CURATING AI-GENERATED ARTWORKS CHALLENGES AND SOLUTIONS

Smitha S P; Sunita Samanta; Shikha Gupta; Manish Nagpal; Prakriti Kapoor; Ruchika

doi:10.29121/shodhkosh.v6.i1s.2025.6679

Authors

Ms. Smitha S P Assistant Professor,Computer Science and Engineering, Presidency University, Bangalore, Karnataka, India
Dr. Sunita Samanta Assistant Professor, Department of Electronics and Communication Engineering, Institute of Technical Education and Research, Siksha 'O' Anusandhan, Deemed to be University, Bhubaneswar, Odisha, India
Shikha Gupta Assistant Professor, School of Business Management, Noida international University 203201, India
Manish Nagpal Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, Solan, 174103, India
Prakriti Kapoor Centre of Research Impact and Outcome, Chitkara University, Rajpura- 140417, Punjab, India
Ruchika Assistant Professor, Department of Computer Science & Engineering(AI), Noida Institute of Engineering and Technology, Greater Noida, Uttar Pradesh, India

DOI:

https://doi.org/10.29121/shodhkosh.v6.i1s.2025.6679

Keywords:

AI Art Curation, Generative Models, Authorship and Ethics, Algorithmic Transparency, Human–AI Collaboration, Digital Aesthetics

Abstract [English]

The fast growth of artificial intelligence (AI) in the creative field has changed the way curators do their jobs and brought up difficult psychological, moral, and technical issues. Artworks created by algorithms, neural networks and generative models that are created by AI challenge traditional concepts of creation, ownership and aesthetic judgement. This essay examines how the roles of managers are evolving as they work to link the actions of humanity with those of machines. It considers the key issues raised when attempting to organize AI art: challenges related to challenges of authenticity, originality, ambiguous ownership and copyright, and the technology's black box decision-making process. It's harder for curators job due to ethical problems with data-bias and figuring out who wrote a piece. On a functional level, it's difficult for managers to make sense of and to put their stake in works that it's difficult to understand the creative processes of systems that are not always clear. The paper talks about new ways for humans and AI to work together in curating, ways to judge the intellectual and stylistic value of something, and ways to include algorithmic openness in the design of a show. It displays the best practices and new ways of curating digital art through examples of big AI art shows and attempts by institutions to set moral standards.

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