Designing Intelligent Agents in Normative Systems Toward Data Regulation Representation

Personal data protection regulation plays an important role in defining the rights and obligations of the agents involved in processing personal data (i.e., data subjects, controllers, and processors). These agents are allowed to execute actions to achieve their goals by obeying the personal data pr...

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Main Authors: Paulo Henrique Alves, Fernando Correia, Isabella Frajhof, Clarisse Sieckenius De Souza, Helio Lopes
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10124204/
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author Paulo Henrique Alves
Fernando Correia
Isabella Frajhof
Clarisse Sieckenius De Souza
Helio Lopes
author_facet Paulo Henrique Alves
Fernando Correia
Isabella Frajhof
Clarisse Sieckenius De Souza
Helio Lopes
author_sort Paulo Henrique Alves
collection DOAJ
description Personal data protection regulation plays an important role in defining the rights and obligations of the agents involved in processing personal data (i.e., data subjects, controllers, and processors). These agents are allowed to execute actions to achieve their goals by obeying the personal data protection rules; however, this exercise may spawn data flow information asymmetry; for instance, a company may have more information regarding how that data is being used than individuals. This asymmetry can undermine individuals’ ability to protect their rights and interests and lead to a lack of trust in organizations and government bodies responsible for protecting their data. In this context, this article proposes: (i) a consent metamodel based on the literature to aid agents in identifying their major concerns when sharing personal data; (ii) a structure to build use case scenarios in the personal data regulation context; (iii) an intelligent normative multiagent system architecture to represent the personal data regulation rights and obligations, as well as the agent’s decision-making process. The latter will consider the normative rewards and punishments in the aforementioned scenario structure; (iv) a use case in the open banking scenario. This article demonstrates how we propose to contribute to representing agents’ preferences and data regulation concerns. We do so with a normative multiagent system and designing agents with cognitive reasoning capabilities.
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spelling doaj.art-dda1ff703d7e4b31bf999c0e6748b64c2023-06-02T23:00:48ZengIEEEIEEE Access2169-35362023-01-0111515905160510.1109/ACCESS.2023.327629410124204Designing Intelligent Agents in Normative Systems Toward Data Regulation RepresentationPaulo Henrique Alves0https://orcid.org/0000-0002-0084-9157Fernando Correia1https://orcid.org/0000-0003-0394-056XIsabella Frajhof2https://orcid.org/0000-0002-3901-4907Clarisse Sieckenius De Souza3https://orcid.org/0000-0002-2154-4723Helio Lopes4https://orcid.org/0000-0003-4584-1455Department of Informatics, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, BrazilDepartment of Informatics, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, BrazilLaw Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, BrazilDepartment of Informatics, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, BrazilDepartment of Informatics, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, BrazilPersonal data protection regulation plays an important role in defining the rights and obligations of the agents involved in processing personal data (i.e., data subjects, controllers, and processors). These agents are allowed to execute actions to achieve their goals by obeying the personal data protection rules; however, this exercise may spawn data flow information asymmetry; for instance, a company may have more information regarding how that data is being used than individuals. This asymmetry can undermine individuals’ ability to protect their rights and interests and lead to a lack of trust in organizations and government bodies responsible for protecting their data. In this context, this article proposes: (i) a consent metamodel based on the literature to aid agents in identifying their major concerns when sharing personal data; (ii) a structure to build use case scenarios in the personal data regulation context; (iii) an intelligent normative multiagent system architecture to represent the personal data regulation rights and obligations, as well as the agent’s decision-making process. The latter will consider the normative rewards and punishments in the aforementioned scenario structure; (iv) a use case in the open banking scenario. This article demonstrates how we propose to contribute to representing agents’ preferences and data regulation concerns. We do so with a normative multiagent system and designing agents with cognitive reasoning capabilities.https://ieeexplore.ieee.org/document/10124204/BDI architecturedata regulationmultiagent systemnormspersonal data
spellingShingle Paulo Henrique Alves
Fernando Correia
Isabella Frajhof
Clarisse Sieckenius De Souza
Helio Lopes
Designing Intelligent Agents in Normative Systems Toward Data Regulation Representation
IEEE Access
BDI architecture
data regulation
multiagent system
norms
personal data
title Designing Intelligent Agents in Normative Systems Toward Data Regulation Representation
title_full Designing Intelligent Agents in Normative Systems Toward Data Regulation Representation
title_fullStr Designing Intelligent Agents in Normative Systems Toward Data Regulation Representation
title_full_unstemmed Designing Intelligent Agents in Normative Systems Toward Data Regulation Representation
title_short Designing Intelligent Agents in Normative Systems Toward Data Regulation Representation
title_sort designing intelligent agents in normative systems toward data regulation representation
topic BDI architecture
data regulation
multiagent system
norms
personal data
url https://ieeexplore.ieee.org/document/10124204/
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AT clarissesieckeniusdesouza designingintelligentagentsinnormativesystemstowarddataregulationrepresentation
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