In English

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

Johan Lennartson
Göteborg : Chalmers tekniska högskola, 2018. 90 s. Master thesis. E - Department of Technology Management and Economics, Chalmers University of Technology, Göteborg, Sweden, 2018.
[Examensarbete på avancerad nivå]

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.

Nyckelord: FINT-model, Artificial Intelligence, Digitalization Strategy, Innovation Management, Leverage AI, Public Sector AI, Public Sector Digitalization

Publikationen registrerades 2019-01-21. Den ändrades senast 2019-01-21

CPL ID: 256461

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