Potential Abstract:
This research article presents a feminist framework for examining the potential of networks in fostering creativity through the application of generative artificial intelligence (AI) techniques. The integration of networks within creative processes has gained significant attention in recent years, yet there remains a dearth of research examining the intersectionality of gender, technology, and creativity within educational contexts. By adopting a feminist lens, this study seeks to address this gap and explore how networks in generative AI can support and promote creative practices, particularly among marginalized groups.
The study employs a mixed-methods approach, combining qualitative interviews, participant observations, and quantitative analysis, to investigate how generative AI networks can facilitate creativity within educational settings. Drawing on critical theories of gender and technology, the research examines the ways in which gendered power dynamics intersect with networked creativity and generative AI technologies. By employing a feminist framework, we aim to shed light on the potential biases and challenges that may exist within these systems, while also exploring opportunities for transformative and emancipatory practices.
Furthermore, this research article proposes a conceptual model that encompasses the interaction between networks, generative AI, and creativity from a feminist perspective. This model considers the complex relationship between individual agency, social structures, and technological affordances to understand the processes through which creativity is fostered within networked environments. By employing a feminist framework, we aim to critically examine how networks can facilitate or hinder creative expression and representation, while also considering the ethical and social implications of using generative AI technologies in educational settings.
Potential References:
- Generative adversarial networks–enabled human–artificial intelligence collaborative applications for creative and design industries: A systematic review of …
- Informing artificial intelligence generative techniques using cognitive theories of human creativity
- Bridging Generative Deep Learning and Computational Creativity.
- Creativity in generative musical networks: evidence from two case studies
- Black-box creativity and generative artifical intelligence
