Design Contradictions: Help or Hindrance?

Fuente: arXiv
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Autori principali: Owen, Aron E., Roberts, Jonathan C.
Natura: Preprint
Pubblicazione: 2024
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author Owen, Aron E.
Roberts, Jonathan C.
author_facet Owen, Aron E.
Roberts, Jonathan C.
contents The need for innovative ideas in data visualisation drives us to explore new creative approaches. Combining two or more creative words, particularly those that contradict each other, can positively impact the creative process, sparking novel ideas and designs. As we move towards AI-driven design, an open question arises: do these design contradictions work positively with AI tools? Currently, the answer is no. AI systems, like large language models (LLMs), rely on algorithms that engender similarity, whereas creativity often requires divergence and novelty. This poster initiates a conversation on how to drive AI systems to be more creative and generate new ideas. This research invites us to reconsider traditional design methods and explore new approaches in an AI-driven world. Can we apply the same techniques used in traditional design, like the double diamond model, or do we need new methods for design engineering? How can we quickly design visualisations and craft new ideas with generative AI? This paper seeks to start this critical conversation and offers practical insights into the potential of AI in driving creativity in data visualisation.
format Preprint
id arxiv_https___arxiv_org_abs_2409_02823
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Design Contradictions: Help or Hindrance?
Owen, Aron E.
Roberts, Jonathan C.
Human-Computer Interaction
The need for innovative ideas in data visualisation drives us to explore new creative approaches. Combining two or more creative words, particularly those that contradict each other, can positively impact the creative process, sparking novel ideas and designs. As we move towards AI-driven design, an open question arises: do these design contradictions work positively with AI tools? Currently, the answer is no. AI systems, like large language models (LLMs), rely on algorithms that engender similarity, whereas creativity often requires divergence and novelty. This poster initiates a conversation on how to drive AI systems to be more creative and generate new ideas. This research invites us to reconsider traditional design methods and explore new approaches in an AI-driven world. Can we apply the same techniques used in traditional design, like the double diamond model, or do we need new methods for design engineering? How can we quickly design visualisations and craft new ideas with generative AI? This paper seeks to start this critical conversation and offers practical insights into the potential of AI in driving creativity in data visualisation.
title Design Contradictions: Help or Hindrance?
topic Human-Computer Interaction
url https://arxiv.org/abs/2409.02823