Book contents
- The Cambridge Handbook of Private Law and Artificial Intelligence
- Reviews
- The Cambridge Handbook of Private Law and Artificial Intelligence
- Copyright page
- Dedication
- Contents
- Figures
- Table
- Contributors
- Acknowledgements
- Abbreviations
- Introduction
- 1 AI for Lawyers
- 2 Computable Law and AI
- Part I Law of Obligations
- Part II Property
- 14 Property/Personhood and AI
- 15 Data and AI
- 16 Intellectual Property Law and AI
- 17 Information Intermediaries and AI
- Part III Corporate and Commercial Law
- Part IV Comparative Perspectives
- Index
15 - Data and AI
The Data Producer’s Right – An Instructive Obituary
from Part II - Property
Published online by Cambridge University Press: 21 March 2024
- The Cambridge Handbook of Private Law and Artificial Intelligence
- Reviews
- The Cambridge Handbook of Private Law and Artificial Intelligence
- Copyright page
- Dedication
- Contents
- Figures
- Table
- Contributors
- Acknowledgements
- Abbreviations
- Introduction
- 1 AI for Lawyers
- 2 Computable Law and AI
- Part I Law of Obligations
- Part II Property
- 14 Property/Personhood and AI
- 15 Data and AI
- 16 Intellectual Property Law and AI
- 17 Information Intermediaries and AI
- Part III Corporate and Commercial Law
- Part IV Comparative Perspectives
- Index
Summary
Data is one of the most valuable resources in the twenty-first century. Property rights are a tried-and-tested legal response to regulating valuable assets. With non-personal, machine-generated data within an EU context, mainstream IP options are not available, although certain types of machine generated data may be protected as trade secrets or within sui generis database protection. However, a new IP right is not needed. The formerly proposed EU data producer’s right is a cautionary tale for jurisdictions considering a similar model. A new property right would both strengthen the position of de facto data holders and drive up costs. However, with data, there are valuable lessons to be learned from constructed commons models.
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- Information
- Publisher: Cambridge University PressPrint publication year: 2024