Chapter 14: Multitasking, Flow States, and the Attention Economy

Three popular psychology claims about attention walk into this chapter. One is well-supported. One is real but overpromised. One is more complicated than headlines suggest.

Claim 1: "Multitasking makes you less productive." The research is solid — what you're doing when you "multitask" is actually task-switching, and each switch costs time and accuracy. This is one of the better-supported findings in cognitive psychology.

Claim 2: "You can hack your way into flow states." Flow — the state of total absorption in a challenging task, described by Mihaly Csikszentmihalyi — is a real psychological phenomenon. But the productivity culture version, which promises that you can reliably trigger flow at will through the right techniques, overpromises on what the research delivers.

Claim 3: "Attention spans are shrinking." This is the claim most frequently cited in discussions of smartphones and social media. It sounds alarming. And the evidence is... complicated. Not clean enough for a dramatic headline in either direction.

This chapter evaluates all three, because together they paint a picture of how attention actually works — which is more interesting and more useful than the pop versions of any individual claim.

Before You Read: Confidence Check

Rate your confidence (1–10) that each statement is true.

1. "Multitasking is less productive than doing one thing at a time." ___
2. "It takes 25 minutes to refocus after being interrupted." ___
3. "Flow states can be reliably triggered using specific techniques." ___
4. "The average human attention span has decreased to 8 seconds — less than a goldfish." ___
5. "Smartphones are fundamentally changing how our brains process information." ___

Multitasking: What You're Actually Doing Is Task-Switching

The Finding

When you think you're multitasking — answering emails while writing a report while listening to a podcast — you are not processing multiple streams of information simultaneously. You are rapidly switching between them. And each switch carries a cost.

This is one of the most robust findings in cognitive psychology. The task-switching cost has been demonstrated in hundreds of studies: switching between tasks takes time (switch cost latency) and increases errors (switch cost accuracy). The costs are larger when the tasks are complex, when the tasks use similar cognitive resources (both are verbal, both are spatial), and when the switches are frequent.

Monsell (2003) provides a comprehensive review: task-switching involves reconfiguring cognitive "task sets" — the mental setup for the current task (what to attend to, what responses to make, what rules to apply). Each switch requires discarding the old task set and loading the new one, which takes measurable time and effort.

Rubinstein, Meyer, and Evans (2001) estimated that the costs of task-switching can reduce productive time by up to 40% for complex tasks. Not 40% less total work done, but 40% of the time spent on switching rather than productive effort.

The "25 Minutes" Claim

You've probably heard that "it takes 25 minutes to get back to a task after an interruption." This claim is based on research by Gloria Mark and colleagues at UC Irvine, who found that workers took an average of 23 minutes and 15 seconds to return to the original task after being interrupted.

The finding is real, but the context matters:

• The 23-minute average includes time spent on other intervening tasks after the interruption — not 23 minutes of staring blankly. Workers were doing other things during that time.
• The time to return to the same cognitive state (where you were in your thinking process) is harder to measure and varies enormously.
• Self-interruptions (checking your phone voluntarily) are actually more common than external interruptions, and they carry similar costs.

The bottom line: the general principle — that interruptions carry meaningful costs for complex cognitive work — is well-supported. The specific "25 minutes" figure is a reasonable estimate of time to return to the original task, but it's context-dependent and shouldn't be treated as a universal constant.

Verdict: "Multitasking is less productive than doing one thing at a time" ✅ SUPPORTED — The task-switching cost is one of the most robust findings in cognitive psychology. What people call "multitasking" is actually rapid task-switching, and each switch costs time and accuracy. The costs are larger for complex tasks. Evidence: hundreds of studies. Monsell (2003) review, Rubinstein et al. (2001). Caveat: "Interleaving" — strategically alternating between related tasks — can sometimes enhance learning (Chapter 12). But this is deliberate, structured alternation, not the reactive switching that characterizes typical multitasking.

Flow States: Real, But Overpromised

What Csikszentmihalyi Found

Mihaly Csikszentmihalyi (pronounced "cheek-sent-me-HIGH") introduced the concept of flow in the 1970s based on extensive interviews with artists, athletes, musicians, and scientists about their optimal experiences. Flow is characterized by:

• Complete absorption in the activity
• Loss of self-consciousness — the sense of self recedes
• Altered sense of time — hours feel like minutes
• Intrinsic motivation — the activity feels rewarding in itself
• The challenge-skill balance — the task is demanding enough to be engaging but not so demanding as to be overwhelming
• Clear goals and immediate feedback — you know what to do and can tell how you're doing

Csikszentmihalyi's research on flow has been influential and has been replicated in various forms. The basic phenomenon is real: people do experience states of total absorption in challenging, engaging activities, and these experiences are associated with positive affect, high performance, and life satisfaction.

Where the Pop Version Overpromises

The productivity culture version of flow — "flow hacking" — takes Csikszentmihalyi's descriptive observations and turns them into a prescriptive system:

"You can trigger flow at will." The pop version suggests that by setting up the right conditions (clear goals, distraction-free environment, challenge-skill match), you can reliably enter flow. The reality: flow is probabilistic, not deterministic. You can create conditions that make flow more likely, but you cannot guarantee it. Flow happens to you; you don't "hack" it.

"Flow produces superhuman productivity." Some flow advocates claim that people in flow are 5x or 10x more productive. These numbers are not based on rigorous measurement. Flow may enhance performance, but the magnitude is not well-established and likely varies enormously across tasks and individuals.

"The flow economy is the future." Steven Kotler and the Flow Research Collective have built a business around flow optimization. While their work is more sophisticated than typical pop psychology, some of the marketing claims (flow as a competitive advantage, flow as the key to peak performance) extend beyond what the research supports.

"Flow is always good." Flow can occur during activities that are unhealthy or unproductive — gambling, video gaming, social media scrolling. The experience of flow doesn't validate the activity. A gambler in flow is not performing at their best; they're absorbed in an activity that may be harmful.

Verdict: "Flow states can be reliably triggered using specific techniques" ⚠️ OVERSIMPLIFIED — Flow is a real, well-documented psychological state. Certain conditions (challenge-skill balance, clear goals, distraction-free environment) make flow more likely. But flow cannot be reliably triggered at will — it is probabilistic, not deterministic. The "flow hacking" industry overpromises on the controllability and magnitude of the effect. Origin: Csikszentmihalyi (1975/1990). The phenomenon has been replicated. The "hacking" and productivity claims extend beyond the evidence.

"Attention Spans Are Shrinking": The Complicated Claim

The Goldfish Statistic

You may have heard that "the average human attention span has decreased to 8 seconds — less than a goldfish (9 seconds)." This statistic was widely cited in media starting around 2015, attributed to a Microsoft study.

The claim is almost certainly wrong, and here's why:

The Microsoft study. In 2015, Microsoft Canada published a report claiming that the average human attention span had decreased from 12 seconds in 2000 to 8 seconds in 2015. However, the "12 seconds in 2000" baseline appears to have no primary source — it was cited to a website called Statistic Brain, which has been unable to provide the original study. The methodology for the "8 seconds" figure is unclear.

The goldfish comparison. There is no reliable scientific literature on "goldfish attention spans." The 9-second figure is folk knowledge with no identifiable research source. Goldfish can actually be trained to perform tasks requiring sustained attention over much longer periods.

Attention span is not a single number. "Attention span" is not a unified cognitive capacity. Sustained attention (maintaining focus on a single task), selective attention (focusing on one thing while ignoring distractions), and attention switching (moving between tasks) are distinct cognitive processes that are measured differently and may be affected differently by technology use.

What the Evidence Actually Shows

If the goldfish statistic is unreliable, is there any evidence that technology is affecting attention?

The smartphone proximity effect (Ward et al., 2017). This study found that having your smartphone within sight — even if it's turned off — reduces available cognitive capacity. Participants performed worse on cognitive tasks when their phone was on the desk (even face down and silent) compared to when it was in another room. This suggests that the mere presence of the phone taxes attention, not because of dopamine but because of the cognitive cost of resisting the urge to check it.

Changes in media consumption patterns. People do consume media in shorter bursts than in previous decades. TikTok's success (short-form video) and declining attention to long-form content suggest changing preferences, though whether this reflects changing capacity is debated.

The Orben and Przybylski (2019) finding. In their analysis of a large dataset (350,000+ adolescents), screen time's association with wellbeing was negative but tiny — comparable to the associations between wellbeing and wearing glasses or eating potatoes. This suggests the effects of technology on attention and wellbeing, if they exist, are much smaller than headlines suggest.

The honest assessment: There is some evidence that technology affects how we deploy attention (shorter engagement, more switching, phone proximity effects), but the evidence that our fundamental attentional capacity has decreased is weak. We may be choosing to attend differently without having lost the ability to sustain attention when motivated.

Verdict: "The average human attention span has decreased to 8 seconds" ❌ DEBUNKED — The specific statistic has no reliable source. The Microsoft report's methodology is unclear. The goldfish comparison has no scientific basis. "Attention span" is not a single measurable quantity. Caveat: Technology may affect how we deploy attention (shorter media consumption, more switching), but the claim that our fundamental attentional capacity has measurably decreased is not well-supported.

Verdict: "Smartphones are fundamentally changing how we process information" 🔬 UNRESOLVED — There is evidence for specific effects (phone proximity reducing cognitive capacity, changes in media consumption patterns). But the grand claim that smartphones are "rewiring our brains" or permanently reducing our attentional capacity outpaces the evidence. The effects documented so far are small and may reflect changing preferences rather than changing capacities. Key study: Ward et al. (2017) on smartphone proximity effects. Context: Orben & Przybylski (2019) showing screen time effects are very small.

What Actually Helps With Attention

Reduce proximity to distractions. The Ward et al. study suggests the simplest intervention: put your phone in another room during focused work. This is a behavioral strategy, not a neurochemical one.

Practice sustained attention. Attention can be trained through deliberate practice on tasks requiring sustained focus. Meditation training has modest evidence for improving attentional control (we'll address this in Chapter 30).

Manage your environment. Noise, interruptions, and visual clutter all tax attention. Environmental design matters more than willpower.

Adequate sleep. Sleep deprivation impairs attention more than any technology. Getting enough sleep is the single most impactful thing most people can do for their focus.

Exercise. Aerobic exercise improves executive function, including attentional control.

Fact-Check Portfolio: Chapter 14

If any of your 10 claims involve attention, focus, productivity, or technology's effects on cognition: - Does the claim cite a specific statistic? Trace it to the original source. - Does the claim distinguish between attention preferences and attention capacity? - Does it overpromise on the controllability of psychological states (like flow)? - Does it conflate behavioral strategies with neurochemical claims?

After Reading: Confidence Revisited

1. "Multitasking is less productive." — How confident are you now, and is the evidence stronger than you expected?
2. "It takes 25 minutes to refocus." — What does Mark's research actually measure?
3. "Flow can be reliably triggered." — What's the difference between making flow more likely and triggering it at will?
4. "Attention spans are 8 seconds." — Where did the number come from, and is there a primary source?
5. "Smartphones are fundamentally changing our brains." — What does Ward et al. (2017) show, and what does it not show?