The world in which most humans live today is radically different from the one in which the human brain evolved. Technology has enabled an informational environment that exposes individuals to an amount of novel information each day that is orders of magnitude greater than the amount of novel information experienced by the ancestral human. In this challenge, participants will attempt to understand how the mind and brain adapt to the modern informational environment.
The information processing limitations of the human brain are well known; in particular, there appears to be a bottleneck in the decision making process that limits the ability to truly perform multiple cognitive tasks at once. Further, it is now clear that there are serious public health consequences (such as increased automotive accident rates) associated with attempts to multitask. Research has begun to address the consequences of widespread use of electronic devices (known as “media multitasking”), but we do not currently understand its implications (either positive or negative) for important brain functions such as learning, decision making, motivation, and emotion. There is also particular concern regarding the effects of informationally-driven cognition on reflection, contemplativeness, and conceptual thinking.
Of particular interest is the question of whether children who develop within an informationally-rich environment (so-called “digital natives”) differ in fundamental ways from individuals who only experience these environments later in life (“digital immigrants”). However, this question
is extremely difficult to address using controlled experiments, and comparisons between cultures or subgroups that differ in media exposure will necessarily be highly confounded. Despite this difficulty, understanding the effects of informational overload on brain development is critical if we wish to know how the human mind and brain are adapting to the world as it currently exists and whether there are particular approaches that would allow individuals to better adapt to this world.
• How does the brain process the constant barrage of information individuals are exposed to every day? Are the brains of “digital natives” and “digital immigrants” different in the way they process information/expectations, or are these differences cultural?
• What impact does media multitasking have on the ability to synthesize, evaluate, and recall information, especially in stressful situations (e.g. medical emergencies)?
• What kinds of processes/tools can facilitate building of knowledge, conceptual thinking, comptemplativeness, and reflection in a digital age?
• What types of neuroplastic change are occurring in today’s “wired” brains that can be capitalized upon to benefit individuals and society?
• Can one improve or retain cognitive and perceptual abilities by mental or physical exercise, and what are the mechanisms by which such improvements are achieved? How can one take advantage of the capacity of the adult brain to undergo experience dependent plastic change?
• How can we create an environment which will pre-dispose the brain to react in ways we consider ideal?
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Strayer DL, Watson JM, and Drews FA. Cognitive distraction while multitasking in the automobile. In: The psychology of learning and motivation volume 54. Elsevier, Inc. Academic Press: Waltham, MA, 2011.
Because of the popularity of this topic, three groups explored this subject. Please be sure to review each write-up, which immediately follows this one.
IDR TEAM MEMBERS—GROUP A
- Mark S. Cohen, University of California, Los Angeles
- Mark W. Lenox, Texas A&M University
- Andreas Malikopoulos, Oak Ridge National Laboratory
- Rene Marois, Vanderbilt University
- Ulrich Mayr, University of Oregon
- David E. Meyer, University of Michigan
- Jonathan Z. Simon, University of Maryland, College Park
- Clara H. Vaughn, University of Maryland
Clara Vaughn, NAKFI Science Writing Scholar University of Maryland
Introduction: Framing the Task
IDR Team 5A was asked to develop a new approach to assess the differences in cognitive and brain function between the brains of digital natives (individuals born during or after the introduction of current digital technologies) and digital immigrants (those individuals born before the widespread use of digital technologies).
The group first developed a framework through which to conceptualize brain function as it relates to the digital world. The framework accounts for potential contributing factors, including the individual under consideration, the technology with which he is interacting and the environment in which he is operating.
The goal of using such a framework was to optimize an individual’s cognitive and brain function in the face of an information-dense digital world. It took on the acronym “DITF” (d-tf), an abbreviation of OM-EPT DITF, or Optimal Managed Environment-Person-Technology Digital In-Trans-Formation.
Digital “In-Trans-Formation” forms the foundation on which the rest of the concept is based, and was named to characterize the constant flux of digital technologies and information shared across online networks.
In our often transient digital world, the individual must not only deal with a constant flow of information across online channels, but the ebb and flow of new technologies. Optimal management of an individual’s cognitive and brain functions as it relates to technology, then, must be highly adaptive to maximize these functions.
To begin developing a practicable management plan for optimizing brain function, the DITF framework considers three key factors: the person, technology, and environment.
The person: Brain-Mind Index
In the framework, the individual is encompassed in a Brain-Mind Index (BMI) that can be used to categorize individuals into types. This sort of personalized cataloguing would allow for individually tailored management that best maximizes the individual’s ability to cope in an information-dense digital world.
The BMI would be determined by examining an individual’s characteristics including distractibility, working memory, sensation seeking, adaptability and awareness. Other influencing characteristics would be incorporated as the framework is tested and refined.
The technology: Device Complexity Index
One factor directly affecting an individual’s cognitive and brain functions is technology, represented in the framework as the Device Complexity Index (DCI). This includes the number of purposes for which the technology is being used, the stability of digital platforms and the sustainable rate of device change, and would incorporate other factors as researchers refine the framework.
The environment: Environmental Confusion Index
The final node in the Environment-Person-Technology triad is the environment in which an individual using technology is immersed. The team named this the Environmental Confusion Index (ECI) to represent the number of potential complicating factors outside of individual-
computer interactions that may affect those interactions. The physical, social, cultural, and electronic characteristics of one’s surroundings represent factors that might shape an individual’s brain-computer interactions.
Optimal management: Adaptive strategies for digital fluency
Developing means to measure environmental, individual, and technological factors and their interplay would be advantageous through providing baseline data that might allow researchers to design personalized strategies for maximizing brain and cognitive function.
Team members proposed management options from digital literacy training starting in elementary school to computerized multitasking management devices as strategies for achieving this goal. Other strategies are discussed later in this paper. They stressed that any plan to enhance brain and cognitive function and efficiency must be adaptive to be effective in helping users navigate the transient digital world.
Concretizing Concepts: Testable Hypotheses
To narrow the focus of the team’s examination of the brain and cognitive functions of digital natives and digital immigrants, team members developed three testable hypotheses based on the DITF model.
The first proposed that immersion in World 2.0 —the current digital milieu—strengthens processing of salient multi-media cues in sensory cortical sites, leading to stronger bottom-up signals and to disruption of activity in the neural network that supports goal-directed behavior.
This hypothesis follows the line of thought presented by conference speaker Clifford Nass, whose research suggests that high media multitaskers use more brain activity, have greater breadth orientation but lower depth orientation, and tend to avoid deep thinking.
The second hypothesis proposed that chronic multitasking might lead to automation of some brain processes. In other words, high media multitaskers’ brains may adapt to the demands placed on them over time, such that these individuals are able to accomplish tasks more efficiently.
The third hypothesis, based on drug addiction research and existing evidence that online “rewards” and drug-induced rewards manifest in similar parts of the brain, posits that chronic exposure to instant multimedia rewards may lead to reduced sensitivity to such rewards, potentially perma-
Challenges and limitations
All three hypotheses could be tested using functional MRI studies and other brain imaging procedures. Scientists in the group agreed that experiments designed to test the three hypotheses developed during the conference would be fairly easy to carry out, but acknowledged several challenges that would impede progress.
First, measures of outcome and assessment must be developed. How should efficiency of cognitive and brain function be defined and captured? When developing personalized management strategies, how can personality traits, such as distractibility, be measured? These and other questions must be answered before meaningful research can progress.
Another challenge is to establish causal, rather than correlational, relationships between behavioral outcomes and cognitive and brain functions. Current research in the field tends to capture only correlational relationships, posing problems for scientists seeking to design brain function-maximizing management plans based on these observations.
Finally, researchers need long-term longitudinal data to establish trends in brain and cognition as technology users adapt to an information-dense digital world. A member of the IDR team said:
I think that we have a pretty long way to go before submitting a proposal for neuroimaging. The questions that we posed are not of the class, “Where in the brain is X processed?” or “How is multitasking mediated in the brain?” Instead, we ask more longitudinal questions about brain changes with continued behavior. There is an implicit long-term study, or a careful case (of) control design.
Adaptive Strategies: A Model for Maximizing Efficiency
Team members designed questions to approach discussions on digital technologies and brain and cognitive functions, then narrowed their focus to one key question: “Can we develop digital and/or behavioral adaptive strategies to enhance efficiency in World 2.0?”
Such strategies could approach the task of maximizing efficiency in an information-dense digital world either from the human-side (e.g., “technology coaches” that guide individuals in best management practices for digital
multitasking) or technology-side (e.g., programs that monitor behavior and apply strategies for improving the technology user’s efficiency). Many of these proposed strategies presented inherent application problems. Digital coaches would be costly and most individuals would choose to spend their money elsewhere, for example.
One practical solution proposed by the team was a computerized task monitor that would present visible feedback on time usage (See figures 1 and 2). To use the monitor to maximize efficiency while on the computer, an individual would enter work and personal objectives, and the monitor would track desired outcomes against actual time allocations on the computer. To help goal versus actual time-use distributions align, team members proposed pop-ups that warn users when their time spent on e-mail exceeds goals, for example, or even automatic shut-down of “distraction” windows.
IDR Team 5A refined the lens used to assess the cognitive and brain functions of digital natives and digital immigrants and identified some key challenges in carrying out experiments in the field.
The need for better measures of outcome (e.g., How does the brain perform? What is the comparative efficiency of task-management after adaptive strategies are applied?) and of assessment (e.g., What is efficiency? How is it measured?) were apparent during discussions.
After such measures are established, the need to develop causal relationships between behavioral outcomes and cognitive and brain functions is of primary importance. Only by extracting causality from a series of outcomes can scientists develop adaptive strategies for maximizing brain and cognitive function in World 2.0. The team’s goal of maximizing brain function in a transient, information-dense digital world can then be met through cultivating optimizing management strategies, both technology- and individual-driven.
The team presented the several testable hypotheses described above and proposed practical management strategies in its two days of interdisciplinary discourse. Future work stemming from these hypotheses will help scientists better understand the human brain as it relates to the digital world, providing a foundation for developing real-world strategies to better manage the brain in World 2.0.
IDR TEAM MEMBERS—GROUP B
- Lisa Aziz-Zadeh, University of Southern California
- Steven Kotier, Flow Genome Project
- Jessica Luton, University of Georgia
- Narayan B. Mandayam, Rutgers University
- John Devin McAuley, Michigan State University
- Kimberly E Raab-Graham, University of Texas at Austin
- David L. Strayer, University of Utah
- Jason M. Watson, University of Utah
Jessica Luton, NAKFI Science Writing Scholar University of Georgia
IDR Team 5B was asked to assess the differences in the cognitive and brain functions in the brains of digital natives and digital immigrants. While the initial goal was to address these differences, it became apparent throughout the course of the first group discussions that the illusive nature of defining digital natives and digital immigrants made it difficult to answer this question, as we are all destined to be digital immigrants at some point throughout our lives, when the next big technological advance comes along to which we are not yet accustomed. For baby boomers, the new technology was the Internet, social media, iPads, and iPods. For their parents, that technology was the invention of the television or even the radio. And for today’s wired youth, there’s no telling what new technology will emerge that they will one day have to learn to adapt just as their parents did. However, the question remains: What exactly is the consumption of digital media, information overload, and constant multitasking doing to the actual chemistry in our brains? How is this changing the way our brain is working? How does our brain work with this technology? And furthermore, are there critical periods of development in which the use of these technologies might have positive or negative effects on the development of a child’s brain? IDR Team 5B grappled with each of these questions. However, by the end of conference, only one thing remained apparent: we have no idea how digital media are really affecting the human brain. There’s no baseline scientific data that can help answer these critical questions about the impact of technology on brain development. Therefore, a large scale, longitudinal study is necessary.
Media Multitasking and Consequences: A Contemplative Discussion
In thinking about the topic at hand, the team members had a unique set of perspectives that brought about a multidisciplinary discussion of the various consequences that media multitasking and a general consumption of too much media could have on not only social skills, but emotional development and the actual development and inner workings of the human brain. Sociological perspectives, combined with the fields of cognitive neurology and network engineering, led to an enthralling discussion on the topic of media use in the modern world.
In talking about the topic, several assumptions, themes, and questions emerged by the final session. Everyone agreed that we are currently living in an increasingly multitasking world, with a faster pace than was previously thought possible. With that assumption in place, the group agreed that there are inherent limitations to multitasking including personal safety, as is the case when drivers use smartphones in their cars, and the ability to complete a task well when one is constantly interrupted from trying to accomplish the task at hand. The team also agreed that high levels of multitasking may produce impairment in not only completing tasks, but also in development of social and emotional skills. For example, the team discussed the topic of disembodiment. Children develop emotional processing by watching their parents and friends, imitating them and learning to decipher emotions, thereby learning to have empathy for others. The group discussed the implications of what less imitation might mean for emotional development. If children are using text via cell phone and social media, does this mean that they’re not developing the skills necessary to understand emotions in real rather than digital people and furthermore experience empathy for other human beings?
Managing Outcomes: The Case of Cognitive Overload
While team participants agreed that very little scientific data actually shows what can be observed in social science research on this topic, the hope is that a longitudinal study might help create solutions for negative and positive outcomes that are observed through this kind of study. That being said, the group discussed several possible solutions to the idea that we are, in fact, experiencing cognitive overload that is impairing our ability to concentrate on one specific task for a long period of time. The use of a queue, whereby secondary tasks are scheduled so as not to interrupt a primary
task, is one possible solution. Studying the rhythmic patterns of activity of individuals might allow further insight. If, for instance, tasks are delayed to interrupt at only specific time intervals, say every three minutes, rather than at random times, one might be able to better be more productive. Further solutions might take into account the context of an individual. For example, when a driver is in the car, his or her cell phone could automatically go into a “busy” mode. Those calling would be asked to call back because the driver is busy. In addition, assessing bio or neuro feedback patterns could also help schedule tasks for more productivity. An application that would give the user cues when they’re getting off task might also be helpful in getting people back on task.
Beyond those possibilities that are mainly device oriented, one area was discussed as being a possible solution for cognitive overload—training. Because the prefrontal cortex requires more energy to process activities that are not novel, the idea of outsourcing or offloading activities to other parts of the brain via training was suggested. For instance, if one is practiced in specific tasks, those tasks no longer require as much energy for the brain to process and the prefrontal cortex is then left to do other tasks.
For IDR Team 5B, the question remained: How can multitasking performance be optimized without enabling or further contributing to impairments? The team concluded that answering any of these questions is a difficult and almost impossible task without having scientific data from a well-funded, longitudinal study that assessed the differences in brains of high multimedia users and low multimedia users. Using the various disciplines, the group constructed a study format that would allow for this type of assessment. Most important, the team wants to know whether there is a critical period of development in which high multimedia use might inhibit normal cognitive and brain development. The group’s proposed study, therefore, focused on various factors including functional differences, shifts in intrinsic oscillation frequencies, early EEG markers and a task battery that would help assess this question from various perspectives.
Constructing a Study: Assessing Cognitive, Social, and Emotional Brain Development
Given the need for a study that would show the actual physiological effects of media use on the brain and therefore help better assess social and emotional effects, IDR Team 5B went about constructing a large-scale cross-sectional longitudinal study that would incorporate a whole range
of assessments to help answer some of these difficult questions. While the results obviously wouldn’t be available for some time, the implications of initial results could be interpreted as each new cohort advanced in the study. Additionally, the design of such a study, using a new cohort every two years or so, would allow the previous cohort to serve as the control group for the new group. A study of this design, despite being long term and likely expensive, would also allow researchers to study the effects of new technologies as they emerge over the course of the next decade or longer.
In assessing the topic at hand, the team had to come to some sort of consensus on how the terms digital native and digital immigrant might be defined. It didn’t take long to figure out that the term is not ideal. Perhaps, the team suggested, media use is on a continuum and a whole range of questions need to assess the type of media being used by different populations, as well as the frequency of media use within the population. Social media, music, Internet, E-mail, talking on the telephone, using a cell phone application, texting, games, sensors like Fitbit, digital TV and video, video chatting, virtual reality, and new emerging technologies yet unveiled were all named as possible categories of media use that might be used as a basis for evaluating media use among today’s population.
Beyond looking at the types of media use, the team also sought out a way to assess just how these different types of media are being used or not used by each new cohort. The team constructed a list of analog interactions, such as face-to-face meetings, books and other print materials, and recreational activities that might assess the ratio of digital media use to physical world interactions.
The team also chose not only to look at the types of media, but also the amount of time spent using each media, how many devices are being used simultaneously, what proportion of one’s life individuals have been using specific media, when they began their media use, the ratio of digital and face-to-face interactions and the attitudes towards different types of media by study participants.
Defining the (New) Normal
To really provide a broad-based study to help answer some of these questions, the team proposed a hypothetical study that would not only provide a behavioral assessment of study participants, but also investigate physiological measures that might provide a base of knowledge for all disciplines to assess the potential positive and negative effects of high digital
The team proposed a study of behavioral characteristics using a whole range of resources including, but not limited to the NASA Task Load Index, an assessment of executive control; testing emotional recognition, processing and management; delayed gratification, timing of interruptions, and implicit imitation; a baseline personality reading; creativity measures, social processing, empathy measures and human vs. machine identification. Beyond these measures, the study would also include a series of physiological measures that might help nail down definitive data on brain development and multimedia use. The team agreed that such a study should look at EEG and MEG data, with specific attention to event related potentials and frequency and time domain. In addition, the study should also use MRI and fMRI data to assess structural brain development and changes, the default resting activity network in the brain, as well as task-related functional connectivity. Furthermore, assessing autonomic responses through ANS, as well as levels of hormones, such as cortisol and adrenaline, might reveal more about the chemistry of the brain when users engage in multimedia use.
IDR TEAM MEMBERS—GROUP C
- David Badre, Brown University
- Ann E. Christiano, University of Florida
- Art Kramer, University of Illinois
- Annie Lang, Indiana University
- Taosheng Liu, Michigan State University
- Oded Nov, Polytechnic Institute of New York University
- Karin A. Remington, Arjuna Solutions
- Rina Shaikh-Lesko, University of California, Santa Cruz
Rina Shaikh-Lesko, NAKFI Science Writing Scholar University of California, Santa Cruz
IDR Team 5C was asked to develop a new approach to assess the differences in cognitive brain function between the brains of “digital natives” who have been exposed to the Internet and other digital media since early child-
hood and the brains of “digital immigrants” who were first exposed to digital technologies later in life. There is evidence that digital natives are more likely to be heavy media users, and more likely to be media multitaskers.
Clifford Nass of Stanford University, in his keynote address, provided evidence that multitasking is a problem that is on the rise among all age groups, but especially teenagers and college-age students, because there are more and more media channels vying for our time. The number of distracting tasks has risen as the number of digital devices has increased. TV, radio, and Internet are now joined by smartphones, tablets, and social media.
There is recent evidence that the vast majority of people—97.5 percent by one measure—are not effective multitaskers. There is also further evidence to suggest that the people who rate themselves as good multitaskers are the worst at it.
However, to IDR Team 5C, the distinction of digital natives and immigrants was an arbitrary one because today’s digital natives will become tomorrow’s digital immigrants. Heavy digital engagement is simply part of the milieu in which we find ourselves, regardless of whether we are digital natives or immigrants or whether we are heavy or light media users. The challenge, now that we are becoming aware of the potential costs of media overload, is how to manage the competing priorities in an effective way.
Structuring the Environment for Productivity
IDR Team 5C team members think there is a qualitative difference between what the team called “good multitasking” and “bad multitasking.” The team defined good multitasking as two or more tasks completed with the same accuracy more quickly and more enjoyably than both (or all) sequentially. An example is when a person downloads audio book chapters onto an iPhone to take with her on a walk to the grocery store. By adding the task of listening to the podcast to walking to the store, and by adding getting exercise by walking instead of driving to the store, three tasks are completed sooner and more enjoyably than any of them alone. “Bad multitasking” is when doing two tasks together takes longer than doing them sequentially and when the process is stressful and unpleasant.
One challenge is that current models of multitasking efficiency rely heavily on cognitive thinking; the dimension of emotion (e.g., enjoyment, pride, stress, fear) is often missing from assessments, as is creative thought. Members of IDR Team 5C speculated there is even a trade-off whereby if the quality of work doesn’t suffer, some people are willing to take more
In order to create more opportunities for people to do good multitasking, it is necessary to better understand how the dimensions of pleasure and creativity impact our current understanding of multitasking behavior.
Whistle While You Work
IDR Team 5C proposed taking advantage of technology to track how productivity is affected by the rising number of distractions, digital or otherwise. They sketched basic functions of an app-based study to track productivity and satisfaction with a given app-mediated work schedule. The app is called “Whistle” from the song, “Whistle while you work,” reflecting the team’s emphasis that the tool provide more than mere time-management tools, but instead, tools that improve happiness and creativity along with productivity.
The app pulls from neuroscience and cognitive science to build an algorithm that provides a schedule for a productive day. For users who download it, the app functions as a life structuring coach, corralling the large number of tasks, distractions, and competing priorities. One team member described it as FitBit for productivity, after the popular, compact smartphone-based health and fitness monitoring tool.
The app would take the information provided by the user and combine tasks that are naturally complementary: listening to classical music while writing versus listening to podcasts while filing. The app can also take into account whether there are times of day that are more productive for certain kinds of tasks. It would be capable of linking a user’s calendar, file storage center (i.e., dropbox, hard drives, or cloud storage). The app would also be capable of learning about users with every completed task.
Tapping into the mobile phone app user audience
One of IDR Team 5C members had a recent relevant example of developing, with the aid of a game designer, a free iPhone game app called BrainBaseline. It has more entertaining and engaging versions of cognitive assessment tests used in laboratory settings. The game was subsequently offered on the iTunes store to the general public where within months thousands of users downloaded the game, played it and uploaded their scores, which researchers then were able to analyze.
Whistle is essentially a “smart assistant” that provides insights into how an individual user works best and eventually, as data is aggregated, can be applied to larger groups. That larger group data can be accessed by researchers as a rich mine of information on how people function and even thrive in a distraction-rich, resource-poor environment.
Two ways to use The Whistle, two ways to work
There are two distinct ways that the team identified that users could interact with The Whistle app. The first is during the initial set-up—a new user would be presented with a detailed questionnaire which would ask about priorities, tasks, what is enjoyable about those tasks, what are the most tempting distractions and any other relevant information the user wants to add that can all be plugged into an algorithm that would work with a user’s calendar, music library, and file storage system to create a daily schedule that is uniquely optimized for that individual.
An alternative approach is for the app to log what people do throughout the day. They could assign a 5-star scale rating on how good or bad they feel about the day in terms of successful task completion and enjoyment. Once there is bank of user data from which to extrapolate, researchers could offer users a four- or five-star day from another user as a way to “try on” new ways of working.
Although researchers have growing evidence about the way the brain reacts to multitasking challenges in an experimental environment that is on a time-scale of seconds to minutes, there is not much evidence of how
The Whistle app will begin to address these gaps. As the repository of user data grows, researchers will get a finer and finer grain picture of user priorities and productivity. It will become a catalog of how users want to allocate their time and the way they actually do. Understanding the factors underlying success task management has several potential long-term benefits. Companies could see cost savings if their workers are using a product like The Whistle. There would likely be less stress-related absenteeism and attrition if workers were productively and creatively engaged, which in turn could lead to lowered health insurance costs.
It is likely that the number of digital distraction will continue to grow. Understanding how humans manage multiple tasks is a relatively young field, but it also represents an opportunity to apply our knowledge of computer science, cognitive science, and neuroscience to understanding a problem that is unique to our digital age.