ShodhKosh: Journal of Visual and Performing Arts

SPECIAL ISSUE ON REIMAGINING VISUAL ARTS, MEDIA, AND CULTURAL PEDAGOGY IN THE AGE OF ARTIFICIAL INTELLIGENCE

2025-12-12T09:42:57+00:00

Dear Readers and Contributors,

It gives me immense pleasure to present this special issue of ShodhKosh: Journal of Visual and Performing Arts (E-ISSN 2582-7472), titled Reimagining Visual Arts, Media, and Cultural Pedagogy in the Age of Artificial Intelligence. As artificial intelligence reshapes contemporary creative practices, this special edition invites educators, researchers, practitioners, and cultural leaders to critically examine how AI is redefining artistic production, educational methodologies, heritage preservation, and institutional management across the visual and performing arts.

In recent years, AI has evolved from a technological tool into a profound cultural and pedagogical mediator. The selected papers in this issue reflect this transition with remarkable depth and interdisciplinary insight. They explore a wide range of themes—from AI-driven digital storytelling, generative art, and neural aesthetics to folk art preservation, digital twins in sculpture education, diffusion-model photography, and AI-enabled museum interactivity. Several contributions address pressing ethical and managerial concerns, including the governance of AI-generated artworks, deepfake risks, and the institutional challenges of integrating AI into academic and cultural ecosystems.

A recurring emphasis across the submissions is the need to balance innovation with responsibility. Many authors foreground the pedagogical implications of AI: its potential to enrich learning environments, transform assessment methods, support creative talent identification, and expand access to cultural knowledge. Equally compelling are the studies that highlight AI’s role in sustainable art production, cloud-based creative management, virtual performances, interactive installations, and data-informed decision-making in media and art institutions.

Submissions opened on 10 January 2025 and closed on 25 March 2025, attracting a substantial number of manuscripts from scholars and practitioners representing diverse domains—visual arts, performing arts, digital media, heritage studies, folk culture, sound design, design technology, and creative management. Each accepted paper underwent rigorous peer review to ensure the highest academic and ethical standards, resulting in a curated selection that reflects both the promise and complexity of AI in contemporary artistic practice.

I extend my heartfelt gratitude to the contributors for their scholarly rigor, to our reviewers for their thoughtful evaluations, and to Granthaalayah Publications for their continued support in strengthening research dissemination in the arts and humanities. The breadth and quality of work featured in this issue affirm our collective commitment to understanding AI not merely as a technological force but as a transformative agent influencing culture, creativity, and education.

As you explore the articles in this special issue, I hope they inspire critical reflection, informed dialogue, and new directions for research and practice. May this volume contribute meaningfully to the evolving discourse on how artificial intelligence is shaping the future of art, media, and cultural pedagogy.

Issue Editor:

Dr. Kumkum Bharadwaj
Professor (HOD) in Fine Arts, Maharani Laxmibai Girls P.G. College, Indore, India
Email: drkumkum.bharadwaj@mp.gov.in

Dr. C. Govindaraj
Professor and Head, Department of English, Periyar University Centre for PG & Research Studies, India
Email: drgovindpupgec@periyaruniversity.ac.in

Dr. R. Devarajulu Reddy
Professor of English, Department of Humanities and Basic Science, Sri Venkatesa Perumal College of Engineering and Technology, RVS Nagar, KN Road, Puttur, Tirupati District, Andhra Pradesh, India
Email: drreddyvari@gmail.com

Dr. A. Wati Walling
Associate Professor in Sociology and Dean (Academic), NIT , Dimapur, Nagaland, India
Email: watiwalling@nitnagaland.ac.in

Dr. A. Noble Jebakumar
Assistant Professor and Head, Department of English, Government Arts and Science College, Manapparai, India
Email: drnoblejk@gmail.com

MANAGEMENT ETHICS IN THE AI-ART ECOSYSTEM

2025-12-13T10:24:58+00:00

The creativity, ownership and ethics of the art ecosystem has been re-defined in a manner that has never before been witnessed due to the fast changing nature of the artificial intelligence (AI) inside the art ecosystem. The problem that the ethics of management in this new domain deals with is the balancing of innovation and moral responsibility, to achieve transparency, fairness, and respect of the human beings and creative integrity. Ethical management should encompass the issue of authorship, intellectual property and accountability in instances whereby the art pieces generated by the AI system are raising issues of originality. The AI application in art production or curation by organizations is met with the issues of algorithmic bias, cultural appropriation, and relegation of human artists. Effective management operations should be inclusiveness, approval and equitable allocation of credit to contributors of human and machine resources. Additionally, ethical leadership should be attentive to data integrity as well as not to reproduce copyrighted material without permission. Transparency in the use of AI tools and the creative process is the key to the assurance of trust and integrity of the people to the art. Making its way through the socio-economic consequences, including the labor migration, and the commercialization of AI art, the management also should. By establishing robust ethical norms and building accountability, managers would have an opportunity to develop a sustainable, human-based innovation that would appreciate technological growth and artistic heritage within the dynamic AI-art ecosystem.

CURATING AI-GENERATED ARTWORKS CHALLENGES AND SOLUTIONS

2025-12-13T10:24:59+00:00

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.

THE FUTURE OF AI-INTEGRATED ART EDUCATION

2025-12-13T10:25:00+00:00

With artificial intelligence (AI) and the art education together alters how individuals are taught to be creative and express themselves using art. The application of AI technologies in art classes changes how students create, interpret, and discuss art due to the development of smarter technologies. The history of AI-integrated art education is considered in this paper, starting with the introduction of the first digital tools and ending with the development of intelligent creative systems. This is demonstrating that AI is emerging as a more of a creative partner and it is assisting students and artists to experiment with new styles, methods and approaches across other areas. The paper examines the ways machine learning algorithms can support the appearance of new ideas and push the boundaries of the artistic practice based on examples of artworks supported by AI. In the classes where AI is introduced into the classroom, training techniques should be reconsidered during art classes. Teachers are replacing the traditional skills based lessons with concept based lessons that are more centered on interpretation, imagination, and social responsibility. Elements like generative design, adaptable learning environments and creative coding software are reimagining the way AI-founded platforms work to enable learning through giving a student-optimized, data-driven input. Nevertheless, AI usage is not without its issues, including accessibility issues, digital equality, writing ethics and freedom of art. The future of art education will be AI, whereby the systems will be adaptable to all people and at the same time balanced with human senses and computer intelligence. The paper projects a vision of AI-powered learning environments in which AI is perceived as a tutor to students and a colleague, which addresses the necessity of students to understand the interrelatedness of art, technology, and society.

MANAGING ART RESIDENCIES USING AI PLATFORMS

2025-12-04T18:29:56+00:00

The adding of Artificial Intelligence (AI) into the administration of art residencies is altering how institutions are producing, staging and promoting creative practice. Below we explain the hybrid field at the crossroad of AI technology and arts administration, and how intelligent systems can be applied to achieve more intelligent decision-making, more efficient resources allocation, and improved artist-institution relations. Despite the recent rise in the trend of digital transformation in the arts, minimal focus has been given to residency programs - locations that require efficiency in their logistics as well as sensitivity in their curation. The practical applications of AI in residency management discussed in this paper include the choice of artists based on the algorithmic approach, auto-scheduling and forecasting tools. Through case analysis of real-life case studies of organizations that apply AI-based platforms, the study demonstrates measurable outcomes of administrative efficiency and inclusiveness. The relative analysis of the AI-assisted and conventional strategies of management indicates that automation can reduce significant expenditures of the operations and, simultaneously, enables transparency in the selection and evaluation procedures based on data. Nevertheless, certain significant ethical and socio-cultural issues are also mentioned in the study.

HYBRID INTELLIGENCE IN ART STUDIO MANAGEMENT

2025-12-13T10:25:01+00:00

The art studios also have a turn in their management to a new transformative change which is the emergence of Hybrid Intelligence (HI) a combination of human creative power and the power of artificial intelligence. This paper discusses how HI frameworks may change creative processes, decision-making, and efficiency of functioning in studios of modern art. Exploring the relationship between cognitive reinforcement and computer automation, the research contributes to the fact that AI systems do not replace human artistic instinct and administration ability but complement it. The literature review is after the elaboration of human creativity in the sphere of management, the application of AI to the creative spheres, and the models of human-AI interaction. It is discussed on the basis of the theoretical framework Hybrid Intelligence theory, where its attention is paid to the shared cognition, adaptive learning, and co-creation. Empirical implementation of case studies has been successful in illustrating how hybrid systems can streamline the decision-making process as well as optimize the workflow, and maximize opportunities to be creative. The results of the research point to the fact that the art studios in which HI models are applied are linked to higher outputs, more innovative models, and more evidence-based management practices with no decline in the artistic authenticity. Additionally, the problems of ethical application, education, and policy change are discussed in the paper as the obstacles that are required to the effective integration. The new AI tools such as generative design, predictive analytics or emotion systems will further infiltrate artistic and managerial practices in the future.

PREDICTIVE ANALYTICS FOR ARTIST CAREER DEVELOPMENT

2025-12-13T11:09:43+00:00

The use of data analytics and artificial intelligence in tandem has led to changes in the talent management processes in the entertainment industry. By looking at measured signs of success, predictive analytics provides us with a data-driven method of understanding and predicting how an artist's work will go. This research suggests a complete way to guess how an artist's career will develop using many different types of data, such as action on social media, live numbers, patterns of cooperation and how involved the audience is. The study is based on entertainment data models that already exist and expands them by using advanced machine learning techniques. The method comprises gathering information in a pre-planned manner from a large number of people who practice their religion on public and digital platforms, including the number of followers, engagement metrics, streaming statistics, and genre preferences. These characteristics are inputted into prediction models such as regression analysis, decision trees, and ensemble learning algorithms. These models attempt to identify the factors that are most influential on an artist's development. Strong preparation, feature engineering and cross-validation methods are emphasised in the suggested framework to make sure model stability and reduce overfitting. A case study is carried out on a few artists of different styles to evaluate the applicability of the model to real life. Revisiting historical data provides us with a way to determine how well we are doing at predicting, and it also gives us insights into the management of artists and planning for the future.

NLP MODELS FOR ARTISTIC STATEMENT GENERATION

2025-12-13T11:09:45+00:00

In this paper we propose a multimodal vision-language multimodality detransformer framework for coherent, expressive, and visually grounded artistic statement generation, which takes advantage of multimodal vision- and language modeling on top of a strong transformer-based text generation network. The proposed system is comprised of a visual encoder to interpret compositional and stylistic aspects of an artwork, a fine-tuned transformer decoder that acts as a conceptually rich story engine and a cross-modal fusion module to ensure the alignment between visual clues and linguistic output. Combined with creative and grounding-based reward mechanisms from reinforcement learning, the interpretive depth and style-grounding are further advanced. Using automated similarity measures, multimodality alignment scores and human expert subjectivity measurement, it is shown that the hybrid model greatly improves over traditional captioning and text-only methods at extracting artistry, emotionality and conceptuality. While the method has great potential, challenges exist in dealing with cultural bias, data limitations, interpretive subjectivity and computational demands. Overall, the research brings forward the field of AI-assisted artistic communication and provides a scalable solution to help artists, curators, educators, and digital art platforms to create quality artistic statements.

GENERATIVE DESIGN FOR CONCEPTUAL INSTALLATIONS

2025-12-06T12:05:21+00:00

Generative design is a huge shift in the manner of thinking out conceptual works by integrating the computer processes with the artistic instincts. The essay examines the role of computer systems in assisting artists in producing shifting, flexible, and information-driven physical experiences that exceed the common boundaries of art. Generative design involves the use of factors, chance, and rule-based reasoning, to generate forms that look like they were not written by a person. It is grounded on computer creativity and algorithmic aesthetics. Through AI and machine learning technologies as well as software applications, such as Grasshopper, Processing, and Houdini, designers have the opportunity to perform repeated research and feedback processes to simulate how things grow, move, and interact in nature. The analysis investigates how generative strategies transform the work of the designer as an entity that makes to one that maintains things running. It also puts into the limelight the interaction between human knowledge and machine intelligence. Case studies of popular generative installations demonstrate the way in which such works form interesting interactive environments that evolve according to the interaction of people with them and the information regarding the surrounding environment. Besides considering how things appear, the issues that are raised in this study include psychological and ethical questions regarding authorship, unpredictable, and the sustainability of computer art over time. The given study demonstrates that generative design can transform the process of creating future conceptual art by addressing such issues as technological restrictions, control over chance and material concerns. Generative design is perceived as a form of creation and a form of thinking of how art, technology, human experience combine to form new modes of expressing ourselves and telling stories in space.

AI FOR SUSTAINABLE ART PRODUCTION MANAGEMENT

2025-12-13T10:25:03+00:00

This study looks into how AI technologies can help artists to use resources more efficiently and make less waste, and make their work more eco-friendly. AI provides tools that enable not only greater creativity but also less damage that can be done to the environment by making and sharing art via AI. It does this by linking new ideas in art with environmental-friendly ways of making things. The first part of the study is an extensive review of the existing literature on the uses of AI in art and acceptance of environmentally friendly methods in creative areas such as design, digital medium, and the visual arts. A mixed approach is applied for the technique, which examines both qualitative and numeric aspects of sustainability, such as energy economy, lifetime effect of materials, and reducing carbon emissions via AI-driven actions. Some important areas of focus are optimising resources with the help of AI, making things that use less energy, and choosing smart materials according to lifecycle analysis. The paper also contains case-studies of digital art platforms that deploy AI, fashion efforts that are good for the environment, and creative AI projects that attempt to reduce waste. The results shows the potential of AI as a creative partner to be a sustainability driver. It can promote responsible innovation without compromising on art purism. The paper comes to the conclusion that the use of AI as a means to aid in making art production more sustainable is a good way for the creative economy to move towards circularity and environmental awareness.