A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Is Deepfake Diversity Real? Analyzing the Diversity of Deepfake Avatars
Tekijät: Kaate, Ilkka; Salminen, Joni; Al Tamime, Reham; Jung, Soon-gyo; Jansen, Bernard J.
Kustantaja: Elsevier
Kustannuspaikka: OXFORD
Julkaisuvuosi: 2025
Journal: Expert Systems with Applications
Tietokannassa oleva lehden nimi: Expert Systems with Applications
Lehden akronyymi: EXPERT SYST APPL
Vuosikerta: 269
Sivujen määrä: 12
ISSN: 0957-4174
eISSN: 1873-6793
DOI: https://doi.org/10.1016/j.eswa.2025.126382
Verkko-osoite: https://doi.org/10.1016/j.eswa.2025.126382
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/485076347
Deepfake technology is increasingly integrated into global mobile and web services when human representation is not feasible or cost-effective. Our analysis of 202 deepfake avatars from three deepfake providers reveals significant demographic disparities with 18 out of 48 possible demographic groups unrepresented. Deepfake avatars' gender distribution was nearly balanced (49.01% male, 50.99% female), but older age groups (Baby Boomers and Silent Generation) were substantially underrepresented by 64.36% and 76.24%, respectively, relative to the average number of all deepfake avatars. Differences in language representation were present in deepfake avatar providers with only 1.06% of global languages covered. The findings indicate that current deepfake technology lacks diversity, primarily favoring young white individuals, neglecting older demographics, Asians, and Middle Eastern populations, with underrepresentation of 40.59% and 52.48%, respectively, relative to the average number of all deepfake avatars. Only 15.27% of deepfake avatars portray any occupational characteristics. Addressing these diversity gaps is crucial for better serving varied user groups and warrants attention from deepfake providers and caution from those using deepfakes.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
