Publications Details

CHARACTERIZING HUMAN PERFORMANCE: DETECTING TARGETS AT HIGH FALSE ALARM RATES

Speed, Ann S.; Wheeler, Jason W.; Russell, John L.; Oppel, Fred; Sanchez, Danielle; Silva, Austin R.; Chavez, Anna

The prevalence effect is the observation that, in visual search tasks as the signal (target) to noise (non-target) ratio becomes smaller, humans are more likely to miss the target when it does occur. Studied extensively in the basic literature [e.g., 1, 2], this effect has implications for real-world settings such as security guards monitoring physical facilities for attacks. Importantly, what seems to drive the effect is the development of a response bias based on learned sensitivity to the statistical likelihood of a target [e.g., 3-5]. This paper presents results from two experiments aimed at understanding how the target prevalence impacts the ability for individuals to detect a target on the 1,000th trial of a series of 1000 trials. The first experiment employed the traditional prevalence effect paradigm. This paradigm involves search for a perfect capital letter T amidst imperfect Ts. In a between-subjects design, our subjects experienced target prevalence rates of 50/50, 1/10, 1/100, or 1/1000. In all conditions, the final trial was always a target. The second (ongoing) experiment replicates this design using a notional physical facility in a mod/sim environment. This simulation enables triggering different intrusion detection sensors by simulated characters and events (e.g., people, animals, weather). In this experiment, subjects viewed 1000 “alarm” events and were asked to characterize each as either a nuisance alarm (e.g., set off by an animal) or an attack. As with the basic visual search study, the final trial was always an attack.