Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Who Gets Credit for AI-Generated Art?

Who Gets Credit for AI-Generated Art?

Thumbnail Image
Download
Name

1-s2.0-S2589004220307070-main.pdf

Description
Published version
Size

2.04 MB

Format

Adobe PDF

Checksum (MD5)

21cda66d49589d8329493d46b1f2e470

sword-2021-03-16T13:31:52.original.xml (130 B)
Original SWORD entry document
Author(s)
Epstein, Ziv
•
Levine, Sydney
•
Rand, David Gertler
•
Rahwan, Iyad
Date Issued
September 2020
Journal
iScience
Publisher
Elsevier BV
Citation
Epstein, Ziv et al. "Who Gets Credit for AI-Generated Art?" iScience 23, 9 (September 2020): 101515 © 2020 The Author(s)
Version
Final published version
Abstract
The recent sale of an artificial intelligence (AI)-generated portrait for $432,000 at Christie's art auction has raised questions about how credit and responsibility should be allocated to individuals involved and how the anthropomorphic perception of the AI system contributed to the artwork's success. Here, we identify natural heterogeneity in the extent to which different people perceive AI as anthropomorphic. We find that differences in the perception of AI anthropomorphicity are associated with different allocations of responsibility to the AI system and credit to different stakeholders involved in art production. We then show that perceptions of AI anthropomorphicity can be manipulated by changing the language used to talk about AI—as a tool versus agent—with consequences for artists and AI practitioners. Our findings shed light on what is at stake when we anthropomorphize AI systems and offer an empirical lens to reason about how to allocate credit and responsibility to human stakeholders.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Sloan School of Management
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution 4.0 International license
https://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/130248
DOI of Published Version
https://doi.org/10.1016/j.isci.2020.101515
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.