AI in Healthcare: Navigating Legal Risk Assessment with JusticeBot

Sébastien Meeùs; Valentina Dalla Giovanna; Samyar Janatian; Hannes Westermann; Karim Benyekhlef; Grégory Lewkowicz

doi:10.3233/FAIA241277

AI in Healthcare: Navigating Legal Risk Assessment with JusticeBot

Sébastien Meeùs^*, Valentina Dalla Giovanna, Samyar Janatian, Hannes Westermann, Karim Benyekhlef, Grégory Lewkowicz

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

The increasing prevalence of technology in healthcare is leading to a corresponding rise in the complexity of the challenges facing hospitals. One such challenge is the difficulty of ensuring legal compliance for projects based on artificial intelligence and data processing. JusticeBot Laso is a tool designed to provide a comprehensive mapping of legal risks and a rating system to assist decision-makers in selecting AI projects. Our evaluation shows the tool improves risk identification accuracy from 20% to over 85%, and enhances risk scoring accuracy from 48% to 92%, compared to manual assessments.

Original language	English
Title of host publication	Legal Knowledge and Information Systems - JURIX 2024
Subtitle of host publication	37th Annual Conference
Editors	Jaromir Savelka, Jakub Harasta, Tereza Novotna, Jakub Misek
Publisher	IOS Press
Pages	384-386
Number of pages	3
Volume	395
ISBN (Electronic)	9781643685625
DOIs	https://doi.org/10.3233/FAIA241277
Publication status	Published - 1 Jan 2024
Event	37th Annual Conference on Legal Knowledge and Information Systems, JURIX 2024 - Brno, Czech Republic Duration: 11 Dec 2024 → 13 Dec 2024 https://jurix.nl/

Publication series

Series	Frontiers in Artificial Intelligence and Applications
Volume	395
ISSN	0922-6389

Conference

Conference	37th Annual Conference on Legal Knowledge and Information Systems, JURIX 2024
Abbreviated title	JURIX 2024
Country/Territory	Czech Republic
City	Brno
Period	11/12/24 → 13/12/24
Internet address	https://jurix.nl/

Keywords

AI Act
artificial intelligence
decision trees
GDPR
healthcare
innovation
JusticeBot
legal modeling
risk assessment

Access to Document

10.3233/FAIA241277Licence: CC BY-NC

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Meeùs, S., Dalla Giovanna, V., Janatian, S., Westermann, H., Benyekhlef, K., & Lewkowicz, G. (2024). AI in Healthcare: Navigating Legal Risk Assessment with JusticeBot. In J. Savelka, J. Harasta, T. Novotna, & J. Misek (Eds.), Legal Knowledge and Information Systems - JURIX 2024: 37th Annual Conference (Vol. 395, pp. 384-386). IOS Press. https://doi.org/10.3233/FAIA241277

Meeùs, Sébastien ; Dalla Giovanna, Valentina ; Janatian, Samyar et al. / AI in Healthcare : Navigating Legal Risk Assessment with JusticeBot. Legal Knowledge and Information Systems - JURIX 2024: 37th Annual Conference. editor / Jaromir Savelka ; Jakub Harasta ; Tereza Novotna ; Jakub Misek. Vol. 395 IOS Press, 2024. pp. 384-386 (Frontiers in Artificial Intelligence and Applications, Vol. 395).

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title = "AI in Healthcare: Navigating Legal Risk Assessment with JusticeBot",

abstract = "The increasing prevalence of technology in healthcare is leading to a corresponding rise in the complexity of the challenges facing hospitals. One such challenge is the difficulty of ensuring legal compliance for projects based on artificial intelligence and data processing. JusticeBot Laso is a tool designed to provide a comprehensive mapping of legal risks and a rating system to assist decision-makers in selecting AI projects. Our evaluation shows the tool improves risk identification accuracy from 20% to over 85%, and enhances risk scoring accuracy from 48% to 92%, compared to manual assessments.",

keywords = "AI Act, artificial intelligence, decision trees, GDPR, healthcare, innovation, JusticeBot, legal modeling, risk assessment",

author = "S{\'e}bastien Mee{\`u}s and {Dalla Giovanna}, Valentina and Samyar Janatian and Hannes Westermann and Karim Benyekhlef and Gr{\'e}gory Lewkowicz",

note = "Funding Information: This project was supported by the FARI - AI for the Common Good Institute (ULBVUB), financed by the European Union, with the support of the Brussels Capital Region (Innoviris and Paradigm). Publisher Copyright: {\textcopyright} 2024 The Authors.; 37th Annual Conference on Legal Knowledge and Information Systems, JURIX 2024, JURIX 2024 ; Conference date: 11-12-2024 Through 13-12-2024",

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doi = "10.3233/FAIA241277",

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volume = "395",

series = "Frontiers in Artificial Intelligence and Applications",

publisher = "IOS Press",

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editor = "Jaromir Savelka and Jakub Harasta and Tereza Novotna and Jakub Misek",

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Meeùs, S, Dalla Giovanna, V, Janatian, S, Westermann, H, Benyekhlef, K & Lewkowicz, G 2024, AI in Healthcare: Navigating Legal Risk Assessment with JusticeBot. in J Savelka, J Harasta, T Novotna & J Misek (eds), Legal Knowledge and Information Systems - JURIX 2024: 37th Annual Conference. vol. 395, IOS Press, Frontiers in Artificial Intelligence and Applications, vol. 395, pp. 384-386, 37th Annual Conference on Legal Knowledge and Information Systems, JURIX 2024, Brno, Czech Republic, 11/12/24. https://doi.org/10.3233/FAIA241277

AI in Healthcare: Navigating Legal Risk Assessment with JusticeBot. / Meeùs, Sébastien; Dalla Giovanna, Valentina; Janatian, Samyar et al.
Legal Knowledge and Information Systems - JURIX 2024: 37th Annual Conference. ed. / Jaromir Savelka; Jakub Harasta; Tereza Novotna; Jakub Misek. Vol. 395 IOS Press, 2024. p. 384-386 (Frontiers in Artificial Intelligence and Applications, Vol. 395).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

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T1 - AI in Healthcare

T2 - 37th Annual Conference on Legal Knowledge and Information Systems, JURIX 2024

AU - Meeùs, Sébastien

AU - Dalla Giovanna, Valentina

AU - Janatian, Samyar

AU - Westermann, Hannes

AU - Benyekhlef, Karim

AU - Lewkowicz, Grégory

N1 - Funding Information: This project was supported by the FARI - AI for the Common Good Institute (ULBVUB), financed by the European Union, with the support of the Brussels Capital Region (Innoviris and Paradigm). Publisher Copyright: © 2024 The Authors.

PY - 2024/1/1

Y1 - 2024/1/1

N2 - The increasing prevalence of technology in healthcare is leading to a corresponding rise in the complexity of the challenges facing hospitals. One such challenge is the difficulty of ensuring legal compliance for projects based on artificial intelligence and data processing. JusticeBot Laso is a tool designed to provide a comprehensive mapping of legal risks and a rating system to assist decision-makers in selecting AI projects. Our evaluation shows the tool improves risk identification accuracy from 20% to over 85%, and enhances risk scoring accuracy from 48% to 92%, compared to manual assessments.

AB - The increasing prevalence of technology in healthcare is leading to a corresponding rise in the complexity of the challenges facing hospitals. One such challenge is the difficulty of ensuring legal compliance for projects based on artificial intelligence and data processing. JusticeBot Laso is a tool designed to provide a comprehensive mapping of legal risks and a rating system to assist decision-makers in selecting AI projects. Our evaluation shows the tool improves risk identification accuracy from 20% to over 85%, and enhances risk scoring accuracy from 48% to 92%, compared to manual assessments.

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KW - artificial intelligence

KW - decision trees

KW - GDPR

KW - healthcare

KW - innovation

KW - JusticeBot

KW - legal modeling

KW - risk assessment

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DO - 10.3233/FAIA241277

M3 - Conference article in proceeding

VL - 395

T3 - Frontiers in Artificial Intelligence and Applications

SP - 384

EP - 386

BT - Legal Knowledge and Information Systems - JURIX 2024

A2 - Savelka, Jaromir

A2 - Harasta, Jakub

A2 - Novotna, Tereza

A2 - Misek, Jakub

PB - IOS Press

Y2 - 11 December 2024 through 13 December 2024

ER -

Meeùs S, Dalla Giovanna V, Janatian S, Westermann H, Benyekhlef K, Lewkowicz G. AI in Healthcare: Navigating Legal Risk Assessment with JusticeBot. In Savelka J, Harasta J, Novotna T, Misek J, editors, Legal Knowledge and Information Systems - JURIX 2024: 37th Annual Conference. Vol. 395. IOS Press. 2024. p. 384-386. (Frontiers in Artificial Intelligence and Applications, Vol. 395). doi: 10.3233/FAIA241277

AI in Healthcare: Navigating Legal Risk Assessment with JusticeBot

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Keywords

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