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Exploring the potential of Artificial Intelligence in system mapping

2025-01-30Dissertação de mestrado Acesso aberto
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datacite.subject.fosCiências Sociais::Economia e Gestãopt_PT
dc.contributor.advisorZózimo, Ricardo
dc.contributor.authorHeur, Maximilian Michael D'
dc.date.accessioned2025-03-31T10:07:18Z
dc.date.available2025-03-31T10:07:18Z
dc.date.issued2025-01-30
dc.date.submitted2024-12-17
dc.description.abstractRapid population growth, inequalities, and technological disruption create interconnected societal challenges driven by dynamic interactions among social, technological, and environmental factors. System mapping, while vital for understanding these complexities, is resource intensive. Generative AI (GenAI) can potentially accelerate the study of such issues, though its practical application remains underexplored. This research employs a mixed-methods approach to examine GenAI's role in system mapping, identifying three dimensions: the potentials of GenAI in system mapping, its challenges and limitations, and the benefits of managing complexity through Human AI Collaboration. These findings provide a foundation for further exploration and practical applications in addressing complex problems.pt_PT
dc.identifier.tid203927222pt_PT
dc.identifier.urihttp://hdl.handle.net/10362/181710
dc.language.isoengpt_PT
dc.relationUID/ECO/00124/2013pt_PT
dc.subjectGenerative AIpt_PT
dc.subjectSystems thinkingpt_PT
dc.subjectSystem mappingpt_PT
dc.subjectParticipatory modellingpt_PT
dc.titleExploring the potential of Artificial Intelligence in system mappingpt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameA Work Project, presented as part of the requirements for the Award of a Master’s degree in Impact Entrepreneurship and Innovation from the Nova School of Business and Economicspt_PT

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NSBE - MA Dissertations