Showing posts with label text and data mining (TDM). Show all posts
Showing posts with label text and data mining (TDM). Show all posts

Thursday, February 20, 2025

AI and Copyright: Expanding Copyright Hurts Everyone—Here’s What to Do Instead; Electronic Frontier Foundation (EFF), February 19, 2025

TORI NOBLE, Electronic Frontier Foundation (EFF); AI and Copyright: Expanding Copyright Hurts Everyone—Here’s What to Do Instead


[Kip Currier: No, not everyone. Not requiring Big Tech to figure out a way to fairly license or get permission to use the copyrighted works of creators unjustly advantages these deep pocketed corporations. It also inequitably disadvantages the economic and creative interests of the human beings who labor to create copyrightable content -- authors, songwriters, visual artists, and many others.

The tell is that many of these same Big Tech companies are only too willing to file copyright infringement lawsuits against anyone whom they allege is infringing their AI content to create competing products and services.]


[Excerpt]


"Threats to Socially Valuable Research and Innovation 

Requiring researchers to license fair uses of AI training data could make socially valuable research based on machine learning (ML) and even text and data mining (TDM) prohibitively complicated and expensive, if not impossible. Researchers have relied on fair use to conduct TDM research for a decade, leading to important advancements in myriad fields. However, licensing the vast quantity of works that high-quality TDM research requires is frequently cost-prohibitive and practically infeasible.  

Fair use protects ML and TDM research for good reason. Without fair use, copyright would hinder important scientific advancements that benefit all of us. Empirical studies back this up: research using TDM methodologies are more common in countries that protect TDM research from copyright control; in countries that don’t, copyright restrictions stymie beneficial research. It’s easy to see why: it would be impossible to identify and negotiate with millions of different copyright owners to analyze, say, text from the internet."

Tuesday, June 5, 2018

Data mining: why the EU’s proposed copyright measures get it wrong; The Conversation, May 24, 2018


Professor of Intellectual Property Law, University of Glasgow and
Senior Lecturer in Intellectual Property and Internet Law, University of Glasgow,
The Conversation;  
Data mining: why the EU’s proposed copyright measures get it wrong

"Data that is mined with the help of machine learning techniques has been a rapid area of technological advancement – with good and bad consequences for everyone. And EU copyright law is currently caught in the crossfire.

Cambridge Analytica and Facebook’s recent data scandal, which involved the profiling of users from their online behaviour facilitated by social networks, brought important issues to the surface about web privacy, only after it was reported that millions of people had their data harvested and improperly shared with a political consultancy.

But the same data mining technique also offers great societal benefit in fields such as traffic prediction, natural language processing and the identification of potential cures for diseases.

Many people think that regulating the use of data is a matter of data protection or privacy laws. However, where the raw material subjected to analysis is not “personal data” but material protected under copyright law, such as texts or certain structured databases, another set of legal norms come into play. This has far reaching and little understood consequences."