Description of Crowdsourcing and AI-Based Tool for Knowledge Management and Systems Change in Public Services

Sanna Ulmanen, Mari Hirvonen (), Peter Tattersall (), Tiina Ristikari (), Vincent Kuo (), Pertti Virta (), Tanja Jurvonen () and Mika Niemelä ()
Additional contact information
Sanna Ulmanen: Faculty of Education and Culture, Tampere University, Ã…kerlundinkatu 5, Tampere 33014, Finland
Mari Hirvonen: ��Itla Children’s Foundation, Siltasaarenkatu 8-10, Helsinki 00530, Finland
Peter Tattersall: ��Hahmota Oy, Fiskars, 10470, Finland
Tiina Ristikari: ��Itla Children’s Foundation, Siltasaarenkatu 8-10, Helsinki 00530, Finland
Vincent Kuo: �Department of Civil Engineering, Aalto University, Otaniemi, Espoo, Finland
Pertti Virta: �Northern Competence and Support Center, Kirjaamo PL 10 90029 POHDE, Finland
Tanja Jurvonen: ��City of Tampere, Frenckellinaukio 2 B, PL 487, 33101 Tampere, Finland
Mika Niemelä: *Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland

International Journal of Innovation and Technology Management (IJITM), 2024, vol. 21, issue 04, 1-29

Abstract: This study presents a crowdsourcing IT platform and working model intended to support knowledge management processes and systems change to help public service organizations fulfill their purpose and perform their tasks in a rapidly changing environment. The tool brings together tacit and explicit knowledge regarding organizational processes in one database and provides an AI-assisted platform for knowledge processing. Additionally, it allows for disseminating refined data to grassroots-level actors, enables the implementation of initiatives, and monitors their effectiveness. By utilizing crowdsourcing, the tool leverages the collective intelligence of actors across organizational boundaries, thereby promoting collective, knowledge-based learning and organizational self-renewal.

Keywords: Knowledge management tool; systems change; crowdsourcing; artificial intelligence; collective impact; public service organization (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219877024500275

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