Intellectual property protection in the age of self-learning systems: Appropriability issues in artificial intelligence

Item Type Conference or Workshop Item (Paper)
Abstract

This study examines how firms in the autonomous driving industry that pursue artificial intelligence-based innovations attempt to appropriate returns from these innovations. It intends to contribute to the literature on value appropriation from innovation by investigating the extent to which firms can and do keep the key components of AI systems (data set, training approach, and model) private versus publishing them. Using a qualitative research design, we establish that there are regulatory, technical, and enforcement aspects to the components that prompt firms to either protect or publish.

Authors Häfner, Naomi; Gassmann, Oliver & Borth, Damian
Language English
Subjects business studies
HSG Classification contribution to scientific community
HSG Profile Area SoM - Business Innovation
Date 27 March 2020
Publisher SMS Strategic Management Society
Place of Publication Chicago, IL
Number of Pages 7
Title of Book The Institutional and Regulatory Levers of Innovation and Venture Formation
Event Title Strategic Management Society Special Conference
Event Location Berkeley, CA
Event Dates March 25-27, 2020
Official URL https://www.strategicmanagement.net/berkeley/overv...
Depositing User Prof. Dr. Naomi Häfner
Date Deposited 09 Oct 2020 09:57
Last Modified 09 Oct 2020 09:57
URI: https://www.alexandria.unisg.ch/publications/261181

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Citation

Häfner, Naomi; Gassmann, Oliver & Borth, Damian: Intellectual property protection in the age of self-learning systems: Appropriability issues in artificial intelligence. 2020. - Strategic Management Society Special Conference. - Berkeley, CA.

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https://www.alexandria.unisg.ch/id/eprint/261181
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