An Explainable AI Tool for Operational Risks Evaluation of AI Systems for SMEs

The Anh Han; Max Pandit; Sina Joneidy; M M  Hasan; Julius  Hossain; M Hoque Tania; M A  Hossain; N  Nourmohammadi

doi:10.1109/SKIMA59232.2023.10387301

An Explainable AI Tool for Operational Risks Evaluation of AI Systems for SMEs

The Anh Han, Max Pandit, Sina Joneidy, M M Hasan, Julius Hossain, M Hoque Tania, M A Hossain, N Nourmohammadi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This research addresses the challenges faced by SMEs in deploying Artificial Intelligence (AI) systems ethically and securely. Engaging with twenty SMEs through workshops and surveys, we developed an evaluation tool utilizing explainable AI. This tool examines AI systems' robustness, biases, and vulnerabilities, ensuring ethical usage and legal compliance. By conducting a pilot study on AI-driven language models, we demonstrate the tool's ability to assess risks across various domains, fostering trust and accountability in AI integration for SMEs.

Original language	English
Title of host publication	2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)
Publisher	IEEE
ISBN (Electronic)	9798350316551
DOIs	https://doi.org/10.1109/SKIMA59232.2023.10387301
Publication status	Published - 23 Jan 2024
Event	2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) - Kuala Lumpur, Malaysia Duration: 8 Dec 2023 → 10 Dec 2023 https://camtech.edu.kh/skima-2023/

Conference

Conference	2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)
Country/Territory	Malaysia
City	Kuala Lumpur
Period	8/12/23 → 10/12/23
Internet address	https://camtech.edu.kh/skima-2023/

Access to Document

10.1109/SKIMA59232.2023.10387301

Embargoed Document

Full text
Accepted author manuscript, 2.37 MB
Licence: Other
Embargo ends: 22/01/26
Request copy

Cite this

@inproceedings{9f9619b9ad244458b0cc945bd405975e,

title = "An Explainable AI Tool for Operational Risks Evaluation of AI Systems for SMEs",

abstract = "This research addresses the challenges faced by SMEs in deploying Artificial Intelligence (AI) systems ethically and securely. Engaging with twenty SMEs through workshops and surveys, we developed an evaluation tool utilizing explainable AI. This tool examines AI systems' robustness, biases, and vulnerabilities, ensuring ethical usage and legal compliance. By conducting a pilot study on AI-driven language models, we demonstrate the tool's ability to assess risks across various domains, fostering trust and accountability in AI integration for SMEs.",

author = "Han, {The Anh} and Max Pandit and Sina Joneidy and Hasan, {M M} and Julius Hossain and {Hoque Tania}, M and Hossain, {M A} and N Nourmohammadi",

year = "2024",

month = jan,

day = "23",

doi = "10.1109/SKIMA59232.2023.10387301",

language = "English",

booktitle = "2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)",

publisher = "IEEE",

note = "2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA) ; Conference date: 08-12-2023 Through 10-12-2023",

url = "https://camtech.edu.kh/skima-2023/",

}

Han, TA , Pandit, M , Joneidy, S, Hasan, MM, Hossain, J, Hoque Tania, M, Hossain, MA & Nourmohammadi, N 2024, An Explainable AI Tool for Operational Risks Evaluation of AI Systems for SMEs. in 2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA). IEEE, 2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Kuala Lumpur, Malaysia, 8/12/23. https://doi.org/10.1109/SKIMA59232.2023.10387301

TY - GEN

T1 - An Explainable AI Tool for Operational Risks Evaluation of AI Systems for SMEs

AU - Han, The Anh

AU - Pandit, Max

AU - Joneidy, Sina

AU - Hasan, M M

AU - Hossain, Julius

AU - Hoque Tania, M

AU - Hossain, M A

AU - Nourmohammadi, N

PY - 2024/1/23

Y1 - 2024/1/23

N2 - This research addresses the challenges faced by SMEs in deploying Artificial Intelligence (AI) systems ethically and securely. Engaging with twenty SMEs through workshops and surveys, we developed an evaluation tool utilizing explainable AI. This tool examines AI systems' robustness, biases, and vulnerabilities, ensuring ethical usage and legal compliance. By conducting a pilot study on AI-driven language models, we demonstrate the tool's ability to assess risks across various domains, fostering trust and accountability in AI integration for SMEs.

AB - This research addresses the challenges faced by SMEs in deploying Artificial Intelligence (AI) systems ethically and securely. Engaging with twenty SMEs through workshops and surveys, we developed an evaluation tool utilizing explainable AI. This tool examines AI systems' robustness, biases, and vulnerabilities, ensuring ethical usage and legal compliance. By conducting a pilot study on AI-driven language models, we demonstrate the tool's ability to assess risks across various domains, fostering trust and accountability in AI integration for SMEs.

U2 - 10.1109/SKIMA59232.2023.10387301

DO - 10.1109/SKIMA59232.2023.10387301

M3 - Conference contribution

BT - 2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)

PB - IEEE

T2 - 2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)

Y2 - 8 December 2023 through 10 December 2023

ER -

An Explainable AI Tool for Operational Risks Evaluation of AI Systems for SMEs

Abstract

Conference

Access to Document

Embargoed Document

Fingerprint

Cite this