If we’ve spent any time reading about how to be better consumers of news and media, we’ve probably encountered the phrase “information diet.” It shows up everywhere from digital wellness guides to advice columns about managing anxiety in a 24-hour news cycle. The idea is intuitive and appealing: we should treat the information we consume the way we treat the food we eat, being intentional about what we let in and protecting our mental health the same way we’d protect our physical health.
The concept gained mainstream traction in 2012, when technologist Clay Johnson published The Information Diet, a book that made the case for conscious, deliberate consumption of media. Johnson argued that just as the industrialization of food had created an epidemic of obesity by making cheap, addictive calories available at scale, the industrialization of information had created an epidemic of misinformation and overwhelm by making cheap, addictive content available at scale. The solution, in both cases, was personal responsibility: learn to recognize the junk and develop the habits needed to take control of what you consume.
The book arrived at a specific inflection point. In 2012, social media was rapidly becoming the primary way people encountered news, but the platforms were still relatively new and the scale of the problem was still emerging. Facebook would cross a billion users that same year. Twitter was becoming the default venue for breaking news. The smartphone had put an infinite scroll of content in everyone’s pocket. For many people, this was the first moment when the sheer volume of available information started to feel unmanageable, and the diet metaphor offered a framework that made the problem feel solvable. If the issue was consumption, then the solution was discipline. If the issue was too much input, then the answer was better filters.
That framing resonated deeply, and it’s continued to shape the conversation about media literacy and information overwhelm for more than a decade. Today the information diet shows up in corporate wellness programs and digital detox retreats, in parenting advice about screen time and in the broader language of self-improvement culture. The idea has become so embedded in how we talk about our relationship to information that it can be easy to forget it’s a metaphor at all, and that like all metaphors, it illuminates some things while obscuring others.
The three pillars of the information diet
The information diet isn’t a single set of instructions. It’s a collection of related practices that different writers and thinkers have organized under the same umbrella, and the specific advice varies depending on who’s offering it. But the core recommendations cluster around three consistent themes.
The first is reduction: consume less. This means spending less time scrolling through social media, limiting exposure to 24-hour news cycles, and being deliberate about how many newsletters and feeds and notifications we allow into our daily routines. The reasoning behind this recommendation is that the sheer volume of information we encounter creates a kind of cognitive overload, where we’re processing so much that we lose the ability to think clearly about any of it. Reducing the volume, the argument goes, creates space for deeper and more focused engagement with the information that remains.
The second is curation: consume better. This means actively choosing high-quality sources over low-quality ones, favoring long-form reporting over clickbait, seeking out writers and publications with track records of accuracy rather than defaulting to whatever the algorithm surfaces. Curation also means periodically auditing our feeds and subscriptions to make sure they still reflect our actual interests and needs rather than the accumulated drift of years of casual follows and one-click subscriptions.
The third is protection: set boundaries around our consumption. This means establishing screen-free times and turning off push notifications, creating physical and temporal spaces where information doesn’t reach us. The logic here is that constant connectivity creates a kind of ambient anxiety, and that deliberately disconnecting from the flow of information gives our brains the rest they need to process what we’ve already taken in.
All three of these practices are reasonable, and for many people they represent a meaningful improvement over consuming information passively and without any intentional structure at all. Reducing volume can create the mental space for deeper thinking, and choosing better sources improves the quality of the information we’re working with. Setting boundaries can ease the background stress that comes from feeling perpetually plugged in. These practices help, but the real issue is whether they’re sufficient on their own.
Where the diet metaphor breaks down
Where the framework runs into trouble is in the underlying assumption that ties all three pillars together: that information quality is primarily a problem of individual consumption, and that the solution is primarily a matter of personal discipline. That assumption shapes not just the advice itself, but the way we think about who’s responsible when our information environment fails us.
The amount of content produced globally every day now exceeds what any single person could process in a lifetime, and a growing share of that content is specifically engineered to hold attention rather than to inform. Algorithmic feeds (the systems that platforms like Facebook, Instagram, TikTok, and X use to decide what content appears in our timelines) select content based on engagement metrics like clicks, likes, shares, and time spent. Content that provokes strong emotional reactions gets surfaced more often than content that’s accurate but less attention-grabbing. Asking each of us to individually out-discipline a system designed by some of the best-funded engineering teams on the planet is like asking someone to bail out a flooding basement with a coffee mug. The effort is real, but the tool doesn’t match the scale of the problem.
There’s a deeper issue embedded in the metaphor, too. Framing our relationship to information as a “diet” positions the entire information environment as something to defend against. The strategies are oriented around what to consume less of and what to block and avoid. These defensive moves can help manage the feeling of being overwhelmed, and for people in acute information distress, they can provide meaningful relief. But they don’t address the underlying challenge: evaluating information well requires knowledge and skills that no one person holds across every subject they encounter. We can be as disciplined as we want about our consumption, and we’ll still run into claims we can’t evaluate and stories we can’t contextualize on our own. And that’s where a different question becomes necessary: if individual discipline isn’t sufficient, what would a shared approach to information quality look like? The answer turns out to be less novel than we might expect, because for most of history, shared approaches were the default.
The village we used to have
For most of human history, and for most of the history of mass communication, the work of navigating complex information was shared across institutions and communities rather than carried by individuals acting alone. Public libraries employed reference librarians, professionals whose entire function was to help people find trustworthy information and navigate questions they couldn’t answer on their own. A person didn’t need to independently evaluate every source in the library’s collection. They could walk up to a desk and describe what they were looking for, and a trained professional would guide them toward the most reliable material available on that subject. This wasn’t a luxury or a niche service, but rather the foundational model of how public information access was designed to work. Newsrooms served a similar intermediary function. Editors and fact-checkers verified reporting before publication, so that readers received information that had already been through a review process designed to catch errors and flag unsubstantiated claims.
These systems weren’t perfect. They had biases and blind spots of their own, and access to them was uneven across communities and demographics. But they operated on a shared assumption that’s easy to take for granted until it’s gone: the work of determining what’s reliable is too complex and too consequential to leave entirely to each person acting alone. These were collective systems built to carry a collective burden, and for decades they functioned as the invisible infrastructure beneath the information environment most people navigated daily.
The rise of the internet disrupted many of these intermediary structures and replaced them with something fundamentally different. Social media platforms didn’t just change where we get our information; they changed who does the work of evaluating it. The assessment labor that used to be performed by trained professionals at institutional scale has been pushed onto each of us as individuals, without the training or tools those professionals relied on. And the systems that replaced them weren’t designed to prioritize accuracy in the first place. They were designed to maximize the amount of time we spend on the platform. The shared infrastructure that once carried the weight of information evaluation has largely disappeared, but the need for it hasn’t. If anything, the need has grown.
What an information village looks like
An information village is a way of rebuilding that shared evaluative capacity at the community and personal scale. It’s the ecosystem of sources and relationships we rely on to stay informed. It includes the writers and publications we read, the people we talk to about what’s happening, the places we go when we need to verify a claim, and the habits we’ve built around consuming and evaluating information. When that ecosystem is working well, we feel oriented. We can find what we need, we encounter perspectives that challenge our thinking, and we have ways of checking whether something is reliable before we act on it or pass it along.
Think about the last time a piece of information stopped us in our tracks. Maybe a headline that seemed alarming but also seemed too perfectly crafted to be straightforward reporting. Maybe a statistic that showed up in a friend’s social media post, cited with enough specificity to feel authoritative but without enough context to tell whether it was meaningful. In that moment, what did we do? If the answer was “I just kind of sat with the uncertainty and moved on,” that’s not a personal failure. That’s a gap in the ecosystem. It means the network of sources and people around us didn’t have a clear pathway to the kind of help that would have made a difference in how we processed what we’d encountered.
The village model shifts the question from “How do I individually consume better?” to “Who can I think with?” Instead of treating every confusing or ambiguous piece of information as a test of our personal discernment, we treat it as a prompt to engage the network of people and sources we’ve built around ourselves. A healthcare worker who can’t evaluate a clinical study on her own posts the question in a professional group and gets a detailed methodological breakdown from a pharmacologist within an hour. A parent trying to figure out whether a school policy change is as alarming as a viral post makes it sound texts a friend who works in education and gets the context the post left out. When a major news event breaks and the initial reporting is still developing, the village provides someone we can think through the early reports with in real time, someone who can help sort out what's been confirmed from what's still speculation. In each of these situations, what makes the difference is the existence of a relationship or a shared space where asking for help is normal and where complementary expertise can flow toward the question that needs answering.
How to build an information village
The shift from diet to village is a conceptual reorientation, but it needs concrete infrastructure to function on a daily basis. The raw materials are often already scattered through our lives: a coworker who’s sharp on a topic we aren’t, or a friend who always asks the question that makes us reconsider our first reaction. The work of building a village starts with recognizing the evaluative relationships that already exist in our lives and then strengthening them, filling in the gaps, and giving the whole network enough structure that it functions reliably rather than accidentally.
Build a resource hub.
A resource hub is a single, centralized place where we collect sources that have earned our trust over time. The format matters less than the consistency: a bookmarks folder, a Notion database, a shared Google Doc, or a NotebookLM all work. When a journalist or publication or researcher proves itself reliable through repeated accuracy and rigorous sourcing, it goes into the hub. Over time, this becomes a personalized reference collection we can return to instead of starting every question from scratch with a search engine. The difference between a resource hub and a casual bookmarks bar is intentionality: every entry in the hub is there because it’s been vetted through repeated use, not because we clicked “save” once only to have the bookmark get buried over time.
Create a commons.
A commons is any shared space where information and recommendations flow between people rather than through an algorithm. This can be as simple as a group chat where friends share what they’re reading, or a regular conversation with someone whose taste and judgment we’ve come to trust over time. The value of a commons is that the filter is human judgment rather than platform incentives. Algorithmic feeds are designed to maximize engagement, and engagement-optimized content doesn’t reliably surface accurate or useful information. A commons routes around that dynamic by relying on people who are selecting for quality rather than attention capture.
That said, human judgment carries its own biases. The people in our immediate circles tend to share our worldview and our blind spots. A commons where everyone reads the same sources and arrives at the same conclusions is just an echo chamber with a friendlier name. The counterweight to this isn’t seeking out people who disagree with us on everything — that’s diversity for its own sake, and it can introduce more confusion than clarity. What strengthens a commons is including people who share a commitment to evidence-based reasoning but who bring different professional backgrounds, different reading habits, and different areas of expertise. A nurse and an engineer and a journalist will read the same news story and notice different things. That kind of complementary perspective is what keeps a commons from collapsing into groupthink.
Invest in relationships where candor is normal.
The most valuable people in an information village are the ones who will tell us when they think we’re wrong, and who we can tell the same without the relationship suffering for it. This kind of trust takes time to build. It requires a mutual understanding that changing our minds in response to better evidence is a sign of good thinking rather than inconsistency. It also means building the kind of rapport where someone can say “I don’t know enough about this to have a take yet” without feeling like they’ve revealed a weakness, because that kind of admission is often the starting point for the best collaborative thinking we’ll do.
Share our own expertise.
An information village is reciprocal. Whatever our background or professional experience, there’s likely an area where we bring something others in our network don’t have. That contribution doesn’t have to be domain expertise, either. Maybe we’re the person who reads past the headline to the underlying source material. Maybe we’re the person who slows the group down when everyone is rushing to the same conclusion, the one who asks “Where did this statistic come from?” or “What are we assuming here?” Both deep knowledge and the habit of careful questioning are forms of contribution that make the village function, and the village works because its members give as well as receive.
Audit and maintain.
Our information needs change, and our villages should change with them. A periodic audit means looking at the current state of our information ecosystem and checking for two kinds of problems: gaps and decay.
Gaps are the topics we care about or make decisions around where we don’t have a reliable source or a trusted person informing us. These are the areas where we’re operating on assumptions or outdated information without realizing it. Decay is what happens when sources decline in quality without us noticing. A publication that was rigorous two years ago may have changed ownership or lost key writers or shifted its editorial direction in ways that no longer align with our needs. A relationship that used to be a source of sharp, candid exchange may have gone dormant. Decay is subtle because it happens gradually, and the sources that have degraded are often the ones we stop actively evaluating because we already decided to trust them at some earlier point.
Beyond gaps and decay, it's also useful to look for passivity: the accumulation of subscriptions and follows and feeds we signed up for in a different context or mindset but never revisited or cleared out. An audit helps distinguish between the information we’re intentionally relying on and the information that’s just lingering from an older version of our attention. The goal is to make sure the ecosystem we’ve built still reflects our current needs and current standards rather than the ones we had years ago.
Building the village is one half of the equation. The other half is understanding how village practices relate to the diet practices that many of us already have in place, because the two models aren’t in competition — they do complementary work instead.
The relationship between the two models
The information diet and the information village work at different levels of the same problem. The diet sharpens individual capacity, while the village extends that capacity into territory no single person can cover alone. The most effective information practice draws on both, and understanding where each one is strongest helps clarify how they complement each other.
At the individual level, the diet model asks: what am I consuming, and is it serving me well? These questions build the foundational skills of media awareness and source evaluation that make us more discerning readers and more careful sharers of information. Someone who has developed strong individual information habits brings sharper judgment to every conversation and every recommendation they make within a village.
The village model operates at the level of relationships and shared infrastructure. It asks: who do I think with, and what systems have I built for staying informed that don’t depend entirely on my own capacity? The diet model doesn’t address these questions, because its unit of analysis is the individual consumer. The village model recognizes that every person, no matter how disciplined, will encounter questions that exceed their own expertise, and that the quality of their information environment depends on the quality of the relationships and structures they’ve built around themselves.
The diet model is strongest in sharpening personal discernment, helping us become more aware of our consumption patterns and more intentional about where we spend our attention. Where it runs into limits is in situations that require knowledge or perspective beyond what any one of us can hold on our own, like a breaking news event that crosses multiple domains of expertise or a scientific study whose methods require specialized training to evaluate.
The village model is strongest in extending our evaluative range beyond our own knowledge, turning the question “Is this reliable?” from a solo research project into a collaborative one where different people contribute different lenses. Where it runs into limits is when the relationships within the village lack candor or intellectual diversity, which can turn a village into a closed loop that reinforces existing beliefs rather than testing them.
Each model is strongest when paired with the other. The diet without the village produces isolated individuals trying to do institutional-scale evaluative work on their own, consuming carefully but lacking access to the perspectives and knowledge that would make their evaluations more complete. The village without the diet produces a group of people sharing and amplifying material that none of them have individually scrutinized, creating the appearance of collective wisdom without the foundation of individual rigor beneath it.
The two models differ in structure, but they share a common assumption: that the quality of our information environment is something we can actively shape rather than passively endure. The diet model shapes that environment by removing low-quality inputs and managing the volume of what comes in. The village model shapes it by building the relationships and shared systems that make evaluation a collaborative process rather than a solo one. Moving from diet to village means keeping the protective habits the diet provides while investing new energy in the relational infrastructure the village requires.
Moving from diet to village
The transition is less about abandoning old habits and more about building new infrastructure around them. The diet skills remain, and they become the foundation for a broader set of practices that are relational rather than purely individual. If the diet is about what we consume, the village is about what we build, and the shift between them is a shift in where we invest our energy. That shift tends to follow a few consistent patterns:
From solo filtering to shared filtering. The diet model asks us to evaluate every piece of information on our own. The first step toward a village is identifying the areas where we consistently feel uncertain and then finding a person or source we trust in that specific domain. This doesn’t require building a new relationship from scratch. It might mean paying closer attention to who in our existing network has demonstrated strong judgment on a particular topic, and then making a deliberate choice to consult them when something in that area comes across our feed that we can’t evaluate alone.
From passive consumption to active contribution. In the diet model, we’re consumers. In the village model, we’re participants. That transition means recognizing that we have expertise and perspective that other people in our network don’t, and that sharing what we know when it’s relevant is part of maintaining the ecosystem. If we read a primary source and notice that the headline circulating about it is misleading, saying so in our group chat or sending a note to a friend isn’t just helpful to them; it’s how the village gets built, one small act of shared evaluation at a time.
From algorithmic discovery to curated commons. The diet model tells us to resist the algorithm. The village model gives us something to put in its place. Creating a commons, which can be as simple as a group chat where trusted people share what they’re reading or a shared document where we collect reliable sources, means building an alternative channel where recommendations are filtered through human judgment rather than engagement optimization. The more people contribute to a shared commons, the broader and more diverse the recommendations become, and the less dependent any one person is on algorithmic discovery for finding new material.
From individual boundaries to collective standards. The diet model asks us to set personal limits on our consumption. The village model asks us to develop shared expectations with the people we think with. This can be as simple as a mutual agreement that we’ll tell each other when we think the other is wrong, or a norm within a group chat that we’ll flag the source when we share a claim rather than just sharing the claim itself. These collective standards create a kind of distributed quality control that no individual filter can replicate.
From periodic detox to ongoing maintenance. The diet model tends to frame information management as a cycle of overload and retreat: consume too much, feel overwhelmed, disconnect, repeat. The village model replaces this cycle with ongoing, low-level maintenance of the ecosystem itself. That means periodically checking our resource hub for sources that have drifted or degraded, noticing when a relationship that used to provide sharp thinking has gone dormant, and clearing out the passive subscriptions and follows that no longer serve us. The goal isn’t to achieve a perfect state and hold it, but rather keeping the ecosystem responsive to our actual needs as they evolve.
Each of these shifts is small enough to start with a single conversation or a single shared link. But taken together, they represent a fundamentally different orientation toward the problem of information quality, one that treats staying well-informed as something we do with other people rather than something we do by ourselves. And that reorientation has implications that go beyond any individual practice or habit.
What we’re building when we build a village
The reason this reorientation matters is that the dominant advice for navigating a complex information environment — tighten individual filters! set boundaries around consumption! — has been the prevailing advice for over a decade. This advice has produced some good habits and certainly some useful tools. But it’s also produced an implicit expectation that every person should be capable of navigating the full complexity of the modern information landscape armed with nothing but our own judgment and a list of approved sources.
The institutions that used to share the weight of this navigational work, the libraries and newsrooms that filtered and verified and contextualized information before it reached us, have weakened considerably over the past two decades. And the platforms that filled the space they left behind were designed to optimize for engagement rather than accuracy. So the result is that we've been left doing institutional-scale evaluative work as individuals, without the infrastructure those institutions once provided.
The skills the diet model builds, as useful as they are, will always have a ceiling when practiced in isolation. We can sharpen our personal discernment to a fine edge and still encounter a study that’s difficult to evaluate or a news event we can’t contextualize or a claim that sits in a domain where we have no footing. These moments aren’t failures of discipline. They’re the natural boundaries of individual knowledge, and a village is what connects us to people and sources on the other side of those boundaries.
The raw materials for building a village are already present in most of our lives. We already have people whose thinking we trust on specific subjects, and we already have sources that have proven reliable over time. The shift is in connecting these relationships and sources into a deliberate ecosystem, one we actively maintain and can draw on consistently.
The dominant conversation about information quality for the past decade has centered on a single question: “What should I consume?” That question taught us to curate our feeds, set boundaries on our consumption, and pay closer attention to the sources we rely on. But it left us doing the work of evaluation alone. The question that takes us further is: “What should we build together?”
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This resonates, and one piece worth adding: the diet model treats information overwhelm as a quantity problem, but what people are actually metabolizing is dysregulation. A nervous system in chronic activation can't evaluate sources well no matter how disciplined the consumption. The village works partly because co-regulation does what solo filtering can't. Thinking with someone you trust isn't just intellectual. It settles the body enough to think clearly in the first place. Capacity, not just curation.
Hana, I 2nd the praise above. You, Drey, n Huey r my faves in substack .
That’s some good company ! I wish your commentary were a mandatory read the 2nd year of high school.
It would save a lot of young people from mistakes they will make because of not understanding the present systems in place designed to mislead ( corrupt ) them to put it mildly !