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Investigating the relationship between liking and belief in AI authorship in the context of Irish traditional music

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Abstract

Past work has investigated the degree to which human listeners may be prejudiced against music knowing that it was created by artificial intelligence (AI). While these studies did not find a statistically significant relationship, the listening experiments were performed with music genres such as contemporary classical music or free jazz which are fairly welcoming of technology. In this work, we explore this prejudice in a context where strong opinions on authenticity and technology are typical: Irish traditional music (ITM). We conduct a listening experiment with practitioners of ITM asking each subject to first listen to a human performance of music generated by a computer in the style of ITM (this provenance is unknown to the listener), and then rate how much they like the piece. After rating all six pieces, each subject listens to each again but rates how likely they believe it is composed by a computer. The results of our pilot study suggest ITM practitioners tend to rate belief in AI authorship lower the more they rate liking a tune.
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Dates and versions

hal-03849034 , version 1 (11-11-2022)

Licence

Attribution - CC BY 4.0

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  • HAL Id : hal-03849034 , version 1

Cite

Ken Déguernel, Bob L. T. Sturm, Hugo Maruri-Aguilar. Investigating the relationship between liking and belief in AI authorship in the context of Irish traditional music. CREAI 2022 Workshop on Artificial Intelligence and Creativity, Nov 2022, Udine, Italy. ⟨hal-03849034⟩
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