TY - GEN
T1 - Exploring machine teaching for object recognition with the crowd
AU - Hong, Jonggi
AU - Xu, June
AU - Lee, Kyungjun
AU - Kacorri, Hernisa
N1 - Publisher Copyright:
© 2019 Copyright held by the owner/author(s).
PY - 2019/5/2
Y1 - 2019/5/2
N2 - Teachable interfaces can enable end-users to personalize machine learning applications by explicitly providing a few training examples. They promise higher robustness in the real world by significantly constraining conditions of the learning task to a specific user and their environment. While facilitating user control, their efectiveness can be hindered by lack of expertise or misconceptions. Through a mobile teachable testbed in Amazon Mechanical Turk, we explore how non-experts conceptualize, experience, and reflect on their engagement with machine teaching in the context of object recognition.
AB - Teachable interfaces can enable end-users to personalize machine learning applications by explicitly providing a few training examples. They promise higher robustness in the real world by significantly constraining conditions of the learning task to a specific user and their environment. While facilitating user control, their efectiveness can be hindered by lack of expertise or misconceptions. Through a mobile teachable testbed in Amazon Mechanical Turk, we explore how non-experts conceptualize, experience, and reflect on their engagement with machine teaching in the context of object recognition.
KW - Crowdsourcing
KW - Interactive machine learning
KW - Object recognition
KW - Teachable machines
UR - http://www.scopus.com/inward/record.url?scp=85067309359&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067309359&partnerID=8YFLogxK
U2 - 10.1145/3290607.3312873
DO - 10.1145/3290607.3312873
M3 - Conference contribution
AN - SCOPUS:85067309359
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
T2 - 2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019
Y2 - 4 May 2019 through 9 May 2019
ER -