'Do Androids Dream of Electric Copyright? Comparative Analysis of Originality in Artificial Intelligence Generated Works' by Andrés Guadamuz in (2017) 2 Intellectual Property Quarterly and updated in 2020 comments
The advent of sophisticated artificial neural networks has opened new artistic opportunities, but also a variety of new legal challenges. Computer programs such as Google's Deep Dream can take an image and process it in manners that resemble biological networks, producing artwork that is both unique and unpredictable.
The law is not unfamiliar with the challenges of artificial intelligence, in the past academics and policymakers have had to deal with the legal implications of autonomous agents in contract formation, just to name one are of interest. However, for the most part the implementation of smart systems has been limited in their reach and scope, and in many instances autonomous agents required quite a lot of direction from the programmer, following a very stringent set of rules. This meant that for the most part all rights, responsibilities and liabilities arising from artificial agents fell squarely on the program creator. Neural networks are different, these systems have the potential to generate works in which human interaction is minimal.
Modern copyright law has been drafted to consider originality as an embodiment of the author’s personality, and originality is one of the main requirements for the subsistence of copyright. So, what happens when you remove personality from the equation? Are machine-created works devoid of copyright? Do we need to change copyright law to accommodate autonomous artists?
'A Scanner Darkly: Copyright Liability and Exceptions in Artificial Intelligence Inputs and Outputs' by Guadamuz in 2023 comments
The question of artificial intelligence and copyright has begun to gain considerable momentum over the last few years. One area of study focuses on the authorship of computer-generated works, but arguably, a more intriguing inquiry centers around infringement. To paint, compose music, or write, AI must be taught. The process by which artificial intelligence "learns" to perform these tasks, particularly to generate works that emulate human creativity, often relies on accessing and analysing a large number of existing works to discern patterns and create its own versions. To accomplish this, the computer program needs copies of these works for analysis and subsequent generation of new outputs.
Thus, two significant copyright questions emerge: one concerning the inputs and another the outputs. From the inputs perspective, does the act of accessing, reading, analysing, and mining data constitute copyright infringement? If so, are there any applicable defences? From the outputs perspective, could the copyright owner of one of the works used to train the computer sue the program's creator for copyright infringement due to the resulting derivative works? This article delves into both questions.
