Creating Meaningful Intelligence for Decision-Making by Modelling Complexities of Human Influence: Review and Position - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2022

Creating Meaningful Intelligence for Decision-Making by Modelling Complexities of Human Influence: Review and Position

Abstract

Strategic decision-making still struggles to cope with the interference of people in its proposed plans, creating a gap between idealised and real-world versions. Even when the existence of humans is considered, models and abstractions tend to be simplistic and lacking in complex human traits (e. g. creativity, sentiment). We analyse the current scientific landscape in the dimensions that overlap in the field of strategic decision making and posit that to provide means to a more informed and robust decision-making, humans should not only be seen as elements that need to accept and adopt decisions, but also as actors that affect their outcomes. Humans should be understood as central pieces and the strategic decision-making process should thus consider their importance both in techniques that foster co-creation, and also in developing dynamic models that demonstrate their influence and impact. In this article, we describe this problem-space and outline an approach integrating Decision Intelligence, Enterprise Architecture, Design Thinking, and architectural principles to achieve a human-centric, adaptive strategic design. We also discuss the influence of information presentation and visuals for meaningful participation in strategic decision-making processes.
Fichier principal
Vignette du fichier
528070_1_En_4_Chapter.pdf (398.32 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04308377 , version 1 (27-11-2023)

Licence

Identifiers

Cite

Paulo Pina, Rui Neves-Silva. Creating Meaningful Intelligence for Decision-Making by Modelling Complexities of Human Influence: Review and Position. 13th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Jun 2022, Caparica, Portugal. pp.35-49, ⟨10.1007/978-3-031-07520-9_4⟩. ⟨hal-04308377⟩
30 View
18 Download

Altmetric

Share

More