TY - GEN
T1 - Detecting demographic bias in automatically generated personas
AU - Salminen, Joni
AU - Jansen, Bernard J.
AU - Soongyo, Jung
N1 - Publisher Copyright:
© 2019 Copyright is held by the author/owner(s).
PY - 2019/5/2
Y1 - 2019/5/2
N2 - We investigate the existence of demographic bias in automatically generated personas by producing personas from YouTube Analytics data. Despite the intended objectivity of the methodology, we find elements of bias in the data-driven personas. The bias is highest when doing an exact match comparison, and the bias decreases when comparing at age or gender level. The bias also decreases when increasing the number of generated personas. For example, the smaller number of personas resulted in underrepresentation of female personas. This suggests that a higher number of personas gives a more balanced representation of the user population and a smaller number increases biases. Researchers and practitioners developing data-driven personas should consider the possibility of algorithmic bias, even unintentional, in their personas by comparing the personas against the underlying raw data.
AB - We investigate the existence of demographic bias in automatically generated personas by producing personas from YouTube Analytics data. Despite the intended objectivity of the methodology, we find elements of bias in the data-driven personas. The bias is highest when doing an exact match comparison, and the bias decreases when comparing at age or gender level. The bias also decreases when increasing the number of generated personas. For example, the smaller number of personas resulted in underrepresentation of female personas. This suggests that a higher number of personas gives a more balanced representation of the user population and a smaller number increases biases. Researchers and practitioners developing data-driven personas should consider the possibility of algorithmic bias, even unintentional, in their personas by comparing the personas against the underlying raw data.
UR - http://www.scopus.com/inward/record.url?scp=85067280102&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067280102&partnerID=8YFLogxK
U2 - 10.1145/3290607.3313034
DO - 10.1145/3290607.3313034
M3 - Conference contribution
AN - SCOPUS:85067280102
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019
Y2 - 4 May 2019 through 9 May 2019
ER -