Intellectual property issues in artificial intelligence trained on scraped data

Oecd

No 33, OECD Artificial Intelligence Papers from OECD Publishing

Abstract: Recent technological advances in artificial intelligence (AI), especially the rise of generative AI, have raised questions regarding the intellectual property (IP) landscape. As the demand for AI training data surges, certain data collection methods give rise to concerns about the protection of IP and other rights. This report provides an overview of key issues at the intersection of AI and some IP rights. It aims to facilitate a greater understanding of data scraping — a primary method for obtaining AI training data needed to develop many large language models. It analyses data scraping techniques, identifies key stakeholders, and worldwide legal and regulatory responses. Finally, it offers preliminary considerations and potential policy approaches to help guide policymakers in navigating these issues, ensuring that AI’s innovative potential is unleashed while protecting IP and other rights.

Keywords: AI; artificial intelligence; data scraping; intellectual property; IP (search for similar items in EconPapers)
Date: 2025-02-09
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oec:comaaa:33-en

Access Statistics for this paper

More papers in OECD Artificial Intelligence Papers from OECD Publishing
Bibliographic data for series maintained by ().