Reading list: copyright and AI

Jane C. Ginsburg and Luke Ali Budiardjo, Authors and Machines:

Machines, by providing the means of mass production of works of authorship, engendered copyright law. Throughout history, the emergence of new technologies tested the concept of authorship, and courts in response endeavored to clarify copyright’s foundational principles. Today, developments in computer science have created a new form of machine — the “artificially intelligent” system apparently endowed with “computational creativity” — that introduces challenging variations on the perennial question of what makes one an “author” in copyright law: Is the creator of a generative program automatically the author of the works her process begets, even if she cannot anticipate the contents of those works? Does the user of the program become the (or an) author of an output whose content the user has at least in part defined? This article frames these and similar questionsthat generative machines provoke as an opportunity to revisit the concept of copyright authorship in general and to illuminate its murkier corners. This article examines several fundamental relationships (between author and amanuensis, between author and tool, and between author and co-author) as well as several authorship anomalies (including the problem of “accidental” or “indeterminate” authorship) to unearth the basic principles and latent ambiguities which have nourished debates over the meaning of the “author” in copyright. We present an overarching and internally consistent model of authorship based on two basic pillars: a mental step (the conception of a work) and a physical step (the execution of a work), and define the contours of these basic pillars to arrive at a cohesive definition of authorship. We then apply the conception-and-execution theory of authorship to reach a series of conclusions about the question of machine “authorship.” We contend that even the most technologically advanced machines of our era are little more than faithful agents of the humans who design or use them. Asking whether a computer can be an author therefore is the “wrong” question; the “right” question addresses how to evaluate the authorial claims of the humans involved in either preparing or using the machines that “create.” We argue that in many cases, either the upstream human being who programs and trains a machine to produce an output, or the downstream human being who requests the output, is sufficiently involved in the conception and execution of the resulting work to claim authorship. But in some instances, the contributions of the human designer and user will be too attenuated from the work’s creation for either to qualify as “authors” — leaving the work “authorless.”

As usual, Ginsburg (and her coauthor) do a wonderful, careful job on the doctrinal implications, with bonus Le Petit Prince examples.  I would probably draw the line finding works to be authorless earlier than they would. In particular, I don’t think that the essentially unpredictable and unpredicted outputs of generative computer programs would be authored by the programmer; they should be deemed authorless as well. Betsy Rosenblatt’s project on “work” as a verb and not just a noun was helpful to my thinking here.