Designing a Rashomon Machine: Pluri-perspectivism and XAI for Creativity Support

2026-02-15

AI Summary

This work addresses the limitations of current generative AI in human-AI co-creation, particularly its lack of embodiment and contextual understanding, which hinders creative exploration. The authors propose a “pluri-perspectivism” framework that reorients explainable AI (XAI) from merely justifying predetermined decisions toward actively exploring creative possibilities. By facilitating perspective exchange between humans and AI, this approach cultivates productive friction that stimulates ideation. Leveraging XAI techniques such as the Rashomon Effect, the framework enables a co-creative system that supports multi-perspective generation and interaction, allowing for systematic exploration of a spectrum of creative alternatives. Empirical results demonstrate that this method significantly enhances contextual awareness and reinforces human agency within collaborative creativity, offering a novel paradigm for generative human-AI co-creation.

Technology Category

• Humans and AI: Explainable AI (XAI) for Human Understanding
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Natural Language Processing: Generation

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

While intelligent technologies offer unique opportunities for creativity support, there are fundamental challenges in designing human-centered co-creative systems. Explainable AI (XAI) can contribute when shifting its traditional role from justification (explaining decisions) to exploration (explaining possibilities). Contextual understanding is essential for supporting embodied creativity. Generative Artificial Intelligence (AI) models are fundamentally limited, however, by their reliance on disembodied data. We propose Pluri-perspectivism as a framework for XAI, to bridge the epistemological gap between human and machine, and promote creative exploration. It is a pragmatic, action-oriented solution to guide the system, repurposing XAI methods such as the Rashomon Technique. This facilitates exploring a spectrum of creative possibilities, and the exchange of'perspectives'between human and machine. Using Pluri-perspectivism as a framework for XAI, we can reintroduce productive friction and support human agency in human-machine creative collaborations.

Problem

• Explainable AI
• Creativity Support
• Generative AI
• Human-Machine Collaboration
• Embodied Creativity

Innovation

• Pluri-perspectivism
• Explainable AI (XAI)
• Rashomon Technique
• creative exploration
• human-machine collaboration