Information Is Everywhere. Evidence Is Becoming Rare

The Big Orange Planet Journal-002

16 minute read

Information has become effectively infinite while certainty has become remarkably rare. We have built extraordinary systems capable of producing answers in seconds, summarizing entire industries before coffee finishes brewing, translating languages instantly, generating software, writing legal clauses, designing marketing campaigns and explaining concepts that once demanded years of study. Every advancement has made knowledge appear more accessible than ever before.

Yet I find myself trusting less of what I read than I did twenty years ago.

That sounds backwards until you separate information from evidence.

The internet has never had a shortage of information. Artificial intelligence has multiplied that supply beyond anything previous generations could have imagined. What has become scarce isn't content. It's proof. It's context. It's the accumulated experience that allows someone to distinguish between something that merely sounds correct and something that has repeatedly survived contact with reality.

Those two things are not remotely the same.

I've spent most of my professional life building websites, helping businesses establish credibility online, improving search visibility, documenting organizations and watching the internet evolve through wave after wave of technological change. During that time I've witnessed the arrival of search engines, social media, smartphones, cloud computing, algorithmic ranking, machine learning and now generative AI. Every one of these developments promised easier access to knowledge, and in many respects they delivered exactly that. But they also produced an unintended consequence that grows more obvious every year: we became exceptionally good at creating information while quietly losing many of the systems that once validated it.

That distinction matters more than ever because modern technology has made plausibility incredibly cheap.

A paragraph no longer needs an author who has lived through the experience being described. A business article no longer requires someone who has actually built a business. A travel guide can be assembled without visiting the destination. Software documentation can be rewritten by someone who has never maintained a production server. Medical summaries can be generated from existing publications without any direct clinical experience. Individually, none of these developments is necessarily dishonest. Collectively, however, they produce an environment where polished language increasingly disguises the absence of firsthand knowledge.

The result is an internet filled with explanations that resemble evidence while containing remarkably little of it.

This isn't really an AI problem.

AI simply exposed a weakness that had already been developing for years.

Long before large language models arrived, search engines rewarded scale. Publishing accelerated. Marketing departments measured volume. Websites expanded because more pages frequently meant more opportunities to attract visitors. Content strategies became industrialized. Entire industries emerged around producing articles optimized for algorithms rather than readers. Expertise gradually became something that could be simulated through formatting, citations and confidence rather than demonstrated through accumulated experience.

Artificial intelligence merely made that process faster.

The real challenge is philosophical rather than technological. We have quietly begun confusing the availability of information with the existence of knowledge. They're related, but they are not interchangeable.

Knowledge is what remains after ideas have been tested repeatedly against reality.

Evidence is what survives after convenient explanations fail.

Judgment is what develops when experience refuses to behave like theory.

Those qualities cannot simply be generated because they depend upon something much slower than computation. They depend upon memory.

Not computer memory.

Human memory.

Institutional memory.

Historical memory.

The memory of organizations that remember why decisions were made. The memory of professions that preserve mistakes instead of repeating them. The memory of individuals who understand not merely what happened, but why it happened and what changed afterwards.

I've become increasingly convinced that memory is one of the least appreciated assets any organization possesses.

Every business accumulates thousands of small decisions that never appear in annual reports or marketing materials. Why one supplier was replaced. Why a particular process failed three years ago. Which software migration created unexpected problems. Which customer complaint revealed a deeper structural weakness. Why certain policies exist despite appearing inefficient on paper. None of those decisions looks especially significant in isolation. Together they become the operating system of the organization itself.

Lose that history, and every generation begins solving the same problems from the beginning.

The irony is difficult to ignore. We live in an age obsessed with preserving digital information while simultaneously allowing experiential knowledge to disappear almost unnoticed. Companies archive millions of emails yet fail to document why major strategic decisions succeeded or collapsed. Teams store every presentation ever created while quietly losing the people who actually understand what those presentations represented. Files survive. Context vanishes.

I've seen this happen repeatedly while working with businesses rebuilding or redesigning their websites. Technical documentation often exists. Server credentials can usually be recovered. Databases can be restored. What frequently cannot be recovered is the reasoning behind years of accumulated decisions. Why was this system built this way? Why was this customer journey abandoned? Why does this process look unnecessarily complicated? Someone once knew the answer, but they retired, changed jobs or simply never wrote it down.

The organization remembers the outcome but forgets the evidence.

That's an increasingly dangerous way to operate because artificial intelligence excels at reconstructing visible information while remaining almost completely dependent upon whatever evidence humans chose to preserve in the first place.

This is why I believe documenting experience has become strategically more valuable than documenting information.

Information changes constantly.

Experience compounds.

One tells us what appears true today.

The other tells us what reality has repeatedly demonstrated over time.

Businesses that understand this difference are quietly building an advantage that has very little to do with technology itself. They're recording case studies instead of merely announcing services. They're preserving project histories instead of deleting them after launch. They're encouraging experienced employees to explain why decisions evolved rather than simply listing final procedures. They're building internal knowledge bases that capture judgment instead of merely documenting tasks.

That distinction may seem subtle today.

I suspect it will become one of the defining competitive advantages of the coming decade.

It's one reason I've argued for years that a company's website should be more than an online brochure. A website isn't simply a place to advertise products or collect enquiries. At its best, it becomes the public record of an organization's accumulated thinking. Every carefully documented project, every thoughtful article, every explanation rooted in genuine experience becomes another piece of evidence demonstrating how that organization understands its work. Over time those individual pieces create something algorithms struggle to fabricate convincingly: a coherent history. That philosophy has shaped much of how we approach custom web design, search engine optimization, and long-term brand development, because credibility isn't built by saying you're experienced. It's built by leaving behind a trail of work that allows others to verify it for themselves.

The internet, for all its extraordinary strengths, has always possessed a remarkably short memory.

Search results prioritize freshness. Social platforms reward immediacy. News cycles compress from weeks into hours. Algorithms continually reshuffle visibility based on relevance signals that evolve almost daily. Entire conversations disappear beneath the next update before they've had time to mature. We celebrate acceleration so enthusiastically that permanence often becomes an afterthought.

History, however, has never cared very much about what's trending.

History asks a far less fashionable question.

What actually lasted?

History has an inconvenient habit of exposing fashionable certainty.

Ideas that once appeared beyond question eventually become case studies in misplaced confidence. Technologies celebrated as permanent disappear. Economic theories that seemed mathematically inevitable collapse under the weight of human behavior. Businesses that dominated entire industries become cautionary tales. Medical advice changes. Marketing strategies evolve. Software architectures that were once considered best practice quietly become technical debt. Looking backward, the warning signs often appear obvious, but they rarely felt obvious at the time.

That is precisely why history matters.

History is not simply a record of what happened. It is evidence of what survived.

There's an enormous difference between an opinion that sounds persuasive today and an idea that has remained useful after years of changing conditions. Time performs a kind of peer review that no committee can replicate. Every economic cycle, every technological shift, every unexpected disruption asks the same question: does this still work? Many confident answers quietly disappear under that examination. A surprising number endure.

Artificial intelligence, despite its extraordinary capabilities, has no independent relationship with history. It possesses access to historical material, but access is not understanding. It can recognize patterns across enormous collections of text. It can summarize debates that span decades. It can identify statistical relationships invisible to human readers. What it cannot do is personally distinguish between an observation repeated because it is true and one repeated because enough people copied it.

That distinction belongs to evidence.

Evidence is accumulated reality.

The difference may sound academic until you encounter it in everyday work. I've lost count of the number of businesses that have approached me convinced they needed an entirely new website because someone told them modern design required it. The recommendation usually arrives wrapped in contemporary language. Better user engagement. Improved customer experience. Current design standards. Industry expectations. Sometimes those recommendations are absolutely correct. Sometimes they are remarkably expensive ways of solving the wrong problem.

The interesting part rarely lies in the recommendation itself.

It lies in the absence of historical investigation.

How did customers actually use the existing website?

Which pages consistently generated enquiries?

What changed after previous redesigns?

Which assumptions proved correct?

Which expensive improvements produced no measurable benefit?

Most organizations possess pieces of those answers somewhere, but very few preserve them as an evolving narrative. Instead, every redesign tends to begin as though history started that morning. Teams inherit websites without inheriting the reasoning that shaped them. Consultants produce recommendations without understanding decades of accumulated decisions. New management often assumes visible imperfections reflect incompetence rather than compromises made under conditions no longer remembered.

The evidence disappears while the artifacts remain.

I've come to believe this explains why so many organizations repeat remarkably similar mistakes despite having access to unprecedented amounts of information. They are learning from documentation instead of experience.

Documentation tells you what happened.

Experience tells you why.

Those two forms of knowledge age very differently.

Procedures expire.

Judgment matures.

That distinction becomes even more important in an era where artificial intelligence can produce documentation almost instantly. AI can explain how to configure a server, summarize accounting principles, describe marketing frameworks or generate programming examples with astonishing speed. In many situations it performs those tasks extraordinarily well. Used responsibly, it removes friction from work that once consumed countless hours. I use it myself because refusing useful tools simply because they're new has never struck me as wisdom.

The danger appears when we begin treating generated explanations as substitutes for accumulated understanding.

There's a subtle temptation developing across nearly every profession.

If information can be produced instantly, perhaps expertise itself has become less important.

I suspect the opposite is happening.

Expertise is becoming dramatically more valuable because information has become almost free.

When everyone has immediate access to similar explanations, competitive advantage shifts elsewhere. It moves toward interpretation. Toward judgment. Toward recognizing exceptions. Toward knowing when established rules no longer apply. Toward asking the uncomfortable questions that standardized answers rarely anticipate.

In other words, abundance increases the value of discernment.

We've witnessed this pattern before.

Calculators didn't eliminate mathematicians.

Digital cameras didn't eliminate photographers.

Search engines didn't eliminate researchers.

Each technology automated part of the process while simultaneously increasing the importance of the human qualities surrounding it. Photography became less about operating equipment and more about composition, storytelling and observation. Mathematics increasingly emphasized modeling and problem-solving rather than manual arithmetic. Research shifted toward evaluating sources rather than simply locating them.

Artificial intelligence follows that same trajectory.

The routine becomes easier.

Judgment becomes harder.

This realization has quietly influenced the way I think about publishing online. For years the prevailing assumption was that successful websites simply needed more content. More articles. More keywords. More landing pages. More updates. Scale itself became a strategy because search engines rewarded comprehensive coverage. There was truth in that approach, but only up to a point.

Eventually quantity began competing with credibility.

Thousands of businesses now publish articles that say almost exactly the same thing because they originate from the same pool of publicly available information. Different wording. Similar conclusions. Nearly identical advice. Reading them can feel strangely interchangeable, as though the author matters less than the algorithm assembling the page.

The pieces that continue attracting attention year after year usually possess something else entirely.

They contain memory.

Someone explains what failed before describing what succeeded.

Someone admits uncertainty before offering conclusions.

Someone traces the evolution of an idea instead of presenting the final version as though it appeared fully formed.

Someone leaves enough evidence for readers to reconstruct the reasoning independently.

That is remarkably difficult to fabricate convincingly because genuine history carries imperfections. It includes detours, abandoned assumptions, contradictory observations and inconvenient outcomes. Marketing traditionally tries to smooth those edges away. Experience leaves them visible because they are often the most instructive parts of the story.

Trust has always depended upon that kind of transparency, although we rarely describe it that way.

People don't trust perfection.

They trust consistency.

They trust patterns that remain coherent over time.

They trust organizations whose explanations continue matching observable reality long after the original claims were made.

The same principle applies far beyond business. Scientific credibility depends upon reproducibility. Journalism depends upon verification. Courts depend upon evidence rather than assertion. Engineering depends upon documented testing. Aviation depends upon investigating failures instead of hiding them. Every mature profession eventually discovers the same uncomfortable truth: memory is not an administrative burden. It is infrastructure.

Without memory there is no accountability.

Without accountability there is no reliable evidence.

Without reliable evidence every confident claim begins occupying roughly the same level of credibility.

The Cultural Risk

That may be the greatest risk of our information-rich world.

Not misinformation by itself.

Not artificial intelligence by itself.

Not even the overwhelming volume of content now produced every day.

The deeper risk is cultural.

We may gradually lose the habit of asking where knowledge came from, how it was tested, who observed it, what changed over time and whether anyone bothered to preserve the answers for the people who followed.

Those questions once belonged primarily to historians, scientists and archivists.

Increasingly, I think they belong to all of us.

Because in an age where almost anyone can generate convincing information in seconds, the organizations—and the individuals—that deliberately preserve evidence will begin separating themselves in ways that are difficult to imitate. And that separation has surprisingly little to do with better prompts or faster models. It begins with a quieter decision that is far less glamorous and infinitely more enduring: choosing to remember before the rest of the world forgets.

I don't believe history is becoming less important because artificial intelligence can answer questions.

I believe history is becoming more valuable because AI cannot create it.

It can organize it. It can summarize it. It can compare it, translate it, index it and retrieve it with astonishing efficiency. It can connect ideas that would take a human researcher weeks to assemble. Those capabilities are genuinely transformative. But every one of them depends upon a simple prerequisite: someone, somewhere, had to live the experience first.

That distinction deserves far more attention than it receives.

The internet often gives the impression that knowledge simply exists, waiting to be discovered by anyone who asks the right question. In reality, every reliable source began as somebody's observation. Every engineering standard represents thousands of practical lessons. Every medical guideline reflects years of trials, failures, revisions and validation. Every legal precedent originated with an actual dispute. Every successful business strategy emerged from countless decisions made under imperfect conditions. Before knowledge became searchable, it was experience.

Experience is the raw material from which evidence is made.

That is why I find myself thinking less about artificial intelligence and more about preservation.

For decades, the digital conversation centered on access. We wanted faster search engines, larger databases, cheaper storage and better connectivity. Those goals made perfect sense because information was fragmented. Finding the right document often consumed more effort than understanding it. We solved much of that problem. Access is no longer the primary constraint.

Preservation is.

Not preserving files.

Preserving meaning.

Those are entirely different challenges.

A company can archive every email ever written and still lose its institutional memory. A university can digitize an entire library while quietly losing the professors who understand why certain books mattered. Families can accumulate millions of photographs while forgetting the stories behind the faces. Governments can preserve legislation without preserving the debates that shaped it. Businesses can maintain immaculate project folders while losing the practical wisdom of the people who built them.

Technology excels at storing artifacts.

Humans remain responsible for preserving understanding.

That realization has changed how I think about the work we do every day. Building websites was once viewed primarily as a technical exercise. Pages, code, graphics, databases, servers. All of those components remain important, but increasingly they feel like the visible surface of something much larger. A well-built website is not simply software running on a server. It is an organization's public memory. Every project archive, every thoughtfully written article, every documented case study, every explanation of how a decision evolved becomes another piece of durable evidence that future employees, customers, researchers and even AI systems can learn from. That philosophy sits behind our approach to website development, long-term SEO strategy, and sustainable brand building. None of those disciplines are ultimately about producing more pages. They're about preserving enough authentic history that trust continues growing long after today's technology has been replaced.

That last point matters because technology never stands still.

The internet itself is proof.

I've watched businesses rebuild their websites three, four and sometimes five times over the years. Programming languages evolve. Content management systems rise and fall. Design trends cycle almost predictably. Search algorithms change continuously. Artificial intelligence will change dramatically from where it stands today. Looking back, every generation believed it was using permanent tools. None of them were.

The businesses that endured weren't necessarily those with the newest technology.

They were the ones that continued documenting reality as technology changed around them.

Their websites evolved.

Their evidence accumulated.

Those are not the same thing.

When historians study civilizations, they don't judge them by the sophistication of their filing systems. They examine what those civilizations chose to preserve. Which stories survived? Which records remained trustworthy? Which institutions invested enough effort in documenting reality that later generations could reconstruct what actually happened?

We're creating the equivalent record every single day.

Every published article.

Every project summary.

Every customer testimonial that explains not only the outcome but the process.

Every technical lesson recorded after a difficult migration.

Every mistake documented honestly enough that somebody else won't need to repeat it.

Collectively, those pieces become something much larger than content.

They become cultural memory.

Artificial intelligence will almost certainly become better at generating language than any of us. It will write faster, summarize more efficiently and retrieve relevant information with astonishing precision. Competing against those strengths seems like a poor strategy because machines are designed to excel at exactly those tasks.

But history offers a different lesson.

The technologies that reshape society rarely eliminate the value of uniquely human contributions. They redefine where those contributions matter most.

The printing press didn't eliminate authorship.

Photography didn't eliminate observation.

Computers didn't eliminate reasoning.

Artificial intelligence will not eliminate evidence.

If anything, it raises its value.

The easier it becomes to generate convincing language, the more valuable authentic experience becomes. The easier it becomes to publish polished explanations, the more readers will search for demonstrated credibility. The easier it becomes to imitate expertise, the more organizations will benefit from possessing genuine institutional memory that competitors cannot manufacture overnight.

That may become the defining economic resource of the next generation.

Not data.

Not information.

Not content.

Evidence.

Evidence rooted in lived experience.

Evidence preserved carefully enough that others can verify it.

Evidence accumulated patiently across years rather than assembled quickly across minutes.

For all the conversation surrounding AI, I suspect this quieter shift will prove far more important. We are entering an era where almost everyone can access similar information, ask similar questions and receive remarkably similar answers. The organizations that distinguish themselves will not necessarily possess the largest language models or the fastest publishing pipelines. They will possess something much harder to replicate: a documented history of thoughtful decisions, observable outcomes and accumulated judgment.

In the end, trust has never depended on who speaks the loudest.

It has depended on who leaves behind the strongest evidence.

Perhaps that's the real opportunity hidden beneath all the excitement surrounding artificial intelligence. Instead of asking whether machines can produce more information, we might ask a more consequential question.

What evidence are we creating today that will still deserve to be believed twenty years from now?

That question changes everything because it shifts our attention away from consumption and back toward contribution. Away from producing endless streams of interchangeable information and toward preserving experiences that only real people can live. Away from chasing the next technological advantage and toward building the kind of institutional memory that compounds in value with every passing year.

Conclusion

Information has become abundant.

Evidence has become scarce.

The organizations, professions and individuals that understand the difference will not merely navigate the AI era more successfully.

They will become the sources from which its future knowledge is built.

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This article is the foundation of how we think about websites, AI, search and digital strategy. Over the coming months we’ll expand on these ideas with in-depth articles exploring search, branding, website architecture, local SEO, AI, and what really makes businesses discoverable online.

This article was written by Ally Lennon, Big Orange Planet’s SEO legend—call him directly! Phone: 720-272-0770.  Website Contact