Towards a Principled Evaluation of Likeability for Machine-Generated Art

Lia Coleman; Panos Achlioptas; Mohamed Elhoseiny

Towards a Principled Evaluation of Likeability for Machine-Generated Art

Lia Coleman, Panos Achlioptas, Mohamed Elhoseiny

Computer, Electrical and Mathematical Sciences and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Creativity is a cornerstone of human intelligence and perhaps its most complex aspect. Thus, it is very interesting to understand how AI is already being used by professionals in creative domains like the arts and fashion. Namely, do artists actually like AI-generated “paintings"? In this study we collect and analyze responses on these questions from various contemporary artists and compare them to more naive, crowd-sourced ones. We highlight the importance of considering artists’ opinion when evaluating AI-based art, and present a promising approach for researchers to do this easily.

Original language	English (US)
Title of host publication	32nd Conference on Neural Information Processing Systems (NeurIPS 2019), Montréal, Canada
Publisher	NeurIPS
State	Published - 2019

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We want to thank the artists who helped us with our research: Brooke Cheng, Dwayne Jones, Joseph Wilk, Luisa Fabrizi, Mark Hernandez, Taís Mauk, Michelle Cheung, Julia Peter, Francisco Rojo, Mathilde Mouw-Rao, Iain Nash, and Achim Koh.

Access to Document

https://repository.kaust.edu.sa/bitstream/10754/662646/1/V3_Towards%20a%20Principled%20Evaluation%20of%20Likeability%20for%20Machine-Generated%20Art.pdf

Cite this

Coleman, L., Achlioptas, P., & Elhoseiny, M. (2019). Towards a Principled Evaluation of Likeability for Machine-Generated Art. In 32nd Conference on Neural Information Processing Systems (NeurIPS 2019), Montréal, Canada NeurIPS. https://repository.kaust.edu.sa/bitstream/10754/662646/1/V3_Towards%20a%20Principled%20Evaluation%20of%20Likeability%20for%20Machine-Generated%20Art.pdf

@inproceedings{db19fc32f0e14abb8e48ac13cb1a23fc,

title = "Towards a Principled Evaluation of Likeability for Machine-Generated Art",

abstract = "Creativity is a cornerstone of human intelligence and perhaps its most complex aspect. Thus, it is very interesting to understand how AI is already being used by professionals in creative domains like the arts and fashion. Namely, do artists actually like AI-generated “paintings{"}? In this study we collect and analyze responses on these questions from various contemporary artists and compare them to more naive, crowd-sourced ones. We highlight the importance of considering artists{\textquoteright} opinion when evaluating AI-based art, and present a promising approach for researchers to do this easily.",

author = "Lia Coleman and Panos Achlioptas and Mohamed Elhoseiny",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: We want to thank the artists who helped us with our research: Brooke Cheng, Dwayne Jones, Joseph Wilk, Luisa Fabrizi, Mark Hernandez, Ta{\'i}s Mauk, Michelle Cheung, Julia Peter, Francisco Rojo, Mathilde Mouw-Rao, Iain Nash, and Achim Koh.",

year = "2019",

language = "English (US)",

booktitle = "32nd Conference on Neural Information Processing Systems (NeurIPS 2019), Montr{\'e}al, Canada",

publisher = "NeurIPS",

}

Coleman, L, Achlioptas, P & Elhoseiny, M 2019, Towards a Principled Evaluation of Likeability for Machine-Generated Art. in 32nd Conference on Neural Information Processing Systems (NeurIPS 2019), Montréal, Canada. NeurIPS. <https://repository.kaust.edu.sa/bitstream/10754/662646/1/V3_Towards%20a%20Principled%20Evaluation%20of%20Likeability%20for%20Machine-Generated%20Art.pdf>

TY - GEN

T1 - Towards a Principled Evaluation of Likeability for Machine-Generated Art

AU - Coleman, Lia

AU - Achlioptas, Panos

AU - Elhoseiny, Mohamed

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: We want to thank the artists who helped us with our research: Brooke Cheng, Dwayne Jones, Joseph Wilk, Luisa Fabrizi, Mark Hernandez, Taís Mauk, Michelle Cheung, Julia Peter, Francisco Rojo, Mathilde Mouw-Rao, Iain Nash, and Achim Koh.

PY - 2019

Y1 - 2019

N2 - Creativity is a cornerstone of human intelligence and perhaps its most complex aspect. Thus, it is very interesting to understand how AI is already being used by professionals in creative domains like the arts and fashion. Namely, do artists actually like AI-generated “paintings"? In this study we collect and analyze responses on these questions from various contemporary artists and compare them to more naive, crowd-sourced ones. We highlight the importance of considering artists’ opinion when evaluating AI-based art, and present a promising approach for researchers to do this easily.

AB - Creativity is a cornerstone of human intelligence and perhaps its most complex aspect. Thus, it is very interesting to understand how AI is already being used by professionals in creative domains like the arts and fashion. Namely, do artists actually like AI-generated “paintings"? In this study we collect and analyze responses on these questions from various contemporary artists and compare them to more naive, crowd-sourced ones. We highlight the importance of considering artists’ opinion when evaluating AI-based art, and present a promising approach for researchers to do this easily.

UR - http://hdl.handle.net/10754/662646

UR - https://neurips2019creativity.github.io/doc/V3_Towards%20a%20Principled%20Evaluation%20of%20Likeability%20for%20Machine-Generated%20Art.pdf

M3 - Conference contribution

BT - 32nd Conference on Neural Information Processing Systems (NeurIPS 2019), Montréal, Canada

PB - NeurIPS

ER -

Towards a Principled Evaluation of Likeability for Machine-Generated Art

Abstract

Bibliographical note

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