False Positives vs. False Negatives

Existing approaches to trading off false positive versus false negative errors in input recognition are based on imprecise ideas of how these errors affect user experience that are unlikely to hold for all situations. To inform dynamic approaches to setting such a tradeoff, two user studies were conducted on how relative preference for false positive versus false negative errors is influenced by differences in the temporal cost of error recovery, and high-level task factors (time pressure, multi-tasking). Participants completed a tile selection task in which false positive and false negative errors were injected at a fixed rate, and the temporal cost to recover from each of the two types of error was varied, and then indicated a preference for one error type or the other, and a frustration rating for the task. Responses indicate that the temporal costs of error recovery can drive both frustration and relative error type preference, and that participants exhibit a bias against false positive errors, equivalent to ∼1.5 seconds or more of added temporal recovery time. Several explanations for this bias were revealed, including that false positive errors impose a greater attentional demand on the user, and that recovering from false positive errors imposes a task switching cost.