The Impact Of Inattentional Blindness On Different Individuals
Introduction
Do you know that in our everyday lives we miss common things that are in our line of sight due to being so focused on something else? If your mind is not expecting it or searching for it you might miss it. At home have your parents ever yelled at you because you completely missed a person that walked into the room due to the fact that you were so engrossed in a tv show, or have you ever been on your cell phone while driving and missed a turn or, what about when you're at work trying to multitask and while you're sure you did everything that you were supposed to do correctly, your boss checks your work and sees that you’ve missed a couple of things. Our mind is programmed to pay attention to limited variables at once, we miss certain things because our eyes do not record everything in our field.
What is inattentional blindness?
Have you ever been walking down the street with your headphones listening to music or just fiddling away on your phone so engrossed in whatever in occupying your attention at the time you fail to notice that you have just passed by someone you know until they call your attention to it? That is called, “inattentional blindness. ” In the 1990s, the term inattentional blindness also known as perceptual blindness was coined by two psychologist Arien Mack and Irvin rock. While conducting an experiment Arien Mack and Irvin Rock discovered that their test subjects missed unexpected things in their line of sight of they were preoccupied by a separate consuming event. Inattentional blindness is defined as the phenomenon where someone completely misses something in their visual eye line because they were focusing on something else and new vision is unexpected. “Approximately half of observers fail to notice an ongoing and highly salient but unexpected event while they are engaged in a primary monitoring task. This extends the phenomenon of inattentional blindness ”
The effects of individual differences and task difficulty on inattentional blindness
Why does inattentional blindness occur and what is the effect it has on individual differences and task difficulty? This article explores whether individual differences in the ability to perform a primary task predict noticing rates for an unexpected object. few studies have explored whether individual differences contribute to the failure to notice unexpected events. The study of individual differences in inattentional blindness is considered problematic because the phenomenon is, by definition, limited to one critical trial for each observer it is difficult, if not impossible, to measure the reliability of detection across trials for an individual. To determine what such group differences tell us about individual differences in inattentional blindness, we must first consider why some people notice an unexpected object whereas others do not. Noticing an unexpected object on a critical trial could be due to random variability, so that any given individual would be equally likely to notice the unexpected object.
Experiment 1
A total of 46 undergraduate students (24 male, 22 female) participated voluntarily in exchange for credit in an introductory psychology course. All of them reported normal or corrected-to-normal vision. For the materials used in this experiment. All displays were presented on a Macintosh computer with a 17-in. CRT monitor, and the experimental displays and timing were controlled using custom software written in Python using the VisionEgg libraries and the distance was not restrained. On each trial, participants performed a tracking task in which they monitored the movements of four white shapes and ignored the movements of four black shapes. Their task assigned was to count the total number of times that any of the white shapes touched the sides of a 640 480-pixel gray window centered on the monitor. For each color, two of the shapes were capital L's and two were capital Ts. All objects moved independently on randomly determined trajectories, with the following constraints: (1) Motion was linear between changes of direction (2) every 10 msec, the object turned by a randomly determined amount ranging from 0º to 5º; (3) whenever an object touched the side of the display window, it rebounded at a randomly chosen angle, with additional constraints to prevent an object from bouncing repeatedly in a corner of the window. Each trial lasted approximately 8, 200 msec, and after each trial, participants were prompted to type the total number of times the white shapes touched the sides of the display.
The participants first completed a set of 10 practice trials (without unexpected-object trials) in which the objects moved at a fixed rate of 4. 32º/sec. (All objects on a given trial moved at the same speed. ) Following the practice trials, participants completed two blocks of trials in which the speed of the objects in the display was adjusted from trial to trial based on the accuracy of performance (using the Python port of the QUEST algorithm). Following an accurate count, the speed of the objects was increased, and following an inaccurate count, it was decreased. The object speeds were adjusted for everyone to achieve a consistent level of accuracy across participants.
After reporting the number of touches, participants were first asked “Did you notice anything other than the Ls and Ts on that last trial?” and then asked to “Describe what you saw. ” For these two questions, each individual typed their responses into a text box on the display monitor Results for experiment 1 To summarize the results of these findings, the experiment suggest that as long as participants try equally hard to do the task, noticing rates are driven by the actual task difficulty rather than by the ability to perform the task accurately. That is, participants may try equally hard to do a task, with some achieving better performance than others, but the level of performance does not predict noticing of an unexpected object.
Experiment 2
A total of 109 undergraduate students participated in exchange for credit in an introductory psychology course. All reported normal or corrected-to-normal vision. the data from 27 individuals were discarded, These exclusions left 82 participants (46 male, 36 female). Experiment 2 was identical to that of Experiment 1. Just as the first experiment all participants first completed 10 practice trials with all objects moving at 4. 32º/sec. They then completed two blocks of trials that adaptively determined the object speed necessary for 75%-accurate tracking performance Threshold tracking speeds on the two blocks were averaged to track how fast a participant could track the objects and still achieve 75% accuracy. Neither the practice block nor the QUEST blocks included any unexpected objects. Following these blocks, all participants completed 10 trials at a fixed speed (4. 32º/sec), followed by 1 critical trial at the same speed in which an unexpected object moved across the display (also at 4. 32º/sec). The speeds in this final block of trials and in the critical trial were constant across participants to provide a stable measure of inattentional blindness.
Individual differences in tracking speed were not correlated with noticing of the unexpected object, individual differences in the speed at which people can track objects accurately do not predict the detection of unexpected objects
Conclusion
Although other studies have varied the difficulty of the primary task, none have systematically measured the ability to perform the primary task prior to the critical trial containing the unexpected object. Consistent with earlier evidence, the studies in this article shows that task difficulty influences the rate of inattentional blindness. though, the accuracy with which people performed the primary task was unrelated to noticing of the unexpected object. Together, these findings show that inattentional blindness is driven by the difficulty of the primary task, not by performance on that task. Individual differences in fluid intelligence predicts blindness in a sample of older adults: a preliminary study Recent studies have begun to examine whether individual differences in aspects of cognition may predict inattentional blindness. Working memory capacity (WMC) has been the primary candidate predictor in these studies. The purpose if this research article was to carry out the study in a sample of older adults due to the evidence indicating that gF (general fluid intelligence) speed of processing are age-sensitive mental abilities.
Additionally, Li et al. (2004) have provided evidence that the speed-gF association is stronger in childhood and old age than in mid-life, consistent with the differentiation– dedifferentiation perspective of cognitive function. “We would expect there to be more performance variability in our proposed underlying processes in an older sample, and thereby providing us with a broader range of cognitive functioning to exam” when individuals are engaged with an attention demanding task, regions in the prefrontal cortex are activated (ACC).
In Experiment 1 A total of 36 healthy adults were recruited for the study (13 males, 23 females, age range 61–79, ). All participants were residents of the Edinburgh locality in Scotland. Participants were then screened for any history of neurological, medical, and motor disorders through a given questionnaire. The Participants were also screened for dementia using a device called the MMSE which is a Mini Mental State Exam in which a cut-off score of 26/30 was given. The experimental procedure followed the procedure cited in the Most et al. (2001) as described in my first body paragraph, however the difference in the study is that the researchers let the participants have free eye movement instead of being fixated on a fixed point when observing the stimuli on the screen mimicking the way they view everyday events. For the first two trials, no unexpected stimulus entered the screen and so participants were just required to write down how many times the black shapes (first trial) or white shapes (second trial) bounced off the side of the display window. The total number of bounces for the black shapes in this video was nine and the total number of bounces for the white shapes was 10. This video lasted 11 s. After each of these two trials, participants were told to write down how many bounces they had counted on a questionnaire.
On the third trial, participants were shown a slightly longer video of 17 s and were again required to count how many times the black shapes bounced off the sides of the display window. The total number of counts for the black shapes in this video was 14. In this trial, a black cross in similar size to the ‘L’s and ‘T’s entered the screen on the right side of the display window. Rather than the stimulus moving on a random path like the other shapes on the screen, it moved on a horizontal path. Both the shape and motion were different from the other shapes on the screen so was considered a salient stimulus. This trial was referred to as the critical stimulus (CS) condition. Participants were also asked to write down the number of bounces counted after this trial and whether they had seen anything other than the black and white ‘L’s and ‘T’s in the video. If they had noticed the stimuli in question, they were asked to write down the color, shape, and motion (using an arrow to denote the direction) of the stimulus. Those who did not report seeing the cross were presented with the same video trial again and asked once more to count the black shapes.
This fourth trial was the same as the third trial but was referred to as the divided attention (DA) condition as participants had been prompted to expect something additional in this trial. Again, they were asked if they noticed anything that had not been present in the previous trials and to describe it. If participants still had not seen the object they were asked to look at the video and just observe, i. e. , not to count. This was referred to as the full attention (FA) condition. All participants were shown this trial regardless of whether they had noticed the cross in trial threeThe General fluid intelligence measure experiment In this experiment the Raven’s Advanced Progressive Matrices was used as the measure of general fluid intelligence. The test is comprised of 36 items of 3, 9, 3 matrices of black and white geometric patterns in which the bottom right pattern image was missing. Participants were required to select from a choice of eight pattern options below the matrix display which they think best fits with the overall matrix pattern. The Participants’ performance on this measure was taken as the total number of correct solutions.
Despite the limitation imposed by the sample size, the findings do seem to be consistent with the literature reporting an association between attention control processes and gF. This study demonstrates the possible utility of considering how individual differences in gF may influence IB in future research on this topic. Furthermore, through a discussion of the various theoretical frameworks and models relevant to this topic, many interesting and potential avenues of research have been elucidated. The invisible man: Interpersonal goals moderate inattentional blindness to African Americans. In this experiment, the researchers tested for selective inattentional blindness to racial outgroup members. It was reasoned that some racial groups would be perceived as more relevant than others, depending on the interpersonal goal that was active. White participants were primed with interpersonal goals that ranged from psychologically distant (searching for a coworker) to psychologically close (searching for a romantic partner). In the control condition, no goal was explicitly activated. Then, participants watched a video of 2 teams passing a ball and were asked to count the ball passes of one of the teams. In the middle of the video, a Caucasian or an African American man walked through the scene. Participants were then asked to report whether they had seen the interloper. Results revealed that as interpersonal goals became closer to the self, participants were less likely to see the African American man. This research demonstrates a new form of social exclusion based on early attention processes that may perpetuate racial bias.
