Aoqi Li¹ (), Johan Hulleman¹, Wentao (Taylor) Si², Jeremy Wolfe^3,4; ¹University of Manchester, ²Bates College, ³Brigham and Women's Hospital, ⁴Harvard Medical School

Observers make errors in visual search, whether in a lab experiment or a real-life task. Those errors can be categorized as “deterministic” or “stochastic”. If errors are deterministic, errors committed once will definitely be repeated again. Alternatively, errors can be “stochastic”: occurring randomly with some probability. An error would lie in between these extremes if it is likely, but not guaranteed to occur a second time. To identify the nature of miss errors in a simple T-vs-L visual search task, we presented each search display twice in random sequence. The miss rate, P1, for the first copy of the display and the miss rate, P2, for the second copy were calculated, as was the proportion of cases where both copies were missed, P12. Purely stochastic errors would predict that P12=P1*P2. Purely deterministic errors will lead to P12=min⁡(P1,P2). If errors are a mix of stochastic and deterministic, P12 will fall between these two predictions. In Experiment 1 where the letters were clearly visible, the errors were almost completely stochastic. An error made on the first appearance of a display did not predict that an error would be repeated on the second appearance. In Experiments 2a and 2b where the visibility of the letters was manipulated, the errors became a mix of stochastic and deterministic. Lower contrast targets produced more deterministic errors. In Experiments 3a, 3b and 3c, we tested several interventions with the goal of finding a 'mindless' intervention that could effectively reduce errors without needing to know the answer in advance. An almost mindless intervention that knew the location but not the identity of items (Exp 3c), succeeded in reducing deterministic errors. This gives some insights into possible methods for reducing errors in important real-life visual search tasks, where search items may not be clearly defined and visible.

Acknowledgements: JMW was supported by NIH-NEI: EY017001, NSF: 2146617, and NIH-NCI: CA207490. AL and JH were supported by UKRI grant ES/X000443/1.