Copyright Law Stifles Competition and Innovation
We’re taking part in Copyright Week, a series of actions and discussions supporting key principles that should guide copyright policy. Every day this week, various groups are taking on different elements of copyright law and policy, and addressing what’s at stake, and what we need to do to make sure that copyright promotes creativity and innovation.
Copyright owners increasingly claim more draconian copyright law and policy will fight back against big tech companies. In reality, copyright gives the most powerful companies even more control over creators and competitors. Today’s copyright policy concentrates power among a handful of corporate gatekeepers—at everyone else’s expense. We need a system that supports grassroots innovation and emerging creators by lowering barriers to entry—ultimately offering all of us a wider variety of choices.
Pro-monopoly regulation thru copyright won’t provide any meaningful economic support for vulnerable artists and creators. Because of the imbalance in bargaining power between creators and publishing gatekeepers, trying to help creators by giving them new rights under copyright law is like trying to help a bullied kid by giving them more lunch money for the bully to take.
Entertainment companies’ ancient practices bear out this concern. for example, in the late-2000’s to mid-2010’s, music publishers and recording companies struck multimillion-dollar direct licensing deals with music streaming companies and video sharing platforms. Google reportedly paid more than $400 million to a single music label, and Spotify gave the major record labels a combined 18 percent ownership interest in its now $100 billion company. Yet music labels and publishers frequently fail to share these payments with artists, and artists rarely benefit from these equity arrangements. There’s no reason to think that these same companies would treat their artists more fairly now.
AI Training
In the AI era, copyright may seem like a good way to prevent big tech from profiting from AI at individual creators’ expense—it’s not. Actually, the opposite is true. Developing a large language model requires developers to train the model on millions of works. Requiring developers to license enough AI training data to build a large language model would