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September 1 - October 17, 2023
Our proficiency in setting goals is mediated by a collection of cognitive abilities that are widely known as “executive functions,” a set of skills that include evaluation, decision making, organization, and planning. But goal setting is only half the battle. We also need specialized processes to enact all those lofty goals. Our ability to effectively carry out our goals is dependent on an assemblage of related cognitive abilities that we will refer to throughout this book as “cognitive control.” This includes attention, working memory, and goal management.
The Information Age has emerged on the heels of modern technological breakthroughs in computers, media, and communication. This latest stage in human history may have been sparked by the digital revolution, but the rise of personal computers, the Internet, smartphones, and tablets is really only the surface. The true core of the change to our mental landscape is that we are experiencing an elevation of information itself to the level of the ultimate commodity. This has fueled an ever-expanding explosion in the variety and accessibility of technologies with enticing sounds, compelling visuals,
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These internal, goal-directed, top-down influences occur at the same time as external, stimulus-driven, bottom-up influences to modulate our perceptions and actions. The bottom-up forces are the same as they have always have been: novelty and saliency.
It is important to recognize that neural networks are not nebulous webs of connections that are engaged equivalently during all mental processes.
The fact that ignoring is an active process is critical to understanding the Distracted Mind because it emphasizes that it takes resources to filter out what is irrelevant.
Suppression yields higher-quality representations of relevant information by decreasing the noise and letting the signal shine. It is an essential ingredient of selective attention. Although it may seem counterintuitive, we now appreciate that focusing and ignoring are not two sides of the same coin. In other words, it is not necessarily true that when you focus more on something, you automatically ignore everything else better. We have shown in our lab that different prefrontal cortex networks are engaged when we focus compared to when we ignore the same thing. In other words, they are two
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If one or more tasks are capable of being automated as reflexes, then they can easily be engaged simultaneously with another task without much consequence. This is the classic “walking while chewing gum.” Although the act of walking requires selective attention, the act of chewing under most circumstances does not demand cognitive control because it is performed reflexively. Given this, such an activity may not even qualify as an example of multitasking, since a reflexive action is not really a task.
Even though we gave no instruction to participants to switch between these two tasks, we see that is actually what is happening in their brain. They do not maintain the memory network at the same level when the selective attention network is engaged. Rather, they dynamically switch between these two cognitive control networks. The results of our study are consistent with many other studies that have shown when we simultaneously pursue multiple goals that compete for cognitive control resources, our brains switch between tasks—they do not parallel process.35 So, while the behavioral goals may
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our working memory capacity is quite limited. Individual differences in capacity have been shown to be associated with higher-order cognitive abilities related to real-world activities, such as reading comprehension, learning, and reasoning, as well as estimates of intelligence.19 Individuals who have a larger working memory capacity tend to do better on assessments of these skills and measures of general fluid intelligence.
distractibility is caused by an inefficient filter that results in excessive processing of irrelevant information in the visual cortex, whereas multitasking impairments are caused by a failure to effectively switch between networks involved in performing two tasks. In common between them are alterations in prefrontal cortical networks, both functional and structural, which are at the heart of their goal-interference issues.
Starting with selectivity, children and adults who are diagnosed with ADHD are more susceptible to be negatively influenced by distractors than their age-matched peers.43 But those diagnosed with ADHD are not alone in experiencing this burden. On tests of distractibility, all the clinical conditions mentioned in the preceding paragraph exhibit marked impairments. Consider the Stroop test, a classical assessment of distraction where you see words that are written in colored ink and have to say out loud the name of the color, not the name of the written word. For example, if you see the word RED
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In 1970, prior to the technological revolution that resulted in the information age in which we now all reside, Alvin Toffler, described by some as “the world’s most famous futurologist,” penned his classic book Future Shock, which warned that we were entering an era of “too much change in too short a time.”1 Following up a decade later with The Third Wave, Toffler further described this as a process of succeeding waves of technological innovation, each of which begins, reaches a peak, and then starts to decline as the next wave performs the same process.2 Toffler’s first wave—spanning three
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A recent study followed a group of young adults and a group of older adults who wore biometric belts with embedded eyeglass cameras for more than 300 hours of leisure time.14 While the younger adults switched from task to task twenty-seven times per hour—once every two minutes—the older adults were not all that great at maintaining their attention either, switching tasks seventeen times per hour, or once every three to four minutes. Former Microsoft executive Linda Stone dubbed this constant multitasking “continuous partial attention.”15 As we will discuss later in this book, frequent task
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One interesting aspect of this penchant for combining tasks is that we seem to have lost the ability to single task.
Finally, a study of more than 770 college students discovered that students who used more interfering technology in the classroom also tended to engage in more high-risk behaviors, including using alcohol, cigarettes, marijuana, and other drugs, drunk driving, fighting, and having multiple sex partners. Overall, it appears that college students who use inessential technology either during class sessions or while studying face difficulties on both an academic and personal level.
The researchers interviewed more than 150 students who walked through the square and noted if they were walking alone or with someone else and if they were using a cell phone or listening to music with ear buds. When asked if they saw anything unusual, only 8 percent of cell phone users reported that they saw the clown. This was compared with one in three students walking alone without technology or listening to music wearing ear buds and more than half of he students who were walking in pairs without using technology. When asked directly if they saw a clown, still only one in four of the
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Under these conditions, switching would take place even if there were remaining tasty information treats to be consumed at the original source. In other words, internal factors of boredom and anxiety influence the perceived benefits of being in a patch, even if only subconsciously, to offset the value of consuming important information in a sustained manner.
Quanyify value. What one interprets to be valuable does not need to be valuable to someone else. What the proctor discerns as vluable isn't necessarily valuable to the subject.
we propose that these influences of modern media and high-tech—increased rate of accumulation of anxiety and boredom, and increased accessibility of information—have driven the behaviors in humans described throughout Part II of this book. This in turn has exacerbated the collision between our lofty goals and our cognitive control limitations, as described in Part I, to result in the many negative consequences in our lives that we have been discussing. Let’s examine in more detail these influences on both sides of the MVT model.
Where are the other possibilities? Its easy to conclude one thing when you only present the supportive data. Where are the references to altetnative explanations like technology as escapism, active dissociation on account of anxiety or depression? Is it not possible technology use is the symptom rather than the cause?
Yeykelis found that, on average, students spent only sixty-five seconds on one screen before switching to another, but even more surprising, half of the switches occurred within nineteen seconds.4 That means that these Stanford University students were switching screens roughly five times a minute.
Boredom, as a field of psychological study, has not received much attention, perhaps because it is difficult to define accurately what it means to be bored. For example, John Eastwood and his colleagues at York University suggest in their work that boredom is “the aversive experience of wanting, but being unable, to engage in satisfying activity.”5 Eastwood and his colleagues go further in clarifying boredom as an aversive state that occurs when we • are not able to successfully engage attention with internal (e.g., thoughts or feelings) or external (e.g., environmental stimuli) information
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The three top reasons: while alone (70 percent), when bored or killing time (68 percent), or while waiting for something or someone (61 percent). All of these situations represent the possibility that the motivation for using an app is having free time and not being stimulated or not having something to do. A similar study from the UK reported that 52 percent of 1,350 adult smartphone users and 62 percent of those between eighteen and thirty reported that they prefer to use their device rather than just sit and think.
Rapid media multitasking itself, with such a high novelty load that induces frequent reward feedback, may also influence the boredom curve. In other words, this may all be cyclical: boredom drives frequent switching to new tasks → rapidly induced rewards → increased rate of boredom in nonstimulating information sources → rapid flattening of resource intake curve → quicker switch times → and so on.
This book, for instance, went from engaging in the first section, to boring. Yet still I fight to engague with the topic despite violation to my ability to willfully suspend disbelief.

