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.

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