The cost of staying informed about everything

You are not informed. You are saturated.

You check the news over breakfast. You scan LinkedIn during your commute. You skim three newsletters before your first meeting. By lunch, you have consumed more information than a 15th-century scholar encountered in a year — and you have made zero decisions better because of it.

This is not an exaggeration for effect. The average American adult spends over twelve hours per day consuming media. The average global social media session runs two hours and twenty-one minutes daily. The average knowledge worker stays focused on a single screen for forty-seven seconds before switching to something else (Mark, 2023). You are not staying informed. You are running a deficit — spending your most finite resource, attention, on an infinite supply of content that will never stop arriving, never be complete, and never, on its own, produce a single meaningful action.

In L-0125, you learned that your information diet is a choice. This lesson makes the cost of that choice explicit. Staying informed about everything is not free. It is extraordinarily expensive. And the currency is not money. It is cognitive capacity, decision quality, emotional stability, and the opportunity to go deep on anything that matters.

Information fatigue is a clinical reality, not a metaphor

In 1996 — before smartphones, before social media, before the average person carried an always-connected screen in their pocket — psychologist David Lewis conducted a landmark study for Reuters Business Information called "Dying for Information." He surveyed 1,300 managers across five countries and found that two-thirds reported information overload had damaged their personal relationships, increased tension with colleagues, and reduced job satisfaction. One-third reported physical health problems directly attributable to information stress. Over 40% said important decisions were delayed because excess information hampered their ability to choose (Lewis, 1996).

Lewis coined the term Information Fatigue Syndrome to describe the clinical pattern: anxiety produced not by a lack of information but by an excess of it. The symptoms include paralysis in decision-making, inability to prioritize, chronic distraction, and a persistent sense of falling behind — not because you are doing too little, but because the information environment is producing too much.

That was 1996. The information environment has since grown by orders of magnitude. The diagnosis has not changed. It has intensified.

The Reuters Institute Digital News Report — now the world's largest ongoing study of news consumption — found in 2025 that 40% of people across all surveyed markets say they sometimes or often deliberately avoid the news, the joint highest figure ever recorded. In some countries, the figure exceeds 60%. The percentage of people who say they feel "worn out" by the news agenda has risen from 26% in 2019 to 44% in 2024 (Newman et al., 2025). These are not lazy consumers. They are rational agents who have discovered, through experience, that the cost of staying informed exceeds the benefit.

Herbert Simon saw this coming in 1971

The intellectual framework for understanding information cost was established decades before the internet by Herbert Simon, the Nobel laureate who coined the term "bounded rationality." In a 1971 essay, Simon wrote what remains the single most precise diagnosis of the modern information crisis:

"In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention."

This is not a clever observation. It is an economic law. Attention is a finite resource. Information is an infinite supply. When supply is infinite and the resource it consumes is finite, the resource — not the supply — becomes the binding constraint on performance. Every additional unit of information you consume has an opportunity cost measured in attention you cannot spend elsewhere.

Simon also gave us the solution framework. He distinguished between two decision-making strategies: maximizing and satisficing. A maximizer seeks the best possible option by evaluating all available information. A satisficer defines a threshold of "good enough" and stops searching when that threshold is met. Simon argued that in complex, information-rich environments, satisficing consistently outperforms maximizing — not because it finds the optimal answer, but because it finds a workable answer while the maximizer is still drowning in data (Simon, 1956).

Barry Schwartz extended this research in "The Paradox of Choice" (2004), demonstrating that maximizers — people who insist on evaluating every option — report higher regret, lower satisfaction, and greater decision paralysis than satisficers, even when maximizers objectively make "better" choices by external metrics. The person who researches every restaurant in the city before choosing dinner is measurably less happy with their meal than the person who picks the first place that meets their criteria. More information did not produce a better outcome. It produced a worse experience of the outcome.

This finding scales directly to information consumption. The person who reads every analysis of an industry trend before forming an opinion is not better informed than the person who reads two high-quality sources and decides. They are more anxious, less decisive, and more susceptible to the last thing they read overriding everything that came before.

More information does not mean better decisions

The intuition that more data leads to better decisions is one of the most persistent and damaging cognitive errors in modern life. Research on information load and decision quality has consistently demonstrated an inverted-U relationship: decision quality improves as information increases — up to a threshold. Beyond that threshold, additional information degrades performance.

Eppler and Mengis (2004), in their comprehensive review of information overload research spanning four decades and multiple disciplines, documented this pattern across organizational science, accounting, marketing, and management information systems. The mechanism is consistent: beyond the processing capacity of the decision-maker, additional information introduces noise, creates false confidence, and fragments attention across too many variables to hold in working memory simultaneously.

Chewning and Harrell (1990) demonstrated this specifically in financial decision-making: auditors given excessive case information made worse distress predictions than those given a curated subset. The additional data did not clarify. It obscured.

The practical implication is uncomfortable: for most decisions you face, you already have enough information. You do not need another article, another podcast, another opinion. You need to process what you already have, form a position, and act. The habit of seeking more information is often not a search for clarity. It is an avoidance of commitment.

FOMO is the emotion that keeps you consuming

If information overload is the structural problem, FOMO — the fear of missing out — is the emotional engine that perpetuates it.

Przybylski and colleagues (2013) defined FOMO as "a pervasive apprehension that others might be having rewarding experiences from which one is absent" and established its robust link to compulsive social media engagement, lower life satisfaction, and higher anxiety. But FOMO is not limited to social experiences. It operates identically in information consumption. The fear that you will miss the crucial article, the important development, the signal hidden in today's noise — this fear drives the compulsion to check, scan, skim, and scroll.

The irony is structural. FOMO drives you to consume more information to avoid missing something important. But consuming more information degrades your ability to recognize what is important. You become less capable of detecting signal precisely because you are processing too much noise. The fear of missing out produces the condition it was trying to prevent: you miss the signal because you are buried in noise.

This is why news avoidance correlates with wellbeing rather than ignorance. The Reuters data does not show that deliberate news avoiders are less informed about events that materially affect their lives. It shows that they are less anxious, less overwhelmed, and more capable of engaging with information that matters to them — because they have recovered the attentional capacity that compulsive consumption destroyed.

The opportunity cost is what you never build

Gloria Mark, professor of informatics at UC Irvine, has documented that the average knowledge worker's attention span on screens has collapsed from two and a half minutes in 2004 to forty-seven seconds today. After an interruption, it takes an average of twenty-three minutes to fully recover deep focus (Mark, 2023).

Do the arithmetic. If you check the news three times during a deep work session, you have not spent "five minutes" on the news. You have spent five minutes reading plus roughly seventy minutes recovering your attentional state. The five-minute check cost you over an hour of cognitive performance.

Now scale that across a life. The hours spent scanning headlines, skimming feeds, and monitoring channels are not merely hours spent on low-value information. They are hours not spent building a skill, deepening a relationship, writing something that compounds, or thinking carefully about a problem that actually requires your attention. The cost of staying informed about everything is not measured in what the information does to you. It is measured in what you never do because the information consumed the capacity you needed.

This is the opportunity cost that Simon identified: attention spent on noise is attention unavailable for signal. And unlike money, you cannot earn more attention. You cannot save it. You can only spend it — on breadth that impresses no one, or on depth that changes what you are capable of.

AI as your information triage system

Here is where the curriculum's emphasis on building a Third Brain — the AI layer that augments your cognitive infrastructure — becomes directly practical.

The traditional approach to information overload is discipline: read less, check less, curate more carefully. This works, but it relies on willpower, which is a depletable resource. The AI-augmented approach is structural: delegate the triage to a system that does not experience information fatigue.

Tiago Forte's progressive summarization method — capture, then highlight, then bold the highlights, then write a summary — was designed for a human working alone. Each layer reduces the volume of information while preserving the core insight. AI collapses these layers. You can feed a week's worth of industry news into an LLM and ask: "What are the three developments most relevant to [your specific project or decision]?" The AI does not get fatigued. It does not experience FOMO. It does not need to recover from context switching.

The discipline shifts from consuming information to defining what matters. Instead of scanning everything yourself and hoping your attention catches the signal, you define your signal criteria explicitly — the goals, decisions, and projects that actually require information inputs — and let AI handle the triage. You move from being a consumer of information to being a commander of an information system.

The prerequisite for this approach is the work you did in L-0125: defining your information diet. Without clear criteria for what constitutes signal for your specific goals, AI triage produces sophisticated noise. With clear criteria, it becomes the most powerful information cost-reduction tool available.

Protocol: the information cost audit

This is your executable protocol for measuring and reducing the cost of your current information consumption.

Step 1 — Inventory (15 minutes). List every recurring information source you consume: newsletters, news sites, social feeds, Slack channels, podcasts, group chats, Reddit, YouTube subscriptions, push notifications. Include sources you check "just to stay current." Be exhaustive.

Step 2 — Time estimate (10 minutes). For each source, estimate the minutes per day (or per week, converted to daily average) you spend on it. Be honest. Include scroll time, not just reading time. Include the time you spend thinking about what you read after you close the tab.

Step 3 — The three-question test (20 minutes). For each source, answer: (1) What specific decision have I made better in the last 30 days because of this source? Name the decision. (2) If I stopped checking this source for two weeks, what concrete consequence would occur? Name the consequence. (3) What could I do with the recovered time that would compound? Name the activity. Any source that fails all three questions is a net-negative information input.

Step 4 — Eliminate or batch (5 minutes). For each net-negative source: either eliminate it entirely or batch it to a single weekly check. Do not "reduce." Reduction requires ongoing willpower. Elimination and batching are structural changes that persist without discipline.

Step 5 — Redirect (ongoing). Take the time you recovered and allocate it to a single depth activity: a skill you are building, a project you are advancing, a relationship you are investing in. This is not about doing less. It is about doing less that does not matter so you can do more of what does.

The bridge to depth

You have now confronted the cost structure of information consumption: the cognitive tax, the decision quality degradation, the FOMO engine, the opportunity cost of breadth without depth, and the structural alternative that AI-augmented triage provides.

The next question is directional. If you should not try to stay informed about everything, what should you go deep on instead? How do you choose where to invest the attention you have recovered?

That is the subject of Depth over breadth for signal detection — the argument that concentrated knowledge in a few domains produces better signal detection than shallow awareness across many. The cost of staying informed about everything is not just what it takes from you. It is what it prevents you from becoming.

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Sources

1. Lewis, D. (1996). Dying for Information? An Investigation into the Effects of Information Overload in the UK and Worldwide. Reuters Business Information.
2. Newman, N., Fletcher, R., Robertson, C. T., & Nielsen, R. K. (2025). Reuters Institute Digital News Report 2025. Reuters Institute for the Study of Journalism, University of Oxford.
3. Simon, H. A. (1971). Designing organizations for an information-rich world. In M. Greenberger (Ed.), Computers, Communications, and the Public Interest (pp. 37-72). Johns Hopkins Press.
4. Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological Review, 63(2), 129-138.
5. Schwartz, B. (2004). The Paradox of Choice: Why More Is Less. Ecco/HarperCollins.
6. Iyengar, S. S., & Lepper, M. R. (2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995-1006.
7. Eppler, M. J., & Mengis, J. (2004). The concept of information overload: A review of literature from organization science, accounting, marketing, MIS, and related disciplines. The Information Society, 20(5), 325-344.
8. Chewning, E. G., & Harrell, A. M. (1990). The effect of information load on decision makers' cue utilization levels and decision quality in a financial distress judgment task. Accounting, Organizations and Society, 15(6), 527-542.
9. Przybylski, A. K., Murayama, K., DeHaan, C. R., & Gladwell, V. (2013). Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior, 29(4), 1841-1848.
10. Mark, G. (2023). Attention Span: A Groundbreaking Way to Restore Balance, Happiness and Productivity. Hanover Square Press.