Creative Loss: Ambiguity, Uncertainty and Indeterminacy
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866913655460724736 |
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| author | Holberton, Tom |
| author_facet | Holberton, Tom |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_10369 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Creative Loss: Ambiguity, Uncertainty and Indeterminacy Holberton, Tom Computers and Society Artificial Intelligence Human-Computer Interaction Machine Learning 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. |
| title | Creative Loss: Ambiguity, Uncertainty and Indeterminacy |
| topic | Computers and Society Artificial Intelligence Human-Computer Interaction Machine Learning |
| url | https://arxiv.org/abs/2501.10369 |