013061100003825
PB - SciTePress