Demystifying Artificial Intelligence -Exploring how public sector organizations can approach Artificial Intelligence

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/256461
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Type: Examensarbete för masterexamen
Master Thesis
Title: Demystifying Artificial Intelligence -Exploring how public sector organizations can approach Artificial Intelligence
Authors: Lennartson, Johan
Abstract: Artificial Intelligence has enjoyed a resurgence in recent years. After decades of lofty promises followed by an inability to realize them, the technology is now having a great and growing impact on our society. However, despite its apparent importance, only a fraction of Sweden’s public entities have a structured approach to Artificial Intelligence. Previous research has not explored the intersection between Innovation Management and Artificial Intelligence. Therefore, this study attempts to help public organizations approach Artificial Intelligence strategically. To investigate the issue, interviews were conducted with ten individuals possessing strong insight into the subject. The empirical findings reveal several recurring factors impeding the strategic utilization of Artificial Intelligence in Sweden’s public sector. These factors include an insufficient understanding of how Artificial Intelligence can be utilized, insufficient degree of overall digitalization, and a severe lack of guidelines regarding legal and ethical dilemmas, among others. The FINT-model is ultimately proposed as a suggestion for how public organizations should approach Artificial Intelligence. The model consists of four elements: Digital Foundation, Identification of Needs, Technology, and Innovation. Implementing the suggested model may enable public organizations to create a structured approach to Artificial Intelligence, leveraging the technology to fulfill the needs of their citizens.
Keywords: Innovation och entreprenörskap (nyttiggörande);Övrig annan teknik;Innovation & Entrepreneurship;Other Engineering and Technologies not elsewhere specified
Issue Date: 2018
Publisher: Chalmers tekniska högskola / Institutionen för teknikens ekonomi och organisation
Chalmers University of Technology / Department of Technology Management and Economics
Series/Report no.: Master thesis. E - Department of Technology Management and Economics, Chalmers University of Technology, Göteborg, Sweden
URI: https://hdl.handle.net/20.500.12380/256461
Collection:Examensarbeten för masterexamen // Master Theses



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