Aysha Alfalasi

Thesis

Thesis - Visual Sense-Making in AI Filmmaking (working title)

This practice-led research explores how AI filmmaking operates within the broader context of film studies and the creative industries, with a specific focus on prompt engineering as a core process. Sense, or meaning, in a film is conveyed through the interplay of audio-visual elements arranged to construct meaning within the frame. Using textual inputs, referred to as prompts, Generative Artificial Intelligence (GenAI) tools have enabled filmmakers to push the boundaries of cinematic storytelling, creating films that transcend the limitations of real-world film construction. Prompts, which provide a visual description of the desired output, rely on precise formatting and structuring. However, since GenAI relies heavily on embedded information to generate its outputs, the processes by which it constructs meaning remain largely opaque, raising critical questions about its visual sense-making processes and the integrity of its creative expression. My research addresses the following questions: How does AI interpret and construct meaning? How is that meaning perceived by audiences? What are the implications for authorship and originality?

Biography

Biography

PhD student researching AI filmmaking and visual sense-making. I have a background in applied media sciences, specialising in film production, audio production, graphic design and journalism. After spending seven years in corporate media, I transitioned to practical filmmaking to pursue my passion for visual storytelling. I hold an MSc in Filmmaking and Media Arts from the University of Glasgow and an MLitt in Film, Visual Culture, and Arts Management from the University of Aberdeen.

Research

Research

Research Interests

prompt engineering in generative AI filmmaking; semiotics and the language of cinema; visual sense-making in AI-generated outputs; authorship, authenticity, and originality in AI filmmaking; audience engagement with AI-generated films