TY - GEN
T1 - Enhancing crowdworkers' vigilance
AU - Elmalech, Avshalom
AU - Sarne, David
AU - David, Esther
AU - Hajaj, Chen
N1 - Funding Information:
The research presented in this paper was partially supported by the Israel Science Foundation (grant No. 1083/13),the ISF-NSFC joint research program (grant No. 2240/15), the Ministry of Science, Technology and Space, Israel with the National Science Council (NSC) of Taiwan, and a Harvard Center for Research on Computation and Society fellowship.
PY - 2017
Y1 - 2017
N2 - This paper presents methods for improving the attention span of workers in tasks that heavily rely on their attention to the occurrence of rare events. The underlying idea in our approach is to dynamically augment the task with some dummy (artificial) events at different times throughout the task, rewarding the worker upon identifying and reporting them. The proposed approach is an alternative to the traditional approach of exclusively relying on rewarding the worker for successfully identifying the event of interest itself. We propose three methods for timing the dummy events throughout the task. Two of these methods are static and determine the timing of the dummy events at random or uniformly throughout the task. The third method is dynamic and uses the identification (or misidentification) of dummy events as a signal for the worker's attention to the task, adjusting the rate of dummy events generation accordingly.
AB - This paper presents methods for improving the attention span of workers in tasks that heavily rely on their attention to the occurrence of rare events. The underlying idea in our approach is to dynamically augment the task with some dummy (artificial) events at different times throughout the task, rewarding the worker upon identifying and reporting them. The proposed approach is an alternative to the traditional approach of exclusively relying on rewarding the worker for successfully identifying the event of interest itself. We propose three methods for timing the dummy events throughout the task. Two of these methods are static and determine the timing of the dummy events at random or uniformly throughout the task. The third method is dynamic and uses the identification (or misidentification) of dummy events as a signal for the worker's attention to the task, adjusting the rate of dummy events generation accordingly.
UR - http://www.scopus.com/inward/record.url?scp=85031906138&partnerID=8YFLogxK
U2 - 10.24963/ijcai.2017/675
DO - 10.24963/ijcai.2017/675
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AN - SCOPUS:85031906138
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 4826
EP - 4830
BT - 26th International Joint Conference on Artificial Intelligence, IJCAI 2017
A2 - Sierra, Carles
T2 - 26th International Joint Conference on Artificial Intelligence, IJCAI 2017
Y2 - 19 August 2017 through 25 August 2017
ER -