How the Introduction of Machine Traders and Disclosure of Their Presence Affect Prediction Accuracy: An Online Controlled Experiment in Prediction Market
通过在线控制实验，研究了在传统预测市场中引入基于机器学习的交易者以及是否披露其存在对预测准确性的影响，发现机器引入既通过竞争激励人类更努力决策，也可能因过度交易降低准确性，而披露机器存在则可能减少人类努力。
Incorporating prediction models developed based on machine learning algorithms into the traditional prediction market creates hybrid intelligence. We design and conduct an online controlled experiment to investigate the impacts of two dimensions of human–machine interaction, whether to introduce machines as traders and whether to disclose their presence, on the prediction performance. The results of the experiment reveal that the introduction of machines creates two competing effects on prediction accuracy. The positive influence comes from the intensified competition brought by machines, which fosters a strong desire to win among human participants and motivates them to engage in more deliberate decision-making efforts. Conversely, in the context of intensive competition, humans are inclined to trade at a large magnitude, consequently leading to a decrease in prediction performance. Furthermore, the results indicate that simply disclosing the presence of machines can have a detrimental impact on prediction performance, as it may lead to a reduction in human deliberation efforts. Furthermore, this article delves into the potential mechanisms involved. This study contributes to the understanding of human behaviors in hybrid prediction markets and highlights the need for careful human–machine interaction design to optimize prediction market performance