Interactive Performance: Immersive Storytelling Through Proximate AI-Generated Narratives for Local Theatre Audiences

Project Abstract

This study investigates how proximate artificial intelligence can augment live theatre by delivering immersive, responsive narratives that adapt to local audiences and spaces. Grounded in theatre studies, digital humanities, and human-computer interaction, the research explores a framework for integrating real-time AI-generated narrative elements with performer-led performance, audience participation, and environmental storytelling. The primary aim is to co-create an experiential theatre model where AI acts as a proximate dramaturg and co-creator, shaping plot trajectories, character perspectives, and scene transitions in dialogue with performers and audience input. A mixed-methods approach combines design-based research, dramaturgical analysis, and qualitative user studies to examine aesthetic, ethical, and logistical dimensions of the interactive system. The theoretical component draws on concepts of collaborative authorship, interactivity in performance, and the ethics of machine-generated content in live art. Methodologically, the project develops a modular toolkit comprising (i) an AI narrative engine capable of local context synthesis from audience cues, venue characteristics, and culturally resonant motifs; (ii) a real-time feedback loop connecting audience sensors, performer prompts, and stage management signals; and (iii) a dramaturgical rubric for balancing agency between AI and human creators, ensuring coherence, safety, and artistic intent. The experimental phase conducts a series of performances across diverse local theatres, collecting data on audience engagement, perceived authenticity, and emotional impact through observation, interviews, and physiological measures. The analyses scrutinize how proximate AI influences narrative agency, pacing, character development, and thematic resonance, while also evaluating the implications for accessibility, inclusivity, and community relevance. Key findings illuminate how proximity—physical or perceived—of AI agents enhances immediacy and immersion, enabling dynamic adaptations to audience feedback without diminishing live performance's spontaneity. The research identifies optimal interaction modalities, such as micro-dialogue inserts, audience-initiated plot branches, and actor-AI co-voicing that preserves human expressive nuance. It also foregrounds governance considerations, including transparency about AI contributions, data privacy, and safeguards against biased or harmful content. The study contributes a transferable, ethical blueprint for choreographing AI-human collaboration on stage, with practical guidelines for rehearsal, technical infrastructure, and contingency planning. Additionally, it presents a conceptual model for evaluating immersive theatre experiences that foreground situated, local storytelling while leveraging AI to expand expressive possibilities. Ultimately, the project demonstrates that well-designed proximate AI can extend the dramaturgical repertoire of local theatre, enabling scalable yet intimate storytelling that remains responsive to community contexts. The implications span academic discourse, professional practice, and audience empowerment, offering a framework for future explorations into hybrid performance forms that sustain artistic integrity, inclusivity, and vibrant regional theatre ecosystems.

Project Overview

What This Project Is About

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This project explores how live theatre can feel more immediate and responsive by using AI-generated narratives that react to audiences in real time. It looks at ways performers and audiences interact with AI-driven story elements placed near or on stage, shaping the unfolding drama without losing the human touch of live performance.

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The Problem It Addresses

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Traditional theatre has a fixed script and rarely adapts to audience reactions in real time. This project asks: how can we maintain theatre’s immediacy and artistry while adding smart, audience-aware storytelling that remains accessible and ethically responsible?

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Objectives of the Project

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1. Explore how proximate AI can generate supplementary narratives during a live performance.
2. Evaluate audience reactions and its influence on narrative direction.
3. Test practical integration with actors, lighting, and sound while preserving safety and ethics.
4. Document best practices for rehearsal and live adaptation.

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What You Will Do Step by Step

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1. Survey existing approaches to interactive theatre and AI storytelling.
2. Design a small performance prototype with AI-generated prompts placed near the stage.
3. Run rehearsals to observe how audiences interact and how narratives shift.
4. Collect feedback from participants and compare different interaction modes.
5. Analyze how the AI content affects storytelling clarity and emotional engagement.
6. Refine the setup based on insights and document the process.
7. Prepare a final performance and a reflective report.

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Expected Outcome

A demonstrable live performance model where audience presence subtly shifts the narrative through AI prompts, along with a guide for safe, ethical deployment and a reflective analysis of its artistic value and audience impact.