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."
