With the increased sophistication of technology, humans have the possibility to offload a variety of tasks to algorithms. Here, we investigated whether the extent to which people are willing to offload an attentionally demanding task to an algorithm is modulated by the availability of a bonus task and by the knowledge about the algorithm's capacity. Participants performed a multiple object tracking (MOT) task which required them to visually track targets on a screen. Participants could offload an unlimited number of targets to a "computer partner". If participants decided to offload the entire task to the computer, they could instead perform a bonus task which resulted in additional financial gain-however, this gain was conditional on a high performance accuracy in the MOT task. Thus, participants should only offload the entire task if they trusted the computer to perform accurately. We found that participants were significantly more willing to completely offload the task if they were informed beforehand that the computer's accuracy was flawless (Experiment 1 vs. 2). Participants' offloading behavior was not significantly affected by whether the bonus task was incentivized or not (Experiment 2 vs. 3). These results combined with those from our previous study (Wahn et al. in PLoS ONE 18:e0286102, 2023), which did not include a bonus task but was identical otherwise, show that the human willingness to offload an attentionally demanding task to an algorithm is considerably boosted by the availability of a bonus task-even if not incentivized-and by the knowledge about the algorithm's capacity.
Keywords: Algorithmic appreciation; Algorithmic aversion; Cognitive offloading; Human–computer collaboration; Human–computer interaction; Social cognition.
© 2024. The Author(s).