Copyright + Technology Conference 2023

Join us at Connolly's Times Square!

There are various techniques for training machine learning systems that use preexisting works in different ways and therefore have different implications for copyright. Assessing the potential liability of those techniques requires understanding of how these techniques work. For example, the techniques used to train large language models (such as ChatGPT) are materially different than those for diffusion or image classification models, and they can change again at the fine-tuning level. Throughout these different processes, notions of reproduction, distribution, and display may or may not be implicated, and indeed traditional notions of what these terms mean may be subject to strain and challenge in the world of AI. In this session, we’ll explain how content becomes data for AI purposes and identify where potential reproduction, distribution, and display of content may occur.

The Copyright Office notes that it “will not register works produced by a machine or mere mechanical process that operates randomly or automatically without any creative input or intervention from a human author.” This has led to the Office issuing several high profile registrations rejections for works created in whole or in part using artificial intelligence tools. To determine whether, and to what extent, a human author is involved in the creation of works made with generative AI tools, it is important to understand just what we mean by the term “author.” Our panelists will discuss what it means to be an “author,” whether that “author” must be a human being, and the various doctrines adopted by courts throughout the years in trying to identify and define an author. The panelists will compare the U.S. approach to AI-generated work authorship with those of jurisdictions such as the UK that recognize ownership rights.

The amount of content submitted to commercial services that is generated by AI is poised to explode. Determining which works come from humans and which come from AI–and to what degree–will become more and more important as the volume grows. In this session, we look at efforts to identify AI-generated works proactively as well as emerging technologies for telling the difference after the fact. Are there solutions that will work well enough for rights administration purposes? Our panelists will discuss.

This past March, a district court in New York awarded summary judgment to a group of book publishers in their litigation against the Internet Archive over certain forms of digital book lending. The ruling could have profound implications for libraries as they work to make content available that they preserve in digital form or that is “born digital” on acquisition. On this panel we’ll discuss potential ways forward for libraries if the ruling is let stand on appeal: is controlled digital lending (CDL) dead, or are there ways to achieve its aims that avoid what is now considered liability? Or is licensing going to be the way to fulfill libraries’ missions in the digital age?