A Comparison Study of Human and Machine-Generated CreativitySource: Journal of Computing and Information Science in Engineering:;2023:;volume( 023 ):;issue: 005::page 51012-1DOI: 10.1115/1.4062232Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Creativity is a fundamental feature of human intelligence. However, achieving creativity is often considered a challenging task, particularly in design. In recent years, using computational machines to support people in creative activities in design, such as idea generation and evaluation, has become a popular research topic. Although there exist many creativity support tools, few of them could produce creative solutions in a direct manner, but produce stimuli instead. DALL·E is currently the most advanced computational model that could generate creative ideas in pictorial formats based on textual descriptions. This study conducts a Turing test, a computational test, and an expert test to evaluate DALL·E’s capability in achieving combinational creativity comparing with human designers. The results reveal that DALL·E could achieve combinational creativity at a similar level to novice designers and indicate the differences between computer and human creativity.
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contributor author | Chen, Liuqing | |
contributor author | Sun, Lingyun | |
contributor author | Han, Ji | |
date accessioned | 2023-11-29T18:58:02Z | |
date available | 2023-11-29T18:58:02Z | |
date copyright | 4/19/2023 12:00:00 AM | |
date issued | 4/19/2023 12:00:00 AM | |
date issued | 2023-04-19 | |
identifier issn | 1530-9827 | |
identifier other | jcise_23_5_051012.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4294495 | |
description abstract | Creativity is a fundamental feature of human intelligence. However, achieving creativity is often considered a challenging task, particularly in design. In recent years, using computational machines to support people in creative activities in design, such as idea generation and evaluation, has become a popular research topic. Although there exist many creativity support tools, few of them could produce creative solutions in a direct manner, but produce stimuli instead. DALL·E is currently the most advanced computational model that could generate creative ideas in pictorial formats based on textual descriptions. This study conducts a Turing test, a computational test, and an expert test to evaluate DALL·E’s capability in achieving combinational creativity comparing with human designers. The results reveal that DALL·E could achieve combinational creativity at a similar level to novice designers and indicate the differences between computer and human creativity. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | A Comparison Study of Human and Machine-Generated Creativity | |
type | Journal Paper | |
journal volume | 23 | |
journal issue | 5 | |
journal title | Journal of Computing and Information Science in Engineering | |
identifier doi | 10.1115/1.4062232 | |
journal fristpage | 51012-1 | |
journal lastpage | 51012-10 | |
page | 10 | |
tree | Journal of Computing and Information Science in Engineering:;2023:;volume( 023 ):;issue: 005 | |
contenttype | Fulltext |