"Deep Work" in a Distracted World

Abstract: In a series of blog posts nearly a decade ago, author and computer science professor Cal Newport coined the term “deep work.”[1] In 2016, these posts served as the basis of a book by that same title.? One of the studies cited by Newport came from the work of psychologist Mihaly Csikszentmihalyi, in which subjects were provided pagers who would then receive random alerts throughout their day. The study’s design called for the subjects to write down how they were feeling at the exact moment they received those alerts. While today, this study might seem almost primitive, it proved highly repeatable and informative. The research revealed that the very best moments of the subjects' lives came when they were stretching themselves mentally, physically, or emotionally, in a voluntary pursuit. The term coined to describe this state was called “flow,” and it serves as the basis for this examination of where distraction, flow, and meaningful work currently intersect.

Deep Work Is Valuable, So How Do We Get There?

The first chapter of Newport’s 2016 work was devoted to bolstering the idea that deep work is valuable. In many respects, this seemed strange that he would feel compelled to make such a seemingly obvious assertion, but the chapter is actually more about Newport’s looking ahead to a future where “intelligent machines” and remote work are the norm. The “digital division” that Newport anticipated is obvious to almost anyone paying attention today.

Accepting the assertion that deep work is valuable or meaningful, it seems appropriate to explore how one does this today, in an environment where we seem to be living and operating in a world of either “distraction by design” or “distraction by duress.”? Where is “flow” to be found when so many forces seem to be working against such a state?

In general, the characteristics of being in a flow state can usually be broken down into something like the following:

1. Full task engagement: Flow is marked by the complete immersion in the task at hand, with minimal self-directed thoughts.
2. Strong intentional focus: By its very nature, flow inhibits distractions and irrelevant thoughts, leading to a merging of action and awareness. ?
3. Clear goals and progress: The activity typically has well-defined goals and provides a sense of progress towards those goals, be they academic, professional, or personal.??
4. Immediate feedback: The task should allow for immediate feedback on performance, allowing for adjustments and improvements.?
5. Balance between challenge and skill: There needs to be a good match between the perceived difficulty of the task and the individual's perceived skills.

Of these five characteristics mentioned, it is “Immediate Feedback” that is perceived as the least achievable within the realm of knowledge work. Immediate feedback is sometimes why sports (hitting a ball properly or beating a personal record) are more associated with flow states than other, more mental endeavors.?

The ideas of “challenge” and “skill” are also both slightly more conducive to areas outside of academia or knowledge work. The mastering of a musical instrument often comes with a reasonable challenge that eventually becomes an acquired skill. This “stair step” framework found in certain domains isn’t always present when it comes to academia, business, or research.?

That two out of the five characteristics of Csikszentmihalyi’s flow state are not typically found within the realm of knowledge work could lead one to conclude that “flow” is not possible here; that while the high school quarterback might get immediate feedback on his practice performance from a coach, the high school debate student isn’t likely to have access to a similar feedback loop. While making such an assertion might seem logical, it would be erroneous, or at the very least, lacking in creativity.

Harvard professor Terrance Capellini, in explaining best practices within his biology research course, advises other teachers and professors on the importance of “using multiple types of assessments.”[2] Capellini mentions that exams and quizzes are the central source of feedback in the first half of the course so students are prepared for the final project. The final project according to Capellini is treated like a conference talk, and by its very nature, demands that students can use their research and apply their efforts to real world questions. Some educators refer to this method as “scaffolding,” and its building block nature of learning, culminating in the conference, is something close to the flow state that athletes, musicians, and other high performers often speak of achieving when they’re “in the zone.”

Whether on an athletic practice field or in a university classroom, when it comes to “flow,” the common theme is “intentionality,” and it is here that one would be wise to understand how social media and big tech are ultimately not in the business of fostering your personal or professional intentionality. Anyone who has ever been on Amazon's app and been drawn to items that were “Inspired by your shopping trends,” or “Deals based on your past purchases,” has been exposed to this battle between the real reason you went on to Amazon, and the ways you are being enticed to wander and browse. Yes, you might need some of the things that are being suggested to you, but on the whole, this is an example of your intentions being undermined by an outside agent.

Less is More

In a study by researchers from the University of Virginia, the concept of “additive” versus “subtractive” thinking was explored across a variety of experiments. In short, the study focused on why we as humans seem inclined to add, rather than to subtract when it comes to problem solving. The study included having subjects optimize certain Lego building projects, with researchers paying particular attention to when participants added unnecessary “bricks” to the solution versus when participants subtracted bricks.?

According to the study’s co-author Benjamin Converse, “the conclusion from our studies is that when people are trying to change something, their habit is to ask, ‘What can I add?’ rather than to ask, ‘What can I subtract or add?’ They are fully capable of thinking of subtractions, they just tend to think of adding first – and, often, they choose an additive solution before they even consider a subtractive one.”[3]

The UVA study highlights a reality that social media, search engines, and e-commerce sites know only too well: when it comes to information or content, humans seemingly can never have enough. Even when we presumably know better, we become hoarders, rather than sifters. We often think in terms of volume rather than quality. As information, raw data, insights, and opinions continue to overwhelm us, it is becoming obvious that one’s ability to curate one’s sources, to place context around those sources, and to draw insights from those sources is where knowledge resides, not in one’s ability to simply gather.

While the distinction between “gathering” and actually making meaning of information might appear to simply be the domain of the data scientist, it seems ever more apparent that anyone seeking to excel in a data driven society must take ownership of their own data and information “curation.” From becoming immune to misinformation to simply being capable of seeking to understand a contrary opinion, managing your information intake is a skill worth mastering.

Knowledge vs Creativity or Knowledge and Creativity?

It can be tempting to think that memorizing dates or facts is unimportant and unfair to students, employees, or anyone on the receiving end of information. Armed with an Internet connection, anything is discoverable, so knowing all the United States presidents in order, or the names of all the moons orbiting Jupiter almost seems like wasted brain power.

To be clear, knowing these facts will not get anyone a job, a promotion, or into law school, but one’s ability to know things, to remember things, is critical to one’s ability to connect things, and ultimately, to create things.?

Daniel Coyle is a researcher and author who has devoted a great deal of effort to discover what makes high performing organizations and high performing individuals excel. His first work, The Talent Code took him all over the globe studying tennis players, Olympic divers, cross country skiers, and musicians. In something of a condensed follow up to this first book, he wrote The Little Book of Talent, where amongst other things, he discusses the “sweet spot” as it pertains to acquiring a new skill.

According to Coyle, “locating your sweet spot requires some creativity. For instance, some golfers work on their swings underwater (which slows them down, so they can sense and fix their mistakes). Some musicians play songs backwards (which helps them better sense the relationship between the notes). These are different methods, but the underlying pattern is the same: seek out ways to stretch yourself.”[4]

This idea of creativity leading to a stretching of one’s limits might feel removed from the realm of research or academic pursuits, but it need not be. From whiteboards in a classroom, to mind mapping software on a laptop, the acquisition of a new skill or the novel application of an old idea has always been about the interplay of knowledge and novelty. It is this human ability to do something creative with one’s knowledge that will eventually give power to AI, not AI’s perceived power to turn us all into digital Picassos. ??

Conclusion

Terms like flow, sweet spot, and creativity do not appear at first glance to be part of the lexicon normally attributed to the realm of knowledge work or academic research. They should, and they eventually will, for those who understand what genuine value is likely to look like in an AI infused world.?

Taken together, each of the books or studies included in this discussion all lend credence to the idea that the future of work, and therefore the future of value creation on the part of most individuals within the digital economy, will rely heavily upon one’s ability to have developed a few critical skills:

1. The ability to achieve “flow” state performance based on a keen understanding of feedback loops, and a willingness to stretch one’s cognitive abilities. In the past, this sort of approach has been relegated to the realm of athletics, the arts, or some endeavor where the mental and the physical must be aligned. In the future, “flow” will be demanded for knowledge workers for the simple reality that anything less is likely to be automated, or at the very least, outsourced.
2. The ability to curate incoming data, regardless of the source, with an increasing appreciation for the idea that oftentimes, especially with data, less is more. This is not an excuse to ignore one’s surroundings, or to insulate one from uncomfortable opinions. Rather, it is simply an acknowledgement that Large Language Models demand, crave, and thirst for data.? Any data. Much of it is noise. Discerning the signal will be a superpower.
3. The ability to creatively apply data to real world problems will separate peak performers from those relegated to the mundane tasks of an economy that will increasingly demand highly differentiated and personalized products and services. ??

It is hoped that there is a perceived thread of optimism that runs through this discussion. Yes, there are challenges that await us all in this next stage of tech infused growth and change, but there’s huge upside for those who are able to confidently step into the arena, armed with new skills and fully capable of handling these new challenges.

For more occasional insights, follow Sooth.fyi

[1] Newport, C. (2016). Deep Work: Rules for Focused Success in a Distracted World. Grand Central Publishing. https://play.google.com/store/books/details?id=4QTzCAAAQBAJ&source=gbs_api

[2] Empowering students to develop research skills – Harvard Initiative for Learning and Teaching (HILT). (2021, February 8). Harvard University. https://hilt.harvard.edu/ideas-and-tools/into-practice-items/empowering-students-to-develop-research-skills/

[3] When It Comes to Problem-Solving, New UVA Study Finds That Less Is More | UVA Today. (2021, April 7). University of Virginia. https://news.virginia.edu/content/when-it-comes-problem-solving-new-uva-study-finds-less-more

[4] Coyle, D. (2012). The Little Book of Talent: 52 Tips for Improving Your Skills. Random House Publishing Group. https://play.google.com/store/books/details?id=PxV8_q-9HnUC&source=gbs_api