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Is B.S. One of the Greatest Barriers to Learning?

One of my biggest pet peeves is being in meetings or venues where everyone is acting like they have all the answers—whether because they believe they do or they are performing like they do. This is particularly true, from my experience, in consulting contexts, where there is a high performative aspect to presenting and speaking. In Organizational Learning and Performance, I draw upon research about having a performance-prove orientation, where you’re mostly concerned about appearing as if you have all the answers. This is in contrast to a learning orientation where you are willing to ask questions and probe what you know and don’t know.

To illustrate a performance-prove orientation, I often use a quote from Steve Levitt, of Freakonomics fame:

“What I’ve found in business is that almost no one will ever admit to not knowing the answer to a question. So even if they absolutely have no idea what the answer is, if it’s within their realm of expertise, faking is just an important part. I really have come to believe teaching MBAs that one of the most important things you learn as an MBA is how to pretend you know the answer to any question even though you have absolutely no idea what you’re talking about. And I’ve found it’s really one of the most destructive factors in business—is that everyone masquerades like they know the answer and no one will ever admit they don’t know the answer, and it makes it almost impossible to learn.”

BUT, to my surprise, I recently came across research that more precisely diagnoses the issue: “pseudo-profound bullshit.”

I hadn’t been aware that B.S. had a respectable line of research for all these years.

As Pennycook and colleagues (2015) describe in the opening to their article in Judgment and Decision Making, “the philosopher Frankfurt (2005) defines bullshit as something that is designed to impress but that was constructed absent direct concern for the truth” (p. 549).

The authors continue with several statements, such as:

  • “Hidden meaning transforms unparalleled abstract beauty.”

As the authors say, “Although this statement may seem to convey some sort of potentially profound meaning, it is merely a collection of buzzwords put together randomly in a sentence that retains syntactic structure” (p. 549).

In contrast to Frankfurt, they argue that “pseudo-profound bullshit betrays a concern for verisimilitude or truthiness.” And their prefix of profound “reveals an important defining characteristic of bullshit (in general): that it attempts to impress rather than to inform; to be engaging rather than instructive” (p. 550).

To research the topic, Pennycook and colleagues created a B.S. Receptivity Scale which lists ten meaningless statements such as:

  • “The future explains irrational facts.”
  • “Consciousness consists of frequencies of quantum energy. ‘Quantum’ means an unveiling of the unrestricted.”

Participants rated how profound these statements were on a scale of 1-5. They found that participants who scored higher on the Cognitive Reflection Test (a measure of one’s willingness to question one’s intuitive responses), were more likely to see B.S. for what it is.

In more recent research, a Bullshitting Frequency Scale was developed to measure the act of bullshitting rather than your receptivity to it (Littrell, Risko, & Fugelsang, 2021). The researchers, citing the philosopher Gerald Cohen (2013), describe how “the aim of some bullshitters is to impress using discourse constructed with ‘unclarifiable unclarity’; that is, relying on vacuous, confusing buzzwords which obscure that the statements, while superficially impressive, contain no discernible meaning” (p. 249). In their research, Littrell et al. (2021) found that bullshitting frequency is negatively correlated with honesty, sincerity, and self-worth.

Unfortunately, B.S. is all too common in organizations where a desire to impress can lead us to speak in ways that obscure a deeper understanding of an issue. This combines with an understandable desire among listeners to not ask questions for the risk of appearing to be the only one that doesn’t get it. The result is one of the greatest barriers to learning in organizations.

There aren’t simple answers to counteract B.S., but you can start by asking questions to help understand issues (you might uncover others have similar questions). If you are in a position to set norms for your team or organization, you can highlight behaviors such a being candid or intellectually humble (being willing to admit what you know and don’t know). Or you can more aggressively aim to “forgo B.S.” in a more forthright attempt to learn and address issues you are facing.

For the moment, at least, take heart that there is a group of dedicated researchers shedding light on the opaque phenomenon of bullshit.

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Cohen, G. A. (2013). Complete bullshit. In M. Otsuka (Ed.), Finding oneself in the other (pp. 94–114). Princeton University Press.

Frankfurt, H. G. (2005). On bullshit. Princeton University Press.

Pennycook, G., Cheyne, J. A., Barr, N., Koehler, D. J., & Fugelsang, J. A. (2015). On the reception and detection of pseudo-profound bullshit. Judgment and Decision Making, 10(6), 549-563.

Levitt, S. (2012, January 5). Why is “I don’t know” so hard to say? Freakonomics Radio [Audio Podcast] Retrieved from

Littrell, S., Risko, E. F., & Fugelsang, J. A. (2021). The bullshitting frequency scale: Development and psychometric properties. British Journal of Social Psychology, 60, 248-270.

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How to Overcome Conformity by “Getting at the Truth”

As is human nature, if we know the preferences of a group leader, we’ll tend to conform to that preference. If you’re a group leader or care about making better decisions, that’s a problem. However, one study found a way around this, which was to promote the goal of “getting at the truth” (versus “getting along”) and to promote individual accountability for decision-quality (rather than accountability diffused throughout a group) (Quinn & Schlenker, 2002).

For example, imagine yourself in a situation where you are a middle manager. Perhaps a senior executive has indicated his or her preferred course of action. You are aware of his or her preference and the desire to conform will be strong. What can counteract this pressure? The social norm to get an accurate picture of reality, and if you have to publicly explain your position. As you imagine this future meeting, you don’t want to say you came to your viewpoint because “the senior executive said so.” Instead, if you have to individually explain and justify your viewpoint, and there is a social norm to “get at the truth,” you have a better chance to overcome the pervasive conformity pressure in most organizations.

In the research study that tested this hypothesis, the researchers had individuals primed for either “getting along” or “getting at the truth” by reading different scenarios (Quinn & Schlenker, 2002). How do you prime individuals for “getting at the truth” or “getting along?” They would read a collection of scenarios that either described a search for truth or when your behavior needed to be tailored to the situation (Chen, Schechter, & Chaiken, 1996).

For example, in the “getting at the truth” scenario, you would read about a reporter trying to get the facts of a story. For “getting along,” participants read a scenario about being on a blind date set up by a close friend but quickly realizing there was little attraction. After reading each of the scenarios, participants were asked what actions they would take in that scenario. For example, if they read the priming scenario about being a reporter, an individual might suggest going to the library to look up facts or speaking with an expert.

After reading the priming scenarios, participants then read a case study and had to choose between two different courses of action. In this case, how to allocate a marketing budget between an American and European lager. If participants had been primed with the “getting at the truth” scenario, they were more likely to choose the option that provided an “objectively better return on marketing investment.” However, if they were primed with the “getting along” scenario, they were more influenced by the choice of their discussion partner, regardless of whether it led to an objectively better return on marketing investment.

In addition, the positive effect of being primed to “get at the truth” was most pronounced when participants had to “explain and justify” their decision (i.e. being held accountable). In the case of the experiment, it was having your decision written on a “decision sheet” and shared with a partner. Accountability has many connotations, but accountability can be having to publicly explain your reasoning for a decision, perhaps in a meeting (Lerner & Tetlock, 1999).

As the researchers conclude:

“Accountability to an audience whose preferences are known does not invariably doom people to subpar decisions that are biased by conformity pressures. If people are focused on the goal of making accurate decisions when they are accountable, the quality of their decision making increases as compared to when people are not accountable or to when people have the goal of getting along” (Quinn & Schlenker, 2002, p. 481-482).

These results are a hopeful antidote to the conformity pressures faced in most organizations (and found in most social psychology experiments).

So how do you foster a motivation to “get at the truth” in an organization? At Bridgewater Associates, one of the world’s largest hedge funds, there is a constant refrain and insistence that employees think for themselves and ask “Is it true?” (Dalio, 2017). Likewise, when I spoke with a Chief Investment Officer at a different hedge fund, he set up a monthly meeting with his direct report who would have to answer the question, “What is something you don’t think I want to hear, but you think is true?” Over time, this helped promote the notion of “getting at the truth” over “getting along,” and there was accountability because the CIO’s direct report knew that at each monthly meeting, he’d have to state his viewpoint.

Thus, while conformity is ever-present, if we set up the norm for “getting at the truth,” and ask individuals to explain and justify their viewpoints, we can increase viewpoint diversity in the pursuit of making better decisions.

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Chen, S., Schechter, D., & Chaiken, S. (1996). Getting at the truth or getting along: Accuracy- versus impression-motivated heuristic and systematic processing. Journal of Personality and Social Psychology, 71(2), 262-275.

Dalio, R. (2017). Principles: Life and work. Simon & Schuster.

Lerner, J. S., & Tetlock, P. E. (1999). Accounting for the effects of accountability. Psychological Bulletin, 125(2), 255-275.

Quinn, A., & Schlenker, B. R. (2002). Can accountability produce independence? Goals as determinants of the impact of accountability on conformity. Personality and Social Psychology Bulletin, 28(4), 472-483.

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Slow Hunches, Curiosity, and Innovative Ideas

To be following a slow hunch is to be at the fuzzy edge of our current knowledge. It is to be actively putting vague intuitions into words and building a conceptual map at the edges of understanding. These slow hunches help explain the experience of being at the edge of scientific discovery, as explained by the writer Steven Johnson in his book Where Good Ideas Come From. Johnson compares one-off ideas with innovative ideas that incubate and develop over a longer period of time. As he states:

“Most hunches that turn into important innovations unfold over much longer time frames. They start with a vague, hard-to-describe sense that there’s an interesting solution to a problem that hasn’t yet been proposed, and they linger in the shadows of the mind, sometimes for decades, assembling new connections and gaining strength….But that long incubation period is also their strength, because true insights require you to think something that no one has thought before in quite the same way” (Johnson, 2010 p. 77).

Scientific discovery, by and large, illustrates how a “hunch” (or more formally conceived as a “hypothesis”) guides the pursuit of understanding. Over time, hunches are tested and either gather support or are discarded. In this way there is a certain trial and error to our thinking, where the strongest ideas survive, both in our own minds and in conversation with others (see Weick, 1989).

In the field of economics, the process of following “slow hunches” is what Richard Thaler describes as he and colleagues would eventually revolutionize the field of economics to create the field of behavioral economics. Behavioral economics brings insights from psychology into standard economic questions such as savings and investment decisions. It is work that eventually won Richard Thaler the Nobel prize in economics, but it all started with noticing “anomalies” and following slow hunches. As Thaler describes:

“A slow hunch is not one of those ‘aha’ insights when everything becomes clear. Instead, it is more of a vague impression that there is something interesting going on, and an intuition that there could be something important lurking not far away. The problem with a slow hunch is you have no way to know whether it will lead to a dead end. I felt like I had arrived on the shores of a new world with no map, no idea where I should be looking, and no idea whether I would find anything of value” (Thaler, 2015, p. 40).

Thaler was noticing cases where we fall short of the rational model of behavior. The rational model of behavior often describes our behavior, but not always. We sometimes exhibit self-control, but in many situations we do not. We often plan for the future, but often fall short. The rational model of behavior sets a standard of what we should do, and this model was largely at the heart of economics. Thaler and colleagues, however, began adding descriptive realism into how we behave. For example, one of the signature programs developed from behavioral economics is Save More Tomorrow. Save More Tomorrow starts with the insight that as our income increases in the future, rather than save it, we’ll likely spend it. But, if you ask anyone, they will tell you they should save more in the future. Save More Tomorrow is an automatic plan to increase the percentage of savings from your paycheck when you receive a pay increase in the future. It makes sense that we will fall short of our intentions for savings, but this kind of descriptive realism was largely absent from economics.

This doesn’t mean, of course, that any slow hunch will lead us to revolutionize our respective fields, but we’d never develop innovative ideas if we always ignored a vague notion that our current understanding is incomplete—if we never followed our curiosity.

But how do “slow hunches” and incubation work exactly? The process of incubation seems to happen in three ways (Sio & Ormrod, 2009): First, incubation can help us access greater knowledge networks (both externally and within our own minds) through spreading activation. In this way, over time, new knowledge networks are activated and provide new avenues to approach a problem. Second, incubation can help with selective forgetting of a dominant approach. We can get anchored on initial solutions and be unable to flexibly see the problem in different ways. Incubation can foster selective forgetting which allows a more appropriate solution to surface. Finally, incubation can lead to a restructuring of the problem in more productive ways. Restructuring can be a fundamental shift in how you represent the problem, allowing you to see it in a new light (e.g. the nine-dot problem). In a meta-analysis of 117 studies that examined incubation, support was found for all three aspects of incubation: spreading activation, selective forgetting, and restructuring (Sio & Ormerod, 2009). The positive effects for incubation were found to be strongest for creative problem solving tasks, especially when there are multiple solutions options.

But how do we distinguish a productive slow hunch from a “dead end?” As Thaler mentions, “The problem with a slow hunch is you have no way to know whether it will lead to a dead end.” I often see a preoccupation with wanting to avoid “dead ends” or “rabbit holes.” But, dead ends and “rabbit holes” are only revealed in retrospect, after we’ve spent some time pursuing a line of inquiry. If we are overly concerned with predicting, in advance, if a line of inquiry will lead to a “dead end” we run the risk of not following productive hunches that can lead to innovative ideas. Of course, we face a never-ending dilemma of opportunity cost with our time, but if we’re aiming for innovative ideas, then we need to be more willing to follow slow hunches.

So, if you are aiming for innovative ideas in your work, be more willing to follow slow hunches. An innovative solution may emerge slowly over time and will be well worth your effort.


Johnson, S. (2010). Where good ideas come from: The natural history of innovation. New York: Riverhead.

Thaler, R. H. (2015). Misbehaving: The history of behavioral economics. New York: Norton.

Sio, U. N., Ormerod, T. C. (2009). Does incubation enhance problem solving? A meta-analytic review. Psychological Bulletin, 135, 94–120.

Weick, K. E. (1989). Theory construction as disciplined imagination. Academy of Management Review, 14(4), 516-531.

Photo Source: TeroVesalainen/Pixabay

What are the Benefits of a Learning Orientation?

When Adam Bryant, a reporter for the New York Times, distilled lessons he learned from interviewing hundreds of C.E.O.’s, being intensely curious with a desire to learn from others was at the top of his list. As he states:

“The C.E.O.’s are not necessarily the smartest people in the room, but they are the best students—the letters could just as easily stand for “chief education officer.” “You learn from everybody,” said Alan R. Mulally, the [former] chief executive of the Ford Motor Company. “I’ve always just wanted to learn everything, to understand anybody that I was around—why they thought what they did, why they did what they did, what worked for them, what didn’t work” (Bryant, 2011).

As the noted leadership scholar John W. Gardner succinctly states: “Don’t set out in life to be an interesting person; set out to be an interested person” (Gardner as quoted in Collins, 1997).

In organizational psychology, the desire to be an “interested person” is most commonly labeled having a “learning orientation.” A high learning orientation is approaching any situation with the motivating question: What can I learn? It is having an active exploratory mind and seeking to learn from others. This is often contrasted with a performance orientation, which is concerned with the question: How can I demonstrate my competence (i.e. be “interesting”)? While demonstrating competence is often important, it can crowd out a willingness to ask questions and learn from others because asking question demonstrates you don’t already have all the answers.(1)

One impressive study illustrates how a learning orientation helps us adapt and, ironically, how a high performance orientation can decrease our performance. Michael Ahearne and colleagues followed 400 salespeople from a major U.S. pharmaceutical company over the course of a year as they implemented a new sales technology platform. They first assessed individuals on their learning and performance orientations. They measured one’s learning orientation with seven questions, including statements such as “It is important for me to learn from each selling experience.” In assessing one’s performance orientation, they asked questions such as, “It is very important to me that my supervisor sees me as a good salesperson” (Sujan, Weitz, & Kumar, 1994).(2)

The researchers wanted to know how one’s learning and performance orientations would impact a salesperson’s willingness to learn the new sales technology system and ultimately their performance. Would there be any difference among individuals based on their learning orientation?

Prior to the technology implementation, the 400 individual’s average sales was 4 percent above their quota. After sixth months with the new sales technology system there was a reduction of sales across the board, with all individuals now ~4 percent below their sales quota. What would happen over the next six months? As Ahearne and colleagues found, those in the top quartile of learning orientation rebounded and by the end of twelve months they were back to being 4-5 percent above quota levels. In contrast, those in the bottom quartile of learning orientation never recovered to pre-change levels and just slightly rebounding to be 3 percent below quota levels.

Ahearne and colleagues also looked at individuals solely on the performance orientation scale and their results mirror those regarding learning orientation. Those who were very high on a performance orientation never rebounded back to pre-change levels.

Why, exactly, did this happen? The researcher suggest that a high performance-orientation makes one more fearful of any performance decline and thus an individual takes a “short-term-oriented strategy to adapt to change.” With this orientation, you don’t actually take the time to learn a new system and how it can help you. This impulse is understandable. It’s not efficient to proactively learn a new sales technology system instead of focusing on your performance, but this approach backfires in the long-term as you are stuck in older, inefficient routines.

Changing your learning orientation is possible by being intentional about what you can learn in any situation versus being concerned with superficially demonstrating competence. In fact, workshops have been used as interventions to facilitate a learning or performance orientation among job seekers. In one study, 8-weeks after a learning goal orientation workshop, individuals were more likely to be employed (33 percent) compared to those who were in a workshop that facilitated performance goals (9 percent) (van Hooft & Noordzij, 2009). A learning orientation—by shaping what you pay attention to—helps with effort, persistence, and interpreting situations in a way that is more productive.

Thus, just like Gardner’s injunction to be “interested,” try in the next situation you’re in to set an intention to see what you can learn—opening yourself up to new ways of seeing and understanding. It can help you adapt to change and expand your ability to reach your goals.


Ahearne, M., Lam, S. K., Mathieu, J. E., Bolander, W. (2010). Why are some salespeople better at adapting to organizational change? Journal of Marketing, 74, 65–79.

Bryant, A. (2011, April 16). Distilling the wisdom of C.E.O.s. The New York Times. p. BU1.

Collins, J. (1997). The learning executive. Inc. Retrieved from:

Sujan, H., Weitz, B. A., Kumar, N. (1994). Learning orientation, working smart, and effective selling. Journal of Marketing, 58(3), 39-52.

van Hooft, E. A .J., & Noordzij, G. (2009). The effects of goal orientation on job search and reemployment: a field experiment among unemployed job seekers. Journal of Applied Psychology, 94, 1581–90.

Vandewalle, D. (1997). Development and validation of a work domain goal orientation instrument. Educational and Psychological Measurement, 57(6), 995-1015.

Vandewalle, D., Nerstad, C. G. L., & Dysvik, A. (2019). Goal orientation: A review of the miles traveled and the miles to go. Annual Review of Organizational Psychology and Organizational Behavior, 6, 115-144.


(1) One might reasonably ask what the difference is between a growth mindset and learning orientation. While the two constructs are highly correlated (see Vandewalle, Nerstad, & Dysvik, 2019), a growth mindset is measured as one’s implicit assumption about the malleability of intelligence. It is often revealed retrospectively in situations as you seek to understand failures. A learning orientation benefits from a growth mindset, but highlights the cognitive intention of proactively seeking to learn from any situation.

(2) The scale they used was specific to sales. For a more general scale of learning and performance orientations, see Vandewalle, 1997.

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What Generational Differences (if any) Impact Learning at Work?

What generational differences should you understand as you think about learning and development? I’ll cover two of them in this post, but please also add your thoughts and comments below as well.


In examining generational differences, I’ll admit that by and large, I am a skeptic. Most differences seem overblown and are more likely an impact of age rather than generation (e.g. most people in their 20s tend to be more idealistic, rather than those in their 20s right now being part of the “idealistic generation.”) Nevertheless, social norms do change over time and it’s hard not to see how the Great Depression and World War II shaped the dispositions of a large portion of the population in recognizable ways.

Skepticism about generational differences is fairly easy to voice, but it can be like wielding a machete that chops down the whole jungle without discriminating what plants (ideas) might have some merit. It can close us off from seeking to understand how our culture is shifting, however difficult this might be to pinpoint. This is difficult terrain to examine scientifically, as it requires longitudinal research far beyond the time horizon of most research agendas.

In addition to pinpointing exactly what generational differences exist, it is difficult to know why. Differences are often stated in descriptive terms without any theoretical rationale. It is not hard to understand why the generation that grew-up in the Great Depression would be thriftier, but many differences are presented without any explanation (e.g. “Millennials prefer extrinsic rewards”). These complications are well-understood and tempt one to take a machete to dismiss the entire jungle.

Furthermore, in asking about generational differences and learning and development, if you primarily view the mind as a biological entity, then the question is ludicrous. The biological make-up of our mind wouldn’t evolve in any perceivable way over the course of a few decades. Of course, however, the mind is both a product of our biological heritage and the culture we are enmeshed in. Thus, the question becomes, have cultural values (and technology) shifted in some distinguishable way that impacts how we might engage in learning and development?

It was into this jungle that I went searching for some credible evidence that might shed light on this question.

First, it helps to know what are generally perceived as generational cohorts.

  • Silent Generation (born 1925-1945)
  • Baby Boomers (born 1946-1964)
  • Generation X (born 1965-1979)
  • Millennials (also known as GenMe or GenY, born 1980-1994)
  • iGen (born after ~1995)

Of course, as Jean Twenge (2017) aptly argues in her book iGen, there is no drastic difference between individuals born on either side of these cutoffs. However, individuals born ~10 years apart in these cohorts would have had a different cultural experience.

From the evidence I reviewed (mostly peer-reviewed articles and Jean Twenge’s book iGen, but also data from the Monitoring the Future study of high school seniors that began in 1975), there are two considerations that I could discern to understand generational differences with regard to learning and development at work.

Psychological Safety

By many metrics, there is a greater concern with safety among those in the most recent generational cohort, in particular around avoiding risk. This may be the result of well-intentioned parenting practices that help children and teenagers avoid risky behavior. Twenge (2017) reports that in a nationally representative sample of individuals in 8th and 10th grade, 50% of them in the 1990s agreed with the statement “I like to test myself every now and then by doing something a little risky,” but by 2015 that number had reduced to 40% (p. 153). This, along with reducing number of teenagers getting a driver’s license (around a 15% drop of high school seniors over the last 40 years, Twenge, 2017, p. 26), and parents who always know where their kids are, leads to a portrait of a generation that is more accustomed to being kept safe.

If I had to bet, this is connected (and will continue to be so) with a greater focus on “psychological safety” at work. Psychological safety is defined as “a shared belief that the team is safe for interpersonal risk taking” (Edmondson, 1999). It is measured by asking whether mistakes will be held against you and whether team members are able to bring up problems and tough issues. Amy Edmondson of the Harvard Business School has completed highly-regarded research about psychological safety and how it impacts team learning. In a recent book, I advocated for psychological safety as a means to foster great transparency and organizational learning.

The term also gained more widespread attention after Charles Duhigg published an article in the New York Times Magazine in February of 2016 titled “What Google Learned from its Quest to Build the Perfect Team.” In the article, Duhigg discusses Google’s extensive research of itself to uncover the essentials of great teams. The punch line, as you might guess, is psychological safety.

How can you increase psychological safety at work? In efforts where psychological safety was central to a change initiative, the results have been mixed (Edmonson, 2004). In a comprehensive initiative at Prudential Financial that was aimed at making individuals feel safe to speak up (partly because of prior ethical infractions), Edmondson (2004) concludes, “Psychological safety is not created by telling people to feel safe: it is a byproduct of leadership action and example occurring in the context of doing real work” (p. 11, emphasis in original). Thus, psychological safety is best seen as a means to an end, as a way to facilitate idea sharing in the pursuit of “real work,” not as a pursuit in itself.

Thus, to the extent that you are managing a team, or developing learning programs for those just entering the workforce, you’ll want to have some recognition of psychological safety; not as a central focus, but through modeling some acceptance of what can be learned from mistakes. Of course, this is open to lots of critiques about “coddling a generation” (see Lukianoff & Haidt, 2018), which is fair, but it’s helpful to have a better contextual understanding of subtle generational shifts that may be occurring.

Smartphones, Distractions, and Limitless Content Choices

Central to any understanding of generational differences is how the smartphone impacts one’s development. This is central to Jean Twenge’s thesis in iGen, and owning a smartphone understandably shifts how we experience the world. The iPhone was introduced in 2007 and Twenge cites a 2015 marketing survey that 2 out of 3 U.S. teens own an iPhone (p. 2). If the statistic was that teen smartphone ownership was closer to 100 percent, I wouldn’t doubt it. The question becomes how does smartphone usage impact a generation entering the workforce? A full treatment of this question is beyond the scope of this post, and longitudinal evidence has not been established (for an excellent review, see Wilmer, Sherman, & Chein, 2017), but one obvious influence of the smartphone on our cognition is that it scatters our attention. It can do so exogenously—by text alerts, etc.—but also endogenously, as Wilmer et al. (2017) state:

“Endogenous interruptions occur when the user’s own thoughts drift toward a smartphone-related activity, and thereby evince an otherwise unsolicited drive to begin interacting with the device. These endogenously driven drifts of attention might arise from a desire for more immediate gratification when ongoing goal-directed activities are not perceived as rewarding” (p. 4).

There have been correlational studies that link high “media multitasking” and an ability to sustain attention (for a review see van der Schuur et al., 2015), but no longitudinal studies that can determine causality (to my knowledge). Whether smartphone usage throughout early adolescence has a unique impact during that developmental period compared to impacting individuals of all ages equally remains to be seen.

A potential decline in sustain attention may be evident in the decline of reading. As Twenge (2017) cites, among high school seniors in 1976, 10% of students said they did not read for pleasure the prior year, but by 2015 that number increased to 30% (p. 61). Additionally, throughout the 1970s and 1980s, over 50% of high school seniors “read a book or magazine nearly every day.” That number has steadily declined over the years, and by 2015, now only 16% of high school seniors agree with this statement. As Twenge states, “For a generation raised to click on the next link or scroll to the next page within seconds, books just don’t hold their attention.” As one 12-year old she interviewed states, “I’m not really a big reading person. It’s hard for me to read the same book for such a long time. I just can’t sit still and be superquiet” (p. 61).

Of course, the cause of the decline of reading books would be multifarious, however, the smartphone and our access to limitless content has to be acknowledged. By and large, it is an experience of life where one is less accustomed to focused concentration or engaging in what Cal Newport (2016) calls “deep work,” which he defines as “professional activities performed in a state of distraction-free concentration that push your cognitive capabilities to their limit” (p. 3).

Given the greater difficulties of sustaining attention—a difficulty that may be more pronounced for iGen, all of this ramps up the standards it takes to engage individuals, and suggests the obvious tactic of frequent breaks for any training event as well as setting the friendly ground rule of “being present.” It also suggests taking proactive measures to create less distraction in the workplace (counter to the open-office movement). Given we are already dealing with an internally-driven desire to shift our attention, we can at least make an effort to combat distractions in our environment.


In sum, pinpointing precise generational differences and how they impact work is complex, especially disentangling what are the natural inclinations of age and career stage compared to generation shifts that are unlike anything that has occurred before. In addition, we are dealing with subtle shifts in cultural norms over decades. While I have outlined two things to consider that may be generational, please comment below on your own experiences as well.

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Edmondson, A. (1999). Psychological safety and learning in work teams. Administrative Science Quarterly, 44(2), 350-383.

Edmondson, A. (2004). Teaching Note: Safe to Say at Prudential Financial. 5-604-021. Boston, MA: Harvard Business School Publishing.

Lukianoff, G., & Haidt, J. (2018). The coddling of the American mind: How good intentions and bad ideas are setting up a generation for failure. New York: Penguin Press.

Newport, C. (2016). Deep work: Rules for focused success in a distracted world. New York: Grand Central Publishing.

Twenge, J. M. (2017). iGen: Why today’s super-connected kids are growing up less rebellious, more tolerant, less happy—and completely unprepared for adulthood—and what that means for the rest of us. New York: Atria Books.

van der Schuur, W., Baumgartner, S. E., Sumter, S. R., & Valkenburg, P. M. (2015). The consequences of media multitasking for youth: A review. Computers in Human Behavior, 53, 204-215.

Wilmer, H. H., Sherman, L. E., Chein, J. M. (2017). Smartphones and cognition: A review of research exploring the links between mobile technology habits and cognitive functioning. Frontiers in Psychology, 8, 1-16.

Photo Source: geralt/Pixabay