CYAIHCLGDec 12, 2024

Creative Loss: Ambiguity, Uncertainty and Indeterminacy

arXiv:2501.10369v1
Originality Synthesis-oriented
AI Analysis

This work addresses the problem of integrating machine learning into creative design processes for architects and designers, but it appears incremental as it builds on existing concepts without introducing new methods or data.

The article explores how machine learning can be used creatively to address ambiguity, uncertainty, and indeterminacy, reflecting on its growing role as a creative partner in design, with examples from architectural research at UCL.

This article evaluates how creative uses of machine learning can address three adjacent terms: ambiguity, uncertainty and indeterminacy. Through the progression of these concepts it reflects on increasing ambitions for machine learning as a creative partner, illustrated with research from Unit 21 at the Bartlett School of Architecture, UCL. Through indeterminacy are potential future approaches to machine learning and design.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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