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Intellectual property protection in the age of self-learning systems: Appropriability issues in artificial intelligence
Type
conference paper
Date Issued
2020-03-27
Author(s)
Research Team
AIML Lab
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.
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
SoM - Business Innovation
Book title
The Institutional and Regulatory Levers of Innovation and Venture Formation
Publisher
SMS Strategic Management Society
Publisher place
Chicago, IL
Pages
7
Event Title
Strategic Management Society Special Conference
Event Location
Berkeley, CA
Event Date
March 25-27, 2020
Subject(s)
Division(s)
Eprints ID
261181