Abstract
Incorporating machines into the traditional prediction market can create hybrid intelligence. To leverage the potentials of the human-machine hybrid information market, this study investigates the impacts of two elements of human-machine interaction design, machine participation, and machine disclosure, on prediction performance. The results of the experiment in this study reveal that simply disclosing machines will harm the prediction performance, as it may decrease humans’ deliberation effort. The findings also suggested two competing effects of machines participation on prediction accuracy. The positive influence comes from the intensive competition context brought by machines which enable humans to have desires to win and motivates them to put more deliberate efforts into decision-making. However, in the condition of intensive competition, humans tend to trade in large magnitude, which will lower the prediction performance. These findings provide implications for human-machine hybrid market design.
Recommended Citation
Li, Liting and Zheng, Haichao, "The Impacts of Machines on the Prediction Accuracy of Human-machine Hybrid Information Market" (2022). WHICEB 2022 Proceedings. 33.
https://aisel.aisnet.org/whiceb2022/33