SMART CONTRACTS FOR AI-GENERATED ART RIGHTS - C Komalavalli; Bhati, Rinki; Khan, Akhilesh Kumar; Tripathi, Arun Kumar; Arora, Arpit; Ahluwalia, Gunveen; Diwate, Kajal Sanjay (ShodhKosh: Journal of Visual and Performing Arts, 2025)
The swift AI-generated art development has further fueled the discussion on both authorship and ownership, as well as on whether digital rights can be enforced. The existing intellectual property paradigms lack the ability to recognise works produced by autonomous systems fully or in part, which presents proxies in the maintenance of copyright, derivatives and cross-jurisdictional identification of AI-related rights. With more and more creative outputs based on algorithmic processes, there is an urgent requirement to have transparent, tamper-resistant processes that would be able to define, assign and protect right at scale. One of the promising infrastructures to facilitate legal and economic aspects of AI-generated art is the use of smart contracts, which are the self-executable agreements that run on blockchain networks. This paper discusses how authorship claims can be encoded in smart contracts, how royalty payments can be automated, and how programmable access controls can be offered, at the same time, offering verifiable provenance by tokenizing the provenance. We analyze technical specifications of creating powerful metadata standards to cover creation parameters, level of contributions, and model lineage. Moreover, we discuss interoperability issues in the heterogeneous blockchains and digital marketplaces, which are limited to the immutability, upgradability, and long-term security. In addition to the technical design, the paper evaluates the ethical impact, such as the fairness to human designers, responsible design of AI innovators, and risks to society in general of bias, exploitation, and its unequal distribution of rights-management systems.