From Human Input To AI Output: Determining Authorship And Copyright Rights
- IJLLR Journal
- 2 days ago
- 2 min read
Kashish Upadhyay, Amity Law School, Noida
ABSTRACT
The advent of Artificial Intelligence (AI), and generative AI systems, which can generate text, images, music, software code, and other expressions of creative work, has radically changed the conventional conception of creativity and authorship. Even though traditional instruments simply support the activities of human creators, novel AI systems work using sophisticated machine learning models that process large amounts of data and produce results that can even be considered similar to the works of human creators. This technological revolution is of great challenge to the prevailing modes of copyright that were historically based on the fact that it is human intellect and conscious decision that has been the source of the so- called creativity. This article is a critical analysis of the law of the AI- generated works and especially how to establish authorship and ownership of copyright rights.
It discusses the principles of the copyright law such as originality, fixation, and the idea of the author, and evaluates the application (or non-application) of these principles to AI-generated material. The study question explored is the possibility of AI systems being identified as an author, whether copyright law ought to belong to the human user, the developer or the entity using the AI system, or whether these works should be considered a part of the public domain.
It suggests legislative clarification that should determine the extent of human input in protection and discusses the likelihood of other models of protection or sui generis models of protection. In the end, the article suggests a middle ground that ensures the anthropocentricity of the copyright law and its adjustment to the presence of the quickly developing artificial intelligence technologies.
Keywords: Artificial Intelligence, Copyright, Authorship, Originality, Indian Copyright Act 1957, Training Data, Sui Generis Rights
