AI & Creativity? Why AI cannot create art: Chiang’s arguments revisited

Science fiction writer Ted Chiang has argued why AI cannot create art. I have proposed some counterarguments, which are meant to provoke thought. Chiang’s arguments against AI’s artistic capabilities can be summarized as follows: i) The Microdecision Argument – Art involves numerous conscious and un...

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Detalhes bibliográficos
Autor: Hernández Fernández, Antonio|||0000-0002-9466-2704
Formato: artículo
Fecha de publicación:2025
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/428600
Acesso em linha:https://hdl.handle.net/2117/428600
Access Level:acceso abierto
Palavra-chave:Artificial Intelligence
AI and Art
Creativity
Ted Chiang
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
Descrição
Resumo:Science fiction writer Ted Chiang has argued why AI cannot create art. I have proposed some counterarguments, which are meant to provoke thought. Chiang’s arguments against AI’s artistic capabilities can be summarized as follows: i) The Microdecision Argument – Art involves numerous conscious and unconscious decisions. Chiang argues that AI relies solely on statistical models and imitation, producing predictable and mediocre results; ii)The Lack of Intentionality Argument – True art requires intention. Since AI has no emotions, intellectual joy, or desires, it cannot create with meaningful intent; iii) The Effort and Process Argument – The creative process and effort are integral to artistic value. AI generates content effortlessly, which Chiang believes diminishes artistic worth; iv) The General Intelligence and Efficiency Argument – AI struggles to acquire new skills efficiently compared to humans. Despite excelling at games like Go, it requires vast datasets, whereas humans learn more intuitively—key to artistic creation.v) The Lack of Originality Argument – AI is generative but not creative. Its outputs, built on automated mechanisms, lack true originality, resulting in statistically average work. These points lead to discussions in classrooms and faculty meetings about art (and artistic education), raising counterarguments that may contribute to future research and debate.