The Attention Economy's Hidden Price Tag
Why information literacy is your best defense in an economy designed to keep you from doing the math.
You know that thing where you pick up your phone to check one email and somehow twenty minutes later you’re three layers deep in someone’s vacation photos from 2019, your original task completely forgotten? Yeah. That’s not an accident.
Welcome to the attention economy, where you are simultaneously the consumer, the product, and the currency. And like most economies designed to extract maximum value from participants, it works best when you can’t see what you’re actually paying.
Here’s the pitch you’ve been sold: information is free now. Knowledge at your fingertips. The world’s libraries in your pocket. Just a quick scroll, just a fast search, just checking one thing real quick.
But let me show you the math you’re not doing.
PRICE = What You Think You’re Paying
“It’s free!”
“Just a few seconds of scrolling”
“I’m just checking one thing quickly”
COST = What You’re Actually Paying
Your capacity for sustained attention
Your ability to think critically
Your sense of agency over your information diet
Your mental models getting shaped by algorithmic curation
The slow erosion of being able to sit with not-knowing
VALUE = What You Could Be Getting Instead
Actual understanding vs. surface familiarity
Discernment vs. reaction
Agency vs. passivity
Deep engagement vs. frantic consumption
Here’s what librarians have always known that tech companies are banking on you never figuring out: Information literacy is what lets you see the difference between price, cost, and value. Without it, you genuinely can’t tell what you’re paying or whether you’re getting ripped off.
The attention economy depends on people not being able to calculate true cost. It’s like those payday loan places - the business model only works if people can’t do the math on what they’re actually paying.
And now we’re adding AI to the mix, which promises to make information access even faster, even easier, even more frictionless. Which should make you ask: faster and easier for whom? And what am I trading to get it?
The Cost No One Told You About
Let me tell you what I see in my job, where I help teams integrate AI into their daily work. Smart, capable people who can’t read more than three paragraphs without checking their phone. Designers who used to sit with a creative problem for hours now panic if they don’t have an immediate answer. Writers who’ve trained themselves to skim so efficiently they’ve forgotten how to actually read.
And they all think something is wrong with them.
Nothing is wrong with you. Your attention didn’t break because you’re weak or undisciplined. It was systematically dismantled by an economic system that profits from fragmentation.
Here’s how the cost accumulates:
Your capacity for sustained attention isn’t just about focus. It’s about your ability to hold complexity, to sit with ambiguity, to follow a thought all the way through to its conclusion instead of jumping to the first available answer. Every time you interrupt yourself to check just one thing, you’re practicing fragmentation. And what you practice, you become.
Your ability to think critically requires space. Not just time, but mental space to ask “wait, who benefits from me believing this?” or “what am I not being shown?” When information comes at you in an endless scroll designed to trigger reaction, not reflection, critical thinking doesn’t just get harder - it starts to feel impossible. Exhausting. Not worth it.
Your sense of agency over your information diet is maybe the sneakiest cost. You think you’re choosing what to read, watch, engage with. But the algorithm is choosing what you get to choose from. It’s like thinking you have dietary freedom when someone else decides what’s in your fridge, what’s on the menu, and which aisles you walk down in the grocery store. The choices feel real until you realize how constrained they actually are.
Your mental models getting shaped by algorithmic curation means you’re increasingly seeing a version of the world that confirms what you already think, that shows you what kept you engaged before, that nudges you toward conclusions that serve the platform’s business model. You’re not getting information. You’re getting information-flavored content optimization.
And here’s the one that keeps me up at night: The slow erosion of being able to sit with not-knowing.
When was the last time you had a question and just... sat with it for a while? Didn’t immediately Google it, didn’t ask ChatGPT, didn’t reach for your phone to resolve the uncertainty right now?
That tolerance for not-knowing, that ability to sit in the productive discomfort of genuine curiosity before rushing to resolution: that’s the foundation of actual learning. It’s also becoming extinct.
The attention economy trains you to treat every question as an emergency that must be resolved immediately. AI is accelerating this by making instant answers even more instant. And what we’re losing in the speed-up is the actual thinking that happens in the space between question and answer.
What Librarians Know That You Need To
Here’s what’s different about how librarians think about information: We don’t start with the answer. We start with the question behind the question.
When someone comes to a reference desk and asks “where are the books on depression?”, a good librarian doesn’t just point to the 616s and call it done. They ask: Are you looking for clinical information or personal narratives? For yourself or someone else? Do you want to understand the condition or find coping strategies?
Because “where are the books on depression” isn’t actually the question. It’s the placeholder for a need the person hasn’t fully articulated yet, maybe even to themselves.
This is called the reference interview, and it’s the closest thing librarians have to a superpower. It’s the skill of helping people figure out what they actually need to know, not just what they think they need to know.
And here’s why that matters in the attention economy: You can’t evaluate the value of information if you don’t know why you need it.
📖 Librarian Dictionary
relevance judgment (n.)
/ˈreləvəns ˈdʒʌdʒmənt/ REL-eh-vence JUJ-ment
Library Science. The skill of determining whether information actually addresses your specific need, not just whether it’s related to your topic. Information isn’t relevant or irrelevant in a vacuum - it’s only relevant in relation to what you’re trying to accomplish. This is why you can’t evaluate the value of information if you don’t know why you need it. Without understanding your purpose, you have no basis for judgment.
Classic use: A patron asks for information on climate change. Before judging what’s relevant, a reference librarian determines: Are you writing a high school essay? Deciding whether to buy coastal property? Trying to win an argument with your uncle? The same article on sea level rise might be highly relevant for one need and completely irrelevant for another. Relevance isn’t about the information quality - it’s about the match between information and purpose.
Modern plot twist: The attention economy deliberately obscures this distinction. It serves you “relevant” content based on engagement patterns, not your actual needs. You think you’re learning, but you’re just consuming topically-adjacent information with no clear purpose. AI makes this exponentially worse by answering questions you didn’t actually ask, with information that’s topically related but practically useless for what you need to do. You end up with the illusion of productivity - look how much I learned! - without the ability to assess whether any of it actually helped.
Origin: Formalized in information science in the 1960s when researchers realized retrieval systems were returning topically accurate but practically useless results, because relevance is relational, not absolute.
See also: the reference interview, information need, why “just Google it” gives you answers to questions you didn’t ask, the difference between interesting and useful.
When you’re scrolling reactively, consuming whatever the algorithm serves you, you’re not asking “what do I need to know and why?” You’re just ingesting. Like standing in front of the fridge eating whatever’s at eye level, not because you’re hungry for it, but because it’s there.
Information literacy (real information literacy, not the watered-down version you might have gotten in a one-hour high school library orientation) is about developing a different relationship with information entirely.
It means asking:
Why do I need to know this? (Purpose)
What will I do with this information once I have it? (Application)
Who is telling me this and why? (Source evaluation)
What are they not telling me? (Critical analysis)
Is this the right information for what I actually need, or just adjacent to it? (Relevance)
Am I ready to understand this, or do I need foundational knowledge first? (Context)
These aren’t just nice questions for academic research. These are the questions that let you calculate true cost and value in an economy designed to keep you from doing that math.
When you know why you’re seeking information, you can tell whether you’re getting value or just getting fed. You can distinguish between learning and the performance of learning. Between understanding and the illusion of understanding that comes from skimming three articles and a Wikipedia page.
This is the cost-benefit analysis the attention economy doesn’t want you to run.
Coming up soon: How to actually stop scrolling AI at 2am. The neurochemistry behind why “just one more question” turns into three-hour rabbit holes, and why your brain needs you to stop feeding it information so it can actually process what you already learned. Plus, the librarian’s approach to knowing when you have enough information to close the app and put the phone down.
I swear by the reference librarians’ CRAAP test.
My takeaway is that real learning is relational (and I don’t mean with the AI). Most people don’t know what question to ask without some help, I learned my research skills before there were PCs and smartphones and I am struck with how little people now know how to do. Thank you for this very stimulating essay.