Observers have difficulty detecting visual changes. However, they are unaware of this inability, suggesting that people do not have an accurate understanding of visual processes. We explored whether this error is related to participants’ beliefs about the roles of intention and scene complexity in detecting changes. In Experiment 1 participants had a higher failure rate for detecting changes in an incidental change detection task than an intentional change detection task. This effect of intention was greatest for complex scenes. However, participants (...) predicted equal levels of change detection for both types of changes across scene complexity. In Experiment 2, emphasizing the differences between intentional and incidental tasks allowed participants to make predictions that were less inaccurate. In Experiment 3, using more sensitive measures and accounting for individual differences did not further improve predictions. These findings suggest that adults do not fully understand the role of intention and scene complexity in change detection. (shrink)

Recently, a number of experiments have emphasized the degree to which subjects fail to detect large changes in visual scenes. This finding, referred to as “change blindness,” is often considered surprising because many people have the intuition that such changes should be easy to detect. Levin, Momen, Drivdahl, and Simons documented this intuition by showing that the majority of subjects believe they would notice changes that are actually very rarely detected. Thus subjects exhibit a metacognitive error we refer to as (...) “change blindness blindness.” Here, we test whether CBB is caused by a misestimation of the perceptual experience associated with visual changes and show that it persists even when the pre- and postchange views are separated by long delays. In addition, subjects overestimate their change detection ability both when the relevant changes are illustrated by still pictures, and when they are illustrated using videos showing the changes occurring in real time. We conclude that CBB is a robust phenomenon that cannot be accounted for by failure to understand the specific perceptual experience associated with a change. (shrink)

Smilek, Eastwood, Reynolds, and Kingstone suggests that the studies reported in Beck, M. R., Levin, D. T. and Angelone, B. A. are not ecologically valid. Here, we argue that not only are change blindness and change blindness blindness studies in general ecologically valid, but that the studies we reported in Beck, Levin, and Angelone, 2007 are as well. Specifically, we suggest that many of the changes used in our study could reasonably be expected to occur in the real world. Furthermore, (...) the conclusion from Beck et al. that knowledge about the role of intention and scene complexity in change detection is not readily accessible applies not only to the laboratory studies we conducted but also to real world situations. (shrink)

Previous research demonstrates that implicitly learned probability information can guide visual attention. We examined whether the probability of an object changing can be implicitly learned and then used to improve change detection performance. In a series of six experiments, participants completed 120–130 training change detection trials. In four of the experiments the object that changed color was the same shape on every trial. Participants were not explicitly aware of this change probability manipulation and change detection performance was not improved for (...) the trained shape versus untrained shapes. In two of the experiments, the object that changed color was always in the same general location . Although participants were not explicitly aware of the change probability, implicit knowledge of it did improve change detection performance in the trained location. These results indicate that improved change detection performance through implicitly learned change probability occurs for location but not shape. (shrink)

Statistical properties in the visual environment can be used to improve performance on visual working memory tasks. The current study examined the ability to incidentally learn that a change is more likely to occur to a particular feature dimension and use this information to improve change detection performance for that dimension . Participants completed a change detection task in which one change type was more probable than others. Change probability effects were found for color and shape changes, but not location (...) changes, and intentional strategies did not improve the effect. Furthermore, the change probability effect developed and adapted to new probability information quickly. Finally, in some conditions, an improvement in change detection performance for a probable change led to an impairment in change detection for improbable changes. (shrink)