Deepfake detection technologies

Business strategies for deepfake detection companies, within the Netherlands, to maintain or gain a competitive advantage

Master Thesis (2024)
Author(s)

W.C.J. Peeters (TU Delft - Technology, Policy and Management)

Contributor(s)

Johannes Gartner – Mentor (TU Delft - Delft Centre for Entrepreneurship)

J.A. Anne Annema – Graduation committee member (TU Delft - Transport and Logistics)

Faculty
Technology, Policy and Management
Copyright
© 2024 Willemijn Peeters
More Info
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Publication Year
2024
Language
English
Copyright
© 2024 Willemijn Peeters
Graduation Date
02-04-2024
Awarding Institution
Delft University of Technology
Programme
['Management of Technology (MoT)']
Faculty
Technology, Policy and Management
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Abstract

In today’s climate of the increasing use of fake news for which deepfakes may be used, and their widespread distribution through social media, the challenge of distinguishing reality from manipulation is growing. The development of deepfake detection technologies (DFDTs) is therefore crucial. The number of deepfake detection companies (DFDCs) is growing rapidly, changing the competitive landscape. Literature review shows that little is known about strategic opportunities for DFDCs. Therefore, the aim of this research is to provide business strategies, for DFDCs in the emerging DFDT market, in order to maintain or gain a competitive advantage. The knowledge gap lies in the fact that research is done into business strategies for emerging technologies, however, not specifically for DFDTs. To generate concrete and valuable results, the focus is on the Netherlands...

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