Developing Ethical AI Frameworks for Inclusive Casting and Representation in Independent Cinema: A Mixed-Methods Study - Kashif Lodhi; Dr Atif khan; Gianfranco Rusconi; Sohail Ahmad (Corresponding Author) (`, 2025)
This mixed-methods study examines the transformative impact of Artificial Intelligence (AI) on independent cinema, exploring both opportunities and challenges in developing ethical frameworks for inclusive casting and representation. The research analyzes AI's revolutionary applications across multiple filmmaking domains, including script analysis, storytelling enhancement, visual effects creation, and production efficiency optimization. Through comprehensive examination of AI-enhanced script analysis tools that provide unprecedented audience insights, and deep learning technologies that revolutionize visual effects rendering, the study demonstrates significant productivity gains and creative possibilities. However, the investigation reveals critical ethical concerns surrounding AI-driven casting decisions, particularly regarding algorithmic bias, diversity representation, and the perpetuation of existing stereotypes in the film industry. The research highlights the tension between AI's data-driven efficiency and the preservation of human creativity, emphasizing concerns about reduced human autonomy in key decision-making processes. The study advocates for a balanced approach that harnesses AI's computational power while maintaining ethical oversight, transparency, and inclusivity standards. Findings suggest that successful AI integration in filmmaking requires careful consideration of bias mitigation, fair representation protocols, and the preservation of human artistic intuition. The research concludes that AI should function as a creative collaborator rather than a replacement for human judgment, particularly in casting decisions that directly impact industry diversity and representation. Keywords: Artificial Intelligence, Independent Cinema, Ethical Frameworks, Inclusive Casting, Algorithmic Bias, Human-Machine Collaboration