Keep It Mystic? - The Effects of Algorithm Transparency on the Use of Advice.

Algorithmic decision support is omnipresent for many managerial tasks where human judgment makes the final call. However, the lack of transparency of algorithms is often stated as a barrier of successful human-machine collaboration. In this paper, we analyze the effects of algorithm transparency on the perceived value of algorithmic advice and its resulting utilization for a simple, easy-to-understand algorithm. In a laboratory experiment, participants received algorithmic advice for a forecasting task. Only the treatment group was informed about the underlying principles of the simple yet optimal advice-giving algorithm. While the explanation increased the understanding of the algorithmic procedure, it reduced the perceived value of the algorithmic advice, its utilization, and the participants’ performance. Our results indicate that the effects of algorithm transparency on the use of algorithmic advice are not straightforward, and that transparency might even be harmful. Going forward, we plan to explore whether algorithm complexity moderates this effect.