DocumentCode
2249678
Title
Mini-crowdsourcing end-user assessment of intelligent assistants: A cost-benefit study
Author
Shinsel, Amber ; Kulesza, Todd ; Burnett, Margaret ; Curran, William ; Groce, Alex ; Stumpf, Simone ; Wong, Weng-Keen
Author_Institution
Oregon State Univ., Corvallis, OR, USA
fYear
2011
fDate
18-22 Sept. 2011
Firstpage
47
Lastpage
54
Abstract
Intelligent assistants sometimes handle tasks too important to be trusted implicitly. End users can establish trust via systematic assessment, but such assessment is costly. This paper investigates whether, when, and how bringing a small crowd of end users to bear on the assessment of an intelligent assistant is useful from a cost/benefit perspective. Our results show that a mini-crowd of testers supplied many more benefits than the obvious decrease in workload, but these benefits did not scale linearly as mini-crowd size increased - there was a point of diminishing returns where the cost-benefit ratio became less attractive.
Keywords
cost-benefit analysis; intelligent design assistants; program testing; cost-benefit ratio; cost-benefit study; diminishing returns; intelligent assistants; mini-crowd size; mini-crowdsourcing end-user assessment; systematic assessment; Analysis of variance; Educational institutions; Reliability; Software; Software testing; Systematics; crowdsourcing; end-user programming; machine learning; testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Visual Languages and Human-Centric Computing (VL/HCC), 2011 IEEE Symposium on
Conference_Location
Pittsburgh, PA
ISSN
1943-6092
Print_ISBN
978-1-4577-1246-3
Type
conf
DOI
10.1109/VLHCC.2011.6070377
Filename
6070377
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