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    A Comparison Study of Human and Machine-Generated Creativity

    Source: Journal of Computing and Information Science in Engineering:;2023:;volume( 023 ):;issue: 005::page 51012-1
    Author:
    Chen, Liuqing
    ,
    Sun, Lingyun
    ,
    Han, Ji
    DOI: 10.1115/1.4062232
    Publisher: 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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      A Comparison Study of Human and Machine-Generated Creativity

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4294495
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    contributor authorChen, Liuqing
    contributor authorSun, Lingyun
    contributor authorHan, Ji
    date accessioned2023-11-29T18:58:02Z
    date available2023-11-29T18:58:02Z
    date copyright4/19/2023 12:00:00 AM
    date issued4/19/2023 12:00:00 AM
    date issued2023-04-19
    identifier issn1530-9827
    identifier otherjcise_23_5_051012.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4294495
    description abstractCreativity 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.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Comparison Study of Human and Machine-Generated Creativity
    typeJournal Paper
    journal volume23
    journal issue5
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.4062232
    journal fristpage51012-1
    journal lastpage51012-10
    page10
    treeJournal of Computing and Information Science in Engineering:;2023:;volume( 023 ):;issue: 005
    contenttypeFulltext
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