Bridging Human and AI Decision-Making with LLMs : The RAGADA Approach

Tapio Pitkäranta; Leena Pitkäranta

doi:10.5220/0012705000003690

Bridging Human and AI Decision-Making with LLMs : The RAGADA Approach

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

1 Citation (Scopus)

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Abstract

The Retrieval Augmented Generation Algorithmic Decision Alignment (RAGADA) architecture is an advancement in AI-augmented decision-making for corporate environments. This paper discusses RAGADA’s innovative architecture that merges RAG and Multi-Agent System (MAS) with sophisticated business algorithms and dynamic interfaces, enhancing natural language interaction between AI systems and users. This fusion extends AI’s reach, facilitating adaptable decision-making tools for leaders, in line with evolving business strategies and ethical standards. Experimental validation of RAGADA within the banking sector, involving diverse stakeholder groups ranging from customers to business and ethical managers, confirms its effectiveness. The system adeptly translates natural language inquiries into actionable insights, thereby improving the user experience and decision-making transparency. This validation underscores RAGADA’s potential to transform stakeholder engagement and demonstrates a leap in utilizing AI for strategic and ethical business management.

Original language	English
Title of host publication	Proceedings of the 26th International Conference on Enterprise Information Systems, ICEIS 2024
Editors	Joaquim Filipe, Michal Smialek, Alexander Brodsky, Slimane Hammoudi
Publisher	SciTePress
Pages	812-819
Number of pages	8
Volume	1
ISBN (Electronic)	978-989-758-692-7
DOIs	https://doi.org/10.5220/0012705000003690
Publication status	Published - 2024
MoE publication type	A4 Conference publication
Event	International Conference on Enterprise Information Systems - Angers, France Duration: 28 Apr 2024 → 30 Apr 2024 Conference number: 26

Publication series

Name	International Conference on Enterprise Information Systems, ICEIS - Proceedings
Volume	1
ISSN (Electronic)	2184-4992

Conference

Conference	International Conference on Enterprise Information Systems
Abbreviated title	ICEIS
Country/Territory	France
City	Angers
Period	28/04/2024 → 30/04/2024

Keywords

IR Information Retrieval
LLM Large Language Models
Multi-Agent Systems (MAS)
RAG: Retrieval Augmented Generation
RAGADA: Retrieval Augmented Generation Algorithmic Decision Alignment

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Bridging Human and AI Decision-Making with LLMs_The RAGADA ApproachFinal published version, 939 KBLicence: CC BY-NC-ND

Cite this

Pitkäranta, T., & Pitkäranta, L. (2024). Bridging Human and AI Decision-Making with LLMs : The RAGADA Approach. In J. Filipe, M. Smialek, A. Brodsky, & S. Hammoudi (Eds.), Proceedings of the 26th International Conference on Enterprise Information Systems, ICEIS 2024 (Vol. 1, pp. 812-819). (International Conference on Enterprise Information Systems, ICEIS - Proceedings; Vol. 1). SciTePress. https://doi.org/10.5220/0012705000003690

Pitkäranta, Tapio ; Pitkäranta, Leena. / Bridging Human and AI Decision-Making with LLMs : The RAGADA Approach. Proceedings of the 26th International Conference on Enterprise Information Systems, ICEIS 2024. editor / Joaquim Filipe ; Michal Smialek ; Alexander Brodsky ; Slimane Hammoudi. Vol. 1 SciTePress, 2024. pp. 812-819 (International Conference on Enterprise Information Systems, ICEIS - Proceedings).

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title = "Bridging Human and AI Decision-Making with LLMs : The RAGADA Approach",

abstract = "The Retrieval Augmented Generation Algorithmic Decision Alignment (RAGADA) architecture is an advancement in AI-augmented decision-making for corporate environments. This paper discusses RAGADA{\textquoteright}s innovative architecture that merges RAG and Multi-Agent System (MAS) with sophisticated business algorithms and dynamic interfaces, enhancing natural language interaction between AI systems and users. This fusion extends AI{\textquoteright}s reach, facilitating adaptable decision-making tools for leaders, in line with evolving business strategies and ethical standards. Experimental validation of RAGADA within the banking sector, involving diverse stakeholder groups ranging from customers to business and ethical managers, confirms its effectiveness. The system adeptly translates natural language inquiries into actionable insights, thereby improving the user experience and decision-making transparency. This validation underscores RAGADA{\textquoteright}s potential to transform stakeholder engagement and demonstrates a leap in utilizing AI for strategic and ethical business management.",

keywords = "IR Information Retrieval, LLM Large Language Models, Multi-Agent Systems (MAS), RAG: Retrieval Augmented Generation, RAGADA: Retrieval Augmented Generation Algorithmic Decision Alignment",

author = "Tapio Pitk{\"a}ranta and Leena Pitk{\"a}ranta",

note = "Publisher Copyright: Copyright {\textcopyright} 2024 by SCITEPRESS – Science and Technology Publications, Lda.; International Conference on Enterprise Information Systems, ICEIS ; Conference date: 28-04-2024 Through 30-04-2024",

year = "2024",

doi = "10.5220/0012705000003690",

language = "English",

volume = "1",

series = "International Conference on Enterprise Information Systems, ICEIS - Proceedings",

publisher = "SciTePress",

pages = "812--819",

editor = "Joaquim Filipe and Michal Smialek and Alexander Brodsky and Slimane Hammoudi",

booktitle = "Proceedings of the 26th International Conference on Enterprise Information Systems, ICEIS 2024",

address = "Portugal",

}

Pitkäranta, T & Pitkäranta, L 2024, Bridging Human and AI Decision-Making with LLMs : The RAGADA Approach. in J Filipe, M Smialek, A Brodsky & S Hammoudi (eds), Proceedings of the 26th International Conference on Enterprise Information Systems, ICEIS 2024. vol. 1, International Conference on Enterprise Information Systems, ICEIS - Proceedings, vol. 1, SciTePress, pp. 812-819, International Conference on Enterprise Information Systems, Angers, France, 28/04/2024. https://doi.org/10.5220/0012705000003690

Bridging Human and AI Decision-Making with LLMs : The RAGADA Approach. / Pitkäranta, Tapio ; Pitkäranta, Leena.
Proceedings of the 26th International Conference on Enterprise Information Systems, ICEIS 2024. ed. / Joaquim Filipe; Michal Smialek; Alexander Brodsky; Slimane Hammoudi. Vol. 1 SciTePress, 2024. p. 812-819 (International Conference on Enterprise Information Systems, ICEIS - Proceedings; Vol. 1).

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

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AU - Pitkäranta, Leena

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N2 - The Retrieval Augmented Generation Algorithmic Decision Alignment (RAGADA) architecture is an advancement in AI-augmented decision-making for corporate environments. This paper discusses RAGADA’s innovative architecture that merges RAG and Multi-Agent System (MAS) with sophisticated business algorithms and dynamic interfaces, enhancing natural language interaction between AI systems and users. This fusion extends AI’s reach, facilitating adaptable decision-making tools for leaders, in line with evolving business strategies and ethical standards. Experimental validation of RAGADA within the banking sector, involving diverse stakeholder groups ranging from customers to business and ethical managers, confirms its effectiveness. The system adeptly translates natural language inquiries into actionable insights, thereby improving the user experience and decision-making transparency. This validation underscores RAGADA’s potential to transform stakeholder engagement and demonstrates a leap in utilizing AI for strategic and ethical business management.

AB - The Retrieval Augmented Generation Algorithmic Decision Alignment (RAGADA) architecture is an advancement in AI-augmented decision-making for corporate environments. This paper discusses RAGADA’s innovative architecture that merges RAG and Multi-Agent System (MAS) with sophisticated business algorithms and dynamic interfaces, enhancing natural language interaction between AI systems and users. This fusion extends AI’s reach, facilitating adaptable decision-making tools for leaders, in line with evolving business strategies and ethical standards. Experimental validation of RAGADA within the banking sector, involving diverse stakeholder groups ranging from customers to business and ethical managers, confirms its effectiveness. The system adeptly translates natural language inquiries into actionable insights, thereby improving the user experience and decision-making transparency. This validation underscores RAGADA’s potential to transform stakeholder engagement and demonstrates a leap in utilizing AI for strategic and ethical business management.

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PB - SciTePress

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ER -

Pitkäranta T , Pitkäranta L. Bridging Human and AI Decision-Making with LLMs : The RAGADA Approach. In Filipe J, Smialek M, Brodsky A, Hammoudi S, editors, Proceedings of the 26th International Conference on Enterprise Information Systems, ICEIS 2024. Vol. 1. SciTePress. 2024. p. 812-819. (International Conference on Enterprise Information Systems, ICEIS - Proceedings). doi: 10.5220/0012705000003690

Bridging Human and AI Decision-Making with LLMs : The RAGADA Approach

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