Algorithmic Appreciation Across Task Difficulty.
Eric Bogert, Rick Watson, Aaron Schecter · Journal of the Association for Information Systems · 2020
We propose a two by two experiment that investigates how humans respond to recommendations based on the difficulty of the task and the source of the recommendation. The two types of information sources which will provide recommendations in our experiment are algorithms and human crowds. We contribute to the burgeoning discourse on algorithmic appreciation by focusing on crowd counting, a task in which effort is a strong factor in predicting accuracy.