Blog Home

Is Your Content Review Process Falling Behind?

jen@amicredible.ai (Jennifer Best) — Mon, 31 Aug 2026 20:05:10 GMT

You approved that piece eight months ago.

An executive byline. You drafted it, shaped the argument, got the sign-off from legal and leadership. It went live on a trade publication. You moved on.

Then, someone flagged it. A statistic in the third paragraph was off. Not wildly wrong, but wrong enough. The number your CEO cited confidently, in their name, on a site that gets indexed and archived and screenshotted, was slightly off.

The piece is live on a third party website, and now you have to try to issue a correction and minimize the impact to the CEO’s reputation.

If this hasn't happened to you, it's happened to someone you know. And if you've been using AI to move faster on drafts, the odds that something slipped through are higher than they were two years ago.

You're not imagining that pressure. In a 2026 industry survey of 1,400 professionals, PR, media, and communications ranked highest of any sector for misinformation anxiety with 59% citing it as a top concern, against 40% across all industries (LexisNexis, Future of Work 2026). This isn't a niche concern. It's the sector's defining one.

The content lifecycle can be longer than you think

A lot of what we do in communications is built to move fast. Crisis response. Media relations. Social media. Most of it has a short shelf life by design.

Executive bylines don't. Neither do white papers, op-eds, contributed articles, or the LinkedIn essays you ghostwrite for your leadership team. That content goes into the permanent record: indexed, searchable and attached to real names. It doesn't expire when the news cycle moves on.

In some cases, the impact of inaccurate information can be damaging professionally and personally.

Roughly 83% of pages that get indexed are indexed within the first week of publication (Onely research.) Once indexed, content can persist in search results for years, even after deletion, through caching, archiving, and third-party reproduction.

Most of us know this. We feel the weight of it every time something goes out under a C-suite name. What's shifted is how much of that content we're now expected to produce, and how much of the first draft is coming from a tool that generates confident-sounding prose whether or not the underlying facts hold up.

Don’t mistake polish for accuracy

AI-assisted drafts have a particular quality that makes fact-checking harder, not easier. The writing sounds polished. The statistics look specific. The sourcing feels authoritative. Nothing flags as obviously wrong, so you read for tone and clarity and flow (which is exactly what you're trained to do) and the number that's slightly off, or the study that doesn't quite say what the draft implies it says, slips right through.

If this feels familiar, you aren’t alone. More than a third of PR and Communications professionals (36%) say they struggle to verify whether an AI tool's output is based on high-quality sources, and 32% say they can't reliably identify a hallucination or an incorrect output when they see one (LexisNexis, Future of Work 2026). That's not a knock on the profession, it's a resourcing gap. Communicators are being asked to ship more content than ever, with less training on how to use AI tools or to catch what they get wrong.

In 2024, a reporter at a small Wyoming newspaper resigned after his published articles were found to include AI-generated fabricated quotes and stories.

In New York, when two lawyers filed a court brief with fake cases generated by ChatGPT, a federal judge sanctioned and fined them $5,000 each.

The issue is not a failure of attention. It's that the output doesn't look like something that needs the kind of scrutiny it actually needs.

Most comms teams have developed some version of a review process. You read it carefully. You Google the stats that feel off. You loop in a subject matter expert before anything goes under a senior leader's name. That works until you're managing more volume than that process was built for. 62% of PR professionals say they use genAI tools without approval because deadlines won't wait, and of those respondents, 61% say it comes down to needing the efficiency (LexisNexis, Future of Work 2026). The pressure isn't hypothetical. It's the daily condition most teams are already operating under.

Why AI content needs a credibility review, not just an editorial review

If a factual error makes it into a piece under your CMO's byline and someone (a reporter, a regulator, your own leadership) asks what the review process looked like, the answer matters. Not just for the correction conversation, but for what it says about how your function operates.

The professionals carrying the most risk right now usually aren't the ones being careless. They're the ones running a rigorous manual process that's continually outpaced by what they're being asked to produce. The gap isn't effort. It's infrastructure.

Some in-house comms teams are starting to build a more formal credibility review into their workflow. A documented step, not just a careful read. This isn't an argument against AI in your content process. Used well, it makes good communicators more productive.

It's an argument that the output of AI-assisted work needs a different kind of review than the output of human-drafted work - one that specifically evaluates factual accuracy, source credibility, the precision of claims, and whether the content is supported by context that can hold up to scrutiny.

That's not what a spellchecker does. It's not what an editor does when they're reading for voice and flow. It's a different function, and right now most content workflows don't have it. Tellingly, when the same LexisNexis research asked leaders across industries what actually builds trust in AI-assisted content, the top answers were transparent data sources (45%) and human oversight (41%). It’s clear they are looking for a structural layer that makes sourcing visible and keeps a person in the loop. That's the core function of a credibility review.

How to build an effective credibility review layer into your workflow

It doesn't require a new approval chain. It requires a different kind of checkpoint, one that's separate from your editorial review and focused on a specific set of questions.

1. Separate the credibility review from the copy review. Reading for voice, clarity, and flow is not the same as reading for factual integrity. Most review processes conflate them. When you read a polished draft looking for tone, your brain fills in meaning. For example, a number that sounds plausible reads as correct. The key is to treat them as two distinct passes, done by two different sets of eyes if possible. The credibility pass happens after the draft is clean, not during it.

2. When AI is generating the first draft, flag every factual claim before the review. Before the credibility pass begins, go through the draft and mark every number, study, name, title, date, or attributed claim. Not to check them yet, just to make them visible. Flagging first means your reviewer isn't simultaneously hunting for claims and evaluating them. It slows down one step to speed up the actual verification.

3. Verify every claim against a primary source, not the AI's citation. AI-generated drafts often cite sources that exist but don't say what the draft implies they say. The original study may be from a different year, a different population, or a narrower finding than how the statistic was written. If you can't pull up the primary source and confirm the specific number or claim, it doesn't go out under your executive's name. This is the standard. Write it down so it's not subject to time pressure.

4. Build a content register for anything published under a named executive. A simple log: piece title, publication, date, the claims that were verified and against what. Two reasons. First, if a question arises six months later, you have a paper trail for your review process. Second, it creates accountability in the workflow — people fact-check more carefully when they know they're signing off on something documented.

5. Document a repeatable process. Not every piece of content will take the same amount of time to review. A short LinkedIn post and a white paper distributed to a regulated-industry client will take different amounts of time and involve varying levels of complexity. Define the process explicitly for the various types of content that you create and the time it should take to complete the credibility review for each category.

6. Build in a lag between draft completion and publication. The hardest credibility errors to catch are the ones you're staring at when you're tired and behind deadline. A minimum 24-hour buffer between "draft final" and "approved to publish" for high-stakes pieces creates the breathing room to catch what the first three reads missed. It also gives you time to pull a source you meant to verify and didn't.

None of this eliminates the risk entirely. What it does is make the risk manageable and, critically, documented, which matters both for preventing errors and for explaining your process if one makes it through anyway.

The volume of executive content isn't going down. The tools generating first drafts aren't getting less confident-sounding. The permanent record keeps accumulating. A credibility layer in your workflow isn't a hedge against worst-case scenarios. It's standard operating infrastructure for the job communications teams are now doing.

The piece you approved 8 months ago is probably still live somewhere. The question worth sitting with is, if there had been a misquote or error, whether your current process would have caught it, and whether you could demonstrate that it did.

Ready to improve your content workflow? Join our early adopter program and see exactly how a credibility layer can help your team.

Media Literacy: What It Is and How to Practice It

jen@amicredible.ai (Jennifer Best) — Tue, 11 Aug 2026 14:30:00 GMT

Key Takeaways:

Media literacy is the ability to access, analyze, and evaluate media in all its forms.
Media literacy is about having a reliable process for verifying accuracy and deciding what deserves your trust. Information is moving faster than our collective ability to evaluate it. That's also exactly the environment where misinformation thrives.
To demonstrate media literacy, focus on neutral phrasings and search a topic more than one way, including with words you wouldn't naturally reach for, before deciding what the internet has to say about it.

We have all heard the term "media literacy", but how many of us can actually define it? And, if we can’t define it, how can we practice this crucial skill?

As the rise of AI generated content exacerbates the existing misinformation crisis, media literacy is becoming the crucial difference between navigating the current information environment on purpose and just getting swept along by it.

So, what is media literacy, and how do we practice it? Keep reading to find out.

What Does Media Literacy Actually Mean?

Media literacy is the ability to access, analyze, evaluate, and create media in all its forms, from news articles and social posts to videos, ads, and podcasts.

Break that down and it's really four separate skills working together:

Access: knowing where to find information and how different platforms shape what you see
Analyze: understanding who made a piece of content, why, and what techniques they used to do it
Evaluate: judging whether a claim, source, video, image or story deserves your trust
Create: understanding your own responsibility when you produce or share content

Something important to remember is that media literacy doesn't mean distrusting everything you read. It means knowing how to ask the right questions before you decide what to believe, share, or act on.

Think of it like financial literacy. Being financially literate doesn't mean assuming every bank is a scam. It means understanding interest rates, budgets, and risk well enough to make good decisions with your own money. Media literacy works the same way, except the currency is information.

Why Does Media Literacy Matter?

Media literacy has always mattered, but the case for it has gotten a lot stronger in the last decade. As The Stanford History Education Group put it:

“Reliable information is to civic health what proper sanitation and potable water are to public health. A polluted information supply imperils our nation’s civic health.”

Let’s start with the research on how well people actually do this. The Stanford History Education Group has spent years testing whether students can perform basic tasks like telling a news story apart from an ad, or judging whether an anonymous online source is reliable. Their most recent nationwide assessment, run with over 3,400 high school students across 14 states, found little improvement since their first study back in 2016. The majority of students still struggled with nearly every task researchers gave them.

This issue is not exclusive to high school students. A national survey from Boston University's College of Communication found that nearly three in four Americans say media literacy skills matter given how much misleading information is out there. But when researchers asked people if they actually knew where to find good media literacy training, fewer than half said yes. People know the skill matters. They just don't know how to build it.

The gap shows up again in how people handle AI-generated content specifically. The same survey found most Americans are interested in learning to spot false information, and that interest jumps even higher when the question is about content generated by AI. People sense that the ground is shifting faster than their skills can keep up.

As of the most recent tracking from Media Literacy Now, 25 states have some form of media literacy law on the books, and public support for requiring this kind of education runs high across surveys. The demand is there, but the infrastructure to meet it is still catching up, which means for now the onus is on us as individuals to take responsibility for our own media literacy.

Put it together and the picture is clear: information is moving faster than our collective ability to evaluate it. That's also exactly the environment where misinformation thrives, because misinformation depends on people accepting a claim before they've had the chance, or the tools, to check it.

The Core Skills of a Media-Literate Reader

If media literacy is the goal, here are some specific skills to help you achieve it.

Question the Source and the Motive

Before you evaluate a claim, evaluate the reason it exists. Who made this, and what were they trying to do? Inform you, persuade you, entertain you, or provoke a reaction strong enough that you'd share it without thinking? A lot of content is built to do the last one, and once you start asking the motive question, you might just be surprised what you start to notice. This step is ultimately a credibility check, and good news: we wrote more about how to evaluate the credibility of a claim on our blog.

Read Laterally, Not Just Deeply

Most people evaluate a claim by staring harder at the page it's on: rereading the article, checking if the writing sounds credible, looking for a bio. That's called reading vertically, and it's the wrong direction. Media literacy researchers recommend reading laterally instead: open a new tab and see what other credible sources say about the same claim before you decide what to believe. Fact-checkers work this way for a reason. It's faster and far more reliable than trying to judge a page in isolation.

Diversify Where Your Information Comes From

If every source in your feed leans the same direction, or comes from the same platform, you're not really cross-checking anything, you're just hearing the same take repeated. Deliberately pulling from a mix of outlets, formats, and perspectives gives you something to compare claims against. Without that mix, you have no way of knowing if something is broadly reported or just loud in one corner of the internet.

Watch Your Own Bias, Not Just the Source's

It's easy to scrutinize information that challenges what you already think, and just as easy to wave through information that confirms it. This is known as confirmation bias, and it's one of the most common reasons people share things that turn out to be false. The stuff that feels most obviously true to you is exactly the stuff worth a second look.

Evaluate the Data, Not Just the Headline

Numbers get used to make almost any argument look airtight. Before you accept a statistic, ask a few questions: How was it measured? What's the sample size? Is there a credible methodology behind it, or is it just a number floating in a sentence with no source attached? A stat with no visible methodology deserves the same skepticism as a quote with no visible source.

Know What You're Up Against

Search engines and social platforms aren't neutral librarians. They're ranking content based on engagement, not accuracy, and the keywords you search with will shape what you're shown.

The phrasing of your search matters more than most people realize. Media literacy researcher Francesca Tripodi points out that the exact words you type can hand you a one-sided answer before you've read a single result. Search "NFL ratings down" and you'll get a different set of stories than if you search "NFL ratings up," even though both searches are trying to answer the same underlying question. The same holds for loaded topics like immigration: searching "undocumented workers" versus "illegal aliens" returns two noticeably different frames on the same issue. This happens on every major search engine, not just one.

The good news is that the fix isn't complicated: focus on neutral phrasings and search a topic more than one way, including with words you wouldn't naturally reach for, before deciding what the internet has to say about it. If every phrasing you try keeps confirming what you already believed, that's worth noticing rather than treating as proof.

Digital Media Literacy vs. Traditional Media Literacy

Traditional media literacy grew up around newspapers, radio, and broadcast TV. The skills required were largely around understanding editorial structure: knowing the difference between a news story and an editorial, recognizing advertising, and understanding how a handful of gatekeepers decided what counted as news.

Digital media literacy includes all of that, and so much more.

A few things make digital media literacy its own category:

Anyone can publish. There's no editor standing between a claim and an audience of millions. That means the burden of evaluation shifts almost entirely to the reader.
Algorithms decide what you see. Traditional media literacy taught people to think about editorial choices. Digital media literacy requires understanding that a platform's algorithm is also making choices, usually optimized for engagement rather than accuracy.
Content moves and mutates. A quote, image, or statistic can get stripped from its original context and re-shared thousands of times before anyone traces it back to its source.
AI-generated content is now part of the mix. Text, images, and video can be produced convincingly by tools that didn't exist a few years ago, which adds a whole new evaluation step: is this even real?

None of this makes traditional media literacy obsolete. It just means the skill set has to expand to match the environment people are operating in.

How to Improve Your Media Literacy Today

You don't need a course to start building this skill. A few habits, practiced consistently, go a long way. Each one below puts one of the core skills into action.

1. Ask what the content wants from you before you react to it. Content designed to provoke outrage or fear is also the content most likely to skip past your judgment. Before you respond, ask what the creator's motive was: inform, persuade, entertain, or provoke. That question alone changes how much weight you give what follows.

2. Open a second tab before you trust the first one. Don't just reread the page you're on. Search the claim itself and see what other credible sources say about it. If nobody else is reporting it, or if credible outlets are contradicting it, that's more useful information than anything on the original page.

3. Try the search a different way. Before you accept what a search returns, run it again with different phrasing, including words you wouldn't naturally reach for. If every version of the search keeps agreeing with what you already thought, that's a sign to dig further, not a sign you were right.

4. Notice when something confirms what you already believe. That's exactly the moment confirmation bias is easiest to miss. Content that lines up perfectly with your existing views deserves the same scrutiny as content that challenges them, not less.

5. Check the methodology behind the number, not just the number. Before you accept a statistic, look for how it was measured and how large the sample was. A number with no visible source or methodology should carry less weight than one that shows its work.

6. Rotate your sources on purpose. If you only ever get information from one outlet, one platform, or one type of media, you're not cross-checking anything, you're just hearing it repeated. Make it a habit to pull from a mix of credible sources on any topic that matters to you.

None of these steps require special tools or training. They just require deciding, on purpose, to slow down before you accept, react to, or share a claim.

Remember, media literacy isn't about becoming suspicious of everything you read. It's about having a reliable process for verifying accuracy and deciding what deserves your trust. That process starts with the habits above, and it gets sharper the more you use it.

In the words of the late U.S. Sen. Daniel Patrick Moynihan:

“Everyone is entitled to his own opinion, but not his own facts.”

Media Literacy FAQ

Is media literacy declining? The research suggests it's less that media literacy is getting worse and more that the information environment is outpacing the skills most people were taught. Stanford's ongoing assessments show students today struggle with roughly the same tasks students struggled with in 2016, even as the volume and speed of information has grown substantially. The skill gap hasn't necessarily widened. The stakes of that gap have.

Should media literacy be taught in schools? Public support for this is high. Surveys from groups including the Reboot Foundation and the News Literacy Project consistently find strong majorities in favor of required media literacy education, and a growing number of states have passed legislation addressing it. The bigger challenge right now isn't convincing people it matters. It's building consistent, well-resourced instruction that actually closes the skills gap.

Is media literacy the same as fact-checking? No. Fact-checking is one specific task: verifying whether a particular claim is true. Media literacy is the broader set of skills that includes fact-checking but also covers source evaluation, bias recognition, understanding how algorithms shape what you see, and knowing how to create and share content responsibly.

Can adults improve their media literacy, or is this mainly a school subject? Adults can absolutely build this skill, and the research suggests many want to. The habits outlined above (pausing before sharing, checking sources, looking for corroboration) work at any age and don't require a classroom.

How is AI changing media literacy? AI adds a new evaluation step that didn't exist a few years ago: determining whether content is even genuine before you evaluate whether it's true. Text, images, and video can now be generated convincingly enough that traditional signals of authenticity, like production quality or writing style, are no longer reliable on their own. Surveys show public concern about this is high, and interest in learning to spot AI-generated misinformation is even stronger than interest in spotting traditional misinformation.

Sources:

Breakstone, J., et al. Students' Civic Online Reasoning: A National Portrait. Stanford History Education Group, 2019.

Wineburg, S., & McGrew, S. Lateral Reading: Reading Less and Learning More When Evaluating Digital Information. Stanford History Education Group Working Paper No. 2017-A1.

Boston University College of Communication. Media Literacy Skills Important to Counter Disinformation, Survey Says, 2024.

Media Literacy Now. Current Policy: U.S. Media Literacy Laws by State, 2026.

Media Literacy Now and Reboot Foundation. National Survey Finds Most U.S. Adults Have Not Had Media Literacy Education in High School, 2022.

News Literacy Project. News Literacy in America: A Survey of Teen Information Attitudes, Habits & Skills, 2024.

The University of North Carolina at Chapel Hill, How to improve your media literacy skills, 2021

What Is Misinformation? A Practical Guide to Spotting and Stopping It

dan@plancllc.com (Dan Nottingham) — Mon, 27 Jul 2026 16:22:59 GMT

Somewhere right now, someone is hitting "share" on something that isn't true. They're not doing it to deceive anyone. They just believed it, felt something about it, and passed it along the way you'd pass along a good recipe or a funny video.

That's misinformation. And it's a lot more common, and a lot less sinister, than most people assume.

This guide breaks down what misinformation actually is, how it's different from disinformation (the two get confused constantly), why false information sticks in our brains even after it's been corrected, how it spreads so effectively on social media, and what you can do about it before you're the one hitting share.

What Is Misinformation?

Misinformation is false or inaccurate information that's shared without the intent to deceive. The person sharing it usually believes it's true. Maybe they read a headline that sounded good, but got the facts wrong. Maybe they misremembered a statistic. Maybe a well-meaning friend forwarded something in a group chat that felt too important not to pass along but forgot to verify it first.

Misinformation isn't defined by malice. It's defined by inaccuracy. Someone can spread misinformation with the best of intentions and still do real damage, because the information itself is wrong, regardless of the person’s intention when sharing it.

Common sources of misinformation include:

Outdated information that was once true but no longer is
Satire or parody that gets taken out of context and shared as fact
Honest reporting errors that spread before a correction catches up
Misremembered or garbled statistics ("I read somewhere that...")
Screenshots and quotes stripped of the context that would help explain them

The common thread is simple: the information is wrong, but the person sharing it isn't lying. They're just wrong, and they don't know it.

Misinformation vs. Disinformation: What’s the Difference?

Sometimes, we hear the terms misinformation and disinformation used interchangeably. However, there is a small nuance between the two that has a huge impact on what they actually mean.

Misinformation is false information shared without intent to deceive. The person sharing it believes it.

Disinformation is false information created or shared deliberately to deceive. The person sharing it (or the person who created it) knows it's false, or at least doesn't care whether it's true, and spreads it anyway to manipulate opinion, drive engagement, or push an agenda.

Here's a simple way to remember the difference: misinformation is an honest mistake. Disinformation is a strategy.

The tricky part is that disinformation often becomes misinformation once it starts spreading. Someone creates a fabricated story on purpose (disinformation). A stranger reads it, believes it, and shares it with their own network without knowing it was fabricated (now it's misinformation, at least from that person's side of things). The same piece of false content can have two very different intentions depending on who's sharing it.

This is exactly why the "just don't lie" advice doesn't solve the problem. Most people spreading false information aren't lying. They're relaying something they think is true. The fix isn't a lecture about honesty. It's a habit of checking your information before sharing it.

The Misinformation Effect: Why False Information Sticks Even After It's Corrected

The most frustrating part about misinformation is that correcting it doesn't reliably erase it from someone's memory. This is known as the misinformation effect, and it describes how exposure to false or misleading information after an event can distort a person's memory of the original event, sometimes even after they've seen the correction.

Psychologists have studied this for decades, and the pattern holds up: once a false detail gets planted in someone's understanding of a situation, simply telling them "actually, that's not true" doesn't fully remove it. The original claim often lingers, especially if it was emotionally charged or confirmed something the person already believed.

There are a few reasons this happens:

First impressions are sticky. The first version of a story a person encounters tends to anchor their understanding of it, even if a more accurate version comes along later.
Corrections often get less attention than the original claim. A viral post gets seen by thousands. The correction three days later gets seen by a fraction of that audience.
Repetition builds familiarity, and familiarity feels like truth. The more times someone encounters a claim, even while debunking it, the more familiar it feels, and familiarity is often mistaken for accuracy.

This is one of the reasons that simply yelling "that's false" at someone online rarely works. It's not because people are stubborn (though sometimes they are), it's because contradicting a belief head-on doesn't automatically dislodge it. If you want a more effective approach to actually shifting someone's mind, our piece on how to challenge misinformation walks through what tends to work instead. Spoiler alert: leading with evidence tends to be more successful than confrontation.

How Misinformation Spreads on Social Media

Social media didn't invent misinformation, but it built the perfect delivery system for it. Let’s take a look at why this is the case:

Algorithms reward engagement, not accuracy. Platforms are built to show you more of what keeps you scrolling, commenting, and reacting. Content that provokes a strong emotional response such as surprise, anger, or fear, tends to get amplified regardless of whether it's true. Truth was never the metric being optimized for.

Speed outpaces verification. A claim can reach thousands of people in the time it takes a single fact-checker to confirm or debunk it. By the time accurate information catches up, the false version already has a head start, and head starts are hard to overcome.

Context gets stripped away. A headline gets separated from its article. A quote gets separated from the interview it came from. A statistic gets separated from its source. Once information is reduced to a fragment, it becomes much easier to misunderstand, and much easier to misuse.

Incidental exposure normalizes claims. Most people aren't actively hunting for news anymore. They're scrolling for something else entirely, and information finds them along the way, often without any indication of where it came from or whether it holds up. When you're not looking for information critically, you're less likely to evaluate it critically.

Echo chambers reinforce beliefs instead of testing them. When a feed repeatedly shows someone content that confirms what they already think, a false claim that fits their worldview can feel more credible simply because it's been encountered so many times, from what feel like so many different directions.

None of this means social media is designed to mislead. It means the incentives built into these platforms don't naturally favor accuracy, so accuracy has to be something individual users must actively look for rather than something they can passively rely on.

How to Spot Misinformation Before You Share

You don't need to become a professional fact-checker to meaningfully reduce the amount of false information you spread. There are a few habits that go a long way.

Pause before you react. If something makes you feel a strong jolt of anger, fear, or vindication, that's exactly the moment to slow down. Strong emotional reactions are the easiest way to bypass critical thinking, and misinformation is often engineered (intentionally or not) to trigger exactly that response.

Check the source. Is this coming from an outlet or account with a track record of credibility, or from an anonymous post with no clear origin? Reputable sources are generally willing to show their work. Vague or missing attribution is a red flag worth taking seriously.

Look for corroboration. If a claim is true and significant, it's rarely reported by only one source. A quick search to see whether other credible outlets are covering the same story can tell you a lot in under a minute.

Read past the headline. Headlines are written to grab attention, not to summarize nuance. The actual article often complicates, qualifies, or even contradicts what the headline implies.

Check the date. A surprising amount of misinformation is just old news being recirculated as if it's happening right now. A quick date check can resolve a claim before you even get to the content of it.

This is also (not coincidentally) the exact gap AmICredible was built to close. Instead of relying on gut instinct or conducting a search you might not have time for, you can input a statement into AmICredible and get a credibility score along with the sourced evidence behind it, allowing you to make that judgment call with actual evidence instead of a hunch. It's the difference between guessing whether something's true and actually checking.

FAQ: Quick Answers on Misinformation

Is spreading misinformation a crime? Generally, no. Sharing false information without the intent to deceive isn't illegal in most cases, since misinformation by definition lacks malicious intent. Disinformation, particularly when it involves fraud, defamation, or specific categories like election interference, can carry legal consequences depending on the jurisdiction and the specifics of the case. But most misinformation, an honest mistake shared in good faith, isn't a legal matter. It is, however, a credibility one.

Why is misinformation a problem if people don't mean to lie? Because impact doesn't depend on intent. False information can shape public opinion, influence decisions, damage reputations, and erode trust in institutions, regardless of whether the person spreading it meant any harm. A rumor doesn't do less damage just because it was well-intentioned.

Can misinformation be corrected once it spreads? Sometimes, but not reliably, and not completely. As covered above, corrections often reach fewer people than the original claim and don't fully erase the impression the false version left behind. This is why prevention (pausing, checking, and verifying before sharing) matters more than cleanup after the fact.

How is misinformation different from an opinion? An opinion is a subjective judgment or interpretation. Misinformation is a factual claim that's false. "I think that policy is a bad idea" is an opinion. "That policy cut funding by 50%" is a factual claim that can be checked, and if it's wrong, that's misinformation.

What's the single best habit for avoiding misinformation? Check before you share. Almost every piece of advice in this guide is really just a version of that one habit: giving yourself a moment between "I saw something" and "I told other people about it." to check the facts.

Sources:

The British Psychology Society, The history of an idea: The misinformation effect, 2025.

Credibility Is the New Brand Currency

jen@amicredible.ai (Jennifer Best) — Tue, 07 Jul 2026 15:00:00 GMT

If you’ve heard the phrase, "Trust is the new competitive advantage," you’re not alone.

And, while I do agree with the sentiment, it has left many marketers wondering how they can build brand trust. The answer is simple: Trust is the outcome. Credibility is how you get there.

I've spent years working in communications, and the most significant shift I've witnessed isn't about platforms or algorithms or even the rise of AI, though some of these things have certainly had an influence. The most significant shift I have witnessed is the steady decline of consumer trust in companies and brands.

How Do Gen Z Evaluate Brand Trust?

Earlier this year, a study from We Are Talker caught my attention. They surveyed 2,000 Gen Z Americans to uncover what influences their trust in brands. The findings, though not too surprising, are a clear indication that current marketing practices will have to shift if brands want to build trust with the new generations.

Customer reviews topped the list of most trusted sources when analyzing brand credibility, cited by 72% of respondents. Independent research and surveys ranked second at 68%, followed by expert opinions at 68%, and news articles at 58%.

You know what came last? PR campaigns, stunts, and branded activations. Only 46% of respondents trusted these sources when evaluating brand credibility.

Let that sink in. The things brands typically invest in the most to build awareness ranked dead last when it came to building credibility. Meanwhile, the sources that audiences trust most are the sources the brands have the least direct influence over.

What we are seeing in these results in not just a Gen Z quirk, but a significant shift in what builds brand trust.

How Do You Measure Brand Credibility?

When most people talk about credibility, they default to a single question: is it true?

But, factual accuracy on its own doesn't make a statement credible. We've all seen them, claims that are technically true, but that were actually deeply misleading. And, we've seen scientifically valid evidence be dismissed entirely based on who delivered the information.

True credibility is multifactorial. At AmICredible, we think about it across four dimensions: factual accuracy, source credibility, statement clarity, and contextual support. You need all four working together for a claim to be truly credible. Miss one, and your whole claim can fall apart.

This matters enormously for professional communicators. Our reputations can be dramatically influenced by whether we are perceived as credible by our audience. So, we often put enormous effort into making sure something is technically accurate, but then we might package it in vague language, strip the context, or lean on a source our audience doesn't trust. The information, though true, becomes misleading, and hurts our credibility rather than boosting it.

The Trust Gap Is Getting Harder to Ignore

The numbers on institutional trust are sobering. We recently wrote about the shifts in the public’s trust in the media. And, what I find even more telling is the 2026 Edelman Trust Barometer which found that 70% of people are hesitant to trust someone with different values, facts, or cultural backgrounds. This finding goes beyond just skepticism of institutions telling the story of a fracturing of shared reality.

And, as Edelman's CEO pointed out, the downstream effects of this "insularity" are serious: resistance to change, a loss of collective capacity to act, and a global erosion of optimism.

For brands, this creates a genuine challenge. People aren't just skeptical of what you say. They're skeptical of whether you're even operating from the same set of facts they are. This is a different problem than bad PR, and it requires a different kind of response.

What Consistent Credibility Actually Looks Like

You don't get to be credible in one campaign and invisible the next. Consistency matters. People notice when the quality varies. They remember when something you said didn't hold up. And with the fragmented, algorithm-driven media environment we're all operating in, a single piece of poorly sourced content can undo months of careful communication.

The We Are Talker study also found that the two things most likely to drive Gen Z to engage with a brand are clear and useful information (37%) and seeing real people talk about it (35%). Neither of those is about polish or production value. Both of them are about substance and authenticity showing up together, consistently.

This is the credibility discipline I think about most. Just doing one brilliant, well-sourced, transparent piece of content is not going to build trust. It is the practice of doing that every time that will build an audience that knows what to expect from you, and trust that you'll deliver it.

The AI Complication

AI has removed virtually every barrier to publishing content. Anyone can now produce polished, well-structured, grammatically perfect copy at scale, with no editorial oversight and no accountability. That's an extraordinary capability, but it is adding to the declining trust problem.

When everything looks professional, surface-level cues stop working as proxies for quality. Audiences can't use "this looks well-made" as a shortcut anymore, so they're reaching for harder-to-fake signals: independent reviews, research backing, expert validation - exactly what the We Are Talker survey found.

This is why I genuinely believe credibility is becoming a primary brand asset, not a supporting one. As AI raises the bar on content quality everywhere, it simultaneously raises the stakes on demonstrating that what you're saying is coming from a human, and grounded in something real.

The brands that will win in this environment aren't the ones producing the most content. They're the ones consistently turning up authentically and credibly.

Where to Start

If you're thinking about how to build credibility more intentionally, here are a few places I'd focus:

Treat independent validation as a strategy, not a bonus. Reviews, third-party research, expert citation, and earned media aren't nice-to-haves. They are, according to the Gen Z audience, the most credible signals you can offer. Build them into your communications infrastructure.
Be transparent about your sources. Not just "studies show" or "according to research." Link to the actual research. Show the work. The more open you are about how you know what you know, the more your audience can verify it. And audiences who verify things and find them correct become your most trusted advocates.
Think about credibility as a four-part question. Before you publish, ask: is this factually accurate? Is it sourced well? Is it clearly stated without being misleading? Does the context support the claim? If the answer to any of those is "not quite," fix it before it goes out.
And finally, be consistent. Not just in quality, but in the standards you hold yourself to. Credibility compounds. So does the erosion of it.

We're at an inflection point in how audiences evaluate what content is worth trusting. The brands that recognize this shift now and build accordingly will have an advantage that will only get harder to replicate.

Does Page Rank Equal Credibility? You Might Be Surprised by the Answer

jen@amicredible.ai (Jennifer Best) — Mon, 15 Jun 2026 14:00:01 GMT

There is something about online search that should bother you more than it probably does:

When you type a question into a search engine or AI model, the results you get back aren't ranked by truth or accuracy. They're ranked by hundreds of visibility signals. Factors like how many other sites link to a page, how long the domain has been around, and how well the content is structured for the algorithm, to name a few. But, it’s what they aren’t looking at is most concerning: Not accuracy, and not credibility.

A major new study by AirOps and Kevin Indig, analyzing 16,851 queries and nearly 354,000 pages, has just confirmed what a lot of us have long suspected: the factors that determine whether a source gets cited have little to do with whether that source is credible and have everything to do with whether it's findable, formatted well, and matches the exact words in your query.

So, what does this mean for how we find information and conduct research?

If it’s cited, it must be credible, right?

We've been conditioned to treat Google as a first resort for facts. Someone makes a claim at dinner. You pull out your phone. You search. You find something. Case closed.

But search results don't tell you whether a source is credible. They only tell you whether a source is visible.

The AirOps study (currently one of the most comprehensive analyses of how ChatGPT retrieves and cites information) found that domain authority and backlinks show no positive correlation with citation rate. In fact, they're slightly inversely correlated. Pages that are always cited by ChatGPT have a lower domain authority (53) than pages that are never cited (56). Sites with three times as many backlinks are actually less likely to get cited.

What this means is that the signals we've been trained to associate with trustworthiness online such as reputation, authority, and reach don't predict whether AI systems will recommend them as a source at all.

So, what does influence AI citations? Retrieval rank. A page at position one in ChatGPT's internal search results gets cited 58% of the time. By position ten, that drops to 14%. A four-times gap based purely on where a page lands in a ranking system.

An additional factor that isn’t often mentioned is the cost involved every time a retrieval happens. Providing updated information comes at a cost, so most AI platforms create logic around when and how often this happens. That means that the content they cite can be cached and out of date.

The bottom line is this: well optimised pages get you cited, credibility doesn't.

Wikipedia as a credibility source? Maybe think again.

Wikipedia is a bit of an anomaly. It achieves the highest citation rate at 59.2% despite having the lowest query match scores. Meanwhile, major news outlets, with high domain authorities and newsrooms full of trained journalists, earn a citation rate of just 32%.This is baffling when Harvard University and other top institutions actually advise against using Wikipedia as a citable source.

Why does Wikipedia get cited more often? The study suggests the answer is its content density. The average Wikipedia page contains 4,383 words, 31 lists, and 6.6 tables. The structural density is so overwhelming that it overcomes a terrible retrieval position. The AI model doesn't care that Wikipedia is written and edited by volunteers with no editorial accountability. It cares that the page is long, well-structured, and exhaustively covers a topic.

The TL/DR? It’s content density and not credibility that is causing Wikipedia to get cited more often.

By comparison, Reddit has a high domain authority, nearly identical to major news outlets. It has a citation rate of 29.9% and is the single largest source when ChatGPT cites sources from memory. That means when ChatGPT answers a question from what it already "knows," it's treating Reddit threads with essentially the same weight it gives to vetted journalism.

ChatGPT doesn't distinguish between a well-sourced news article and a Reddit thread where someone confidently stated something false. It knows which one appeared more frequently in its training data and which one matched the pattern of the question being asked. This highlights the crux of the issue: credibility is not a consideration in ChatGPT citations.

AI Results Rank on Structure, Not Authority

Another alarming finding of the AirOps study is that what gets a page cited is structural, not substantive or factual information.

Pages whose headings closely match the user's query are cited 41% of the time, compared to 29% for weak heading matches. Pages with JSON-LD schema markup (a technical formatting signal invisible to readers) earn a 6.5 percentage point citation advantage. College-level writing (Flesch-Kincaid grade 16-17) outperforms simpler writing because AI models appear to treat linguistic complexity as a proxy for expertise.

None of these signals have anything to do with whether the information is true. The system rewards pages that are precisely formatted to answer one specific question, not pages that have done the deepest, most thorough work.

This isn't a criticism of AI systems for being broken. They're doing exactly what they were designed to do: retrieve and organize information at scale. But, "organizing information at scale" is not the same as "verifying whether information is credible." These are completely different problems, and right now, a lot of people are treating them as if they're the same thing.

Credibility Comes From Authoritative Sources, Not Well-Optimized Ones

Search optimizes for visibility. AI optimizes for fluency. AmICredible optimizes for something different: helping you decide whether a claim is credible.

In AmICredible, you're not getting a ranked list of pages. You're not getting a confident summary assembled from training data that treats Reddit threads with the same weight as peer-reviewed research. You're getting an analysis of whether a specific claim is grounded in sourced evidence, with transparent reasoning you can evaluate and push back on.

What AmICredible does is fundamentally different from what a search engine or an AI assistant does. It is designed to evaluate claims based on four dimensions of credibility, and show you where the evidence comes from. Surfacing sources across the political spectrum that agree on the underlying facts. Flagging when something is misleading even if it technically contains accurate elements. And linking back to the journalism and reporting that underlies the analysis. Credibility doesn't exist in a vacuum, it traces back to the reporters and institutions that did the hard work of verifying information.

Visibility and credibility are not the same. And they shouldn't be confused with each other.

You Can't Outsource Your Critical Thinking

Right now, a lot of people think they're doing their own research when they Google something or ask ChatGPT. But, if the tool you're using rewards heading structure over accuracy, and treats a Reddit thread as a high-authority source because it appeared in training data at the right frequency, you're not verifying the claim. You're just finding more versions of it, delivered confidently.

Real credibility evaluation requires different questions: Who reported this? What evidence supports it? Has it been corroborated? Are sources across the ideological spectrum agreeing on the same underlying facts?

A search ranking is not built to answer these questions. And it's not what an AI summary is built to answer either. But it is what a credibility layer like AmICredible is built to answer.

The AirOps research is a useful reminder that the systems we use to find information were not built to evaluate it. They were built to retrieve it, rank it, and surface it quickly. They do that extremely well.

But citations are not credibility. Heading structure is not accuracy. A high domain authority score is not the same as being right.

The job of evaluating credibility still belongs to us. The question is whether we have tools that actually help us do it.

Sources

AirOps / Kevin Indig (Growth Memo). The Fan-Out Effect: What Happens Between a Query and a Citation, April 2026.
Gallup. Trust in Media Trends, 2025.
Pew Research Center. Americans' Complicated Relationship With the News, 2026.
Harvard University. Harvard Guide to Using Sources.

Credibility Is the New Leadership Standard

dan@plancllc.com (Dan Nottingham) — Wed, 10 Jun 2026 14:30:00 GMT

Something significant is happening to trust right now, and most people with a public platform haven't fully reckoned with what it means for them.

The 2026 Edelman Trust Barometer puts a name to it: insularity, the ignorance of or lack of interest in cultures, ideas, or peoples outside one's own experience.

While Americans’ trust in mass media has steadily declined, audiences haven't responded by becoming more open-minded.

In fact, they've done the exact opposite.

People are retreating into closed information loops. And in a closed information loop, the only voices that get through are the ones already inside. Edelman adds that 70% of people say they are hesitant or unwilling to trust someone who holds different values or approaches problems differently.

If that sounds like a problem, it is. However, for content creators, it's also an opportunity.

The Editorial Filter Is Gone

The fundamental problem isn't that people are sharing misinformation on purpose. Most aren't. The problem is structural.

For most of human history, if you wanted to reach thousands or millions of people, you had to go through some kind of editorial filter. A publisher. A broadcaster. An editor. Someone whose job it was to ask: is this accurate? Is this fair? Does this hold up? With the rise of the internet, that filter is gone.

Today, everyone has access to a worldwide platform to say anything, without review, without accountability, and without the credibility layer (like the editorial filter) that used to be built into the news ecosystem by default.

The result? Misinformation is so prevalent that no one knows what to believe. Deep fake videos and click bait headlines only amplify the issue. Even when facts are presented clearly, they're often dismissed in favor of whichever version of events feels emotionally true to the reader.

That cycle doesn't fix itself. It requires something to replace the accountability that used to come built in.

The Opportunity for Creators

Here's where the opportunity comes in, and it's a significant one.

In her article for Edelman, Sara Rezaee says:

“Creators are not simply content distributors. At their best, they are brokers of trust. They cultivate communities over time, grounded in shared values, lived experience, and ongoing dialogue. Their influence is not derived solely from scale, but from the communities they’ve built.”

Trust is an extraordinary asset. And it comes with an equally extraordinary responsibility.

Because when a trusted voice amplifies something, their audience doesn't just hear the information. They receive it with the implied endorsement of someone they already believe in. That's a powerful thing, especially in an insular information environment.

But the opportunity goes further than simply operating within a community. Trusted creators and high-profile individuals have the rare ability to intentionally introduce new perspectives to their audiences without triggering the resistance that usually accompanies unfamiliar ideas. As Rezaee notes, “while communities may be insular, they are not immovable”. A voice that an audience already trusts can bring in new information, challenge assumptions gently, and help break echo chambers rather than reinforce them.

That is not a small task. In a moment when insularity is accelerating and people are less willing than ever to engage with perspectives outside their own, a trusted voice choosing to lead with credibility and nuance is one of the few forces that can actually move the needle.

The leaders who understand this are already operating differently. They're not just asking "is this interesting?" before they share something. They're asking "is this credible?" and “will this help people?” They're treating their public statements not as casual commentary, but as contributions to the information ecosystem that their audience lives in.

Credibility Is a Leadership Differentiator, Not a Restriction

The most trusted voices in any field, across media, business, politics, and culture, have always been the ones willing to stand behind what they say. They're not the loudest. They're the most consistently reliable.

Here's what's shifting: credibility is no longer just a nice-to-have for people in the public eye. It's becoming the differentiator.

As trust in traditional media continues to fracture, audiences aren't becoming less discerning. They're becoming more so. They're watching who gets things right. They're noticing who corrects themselves when they're wrong. They're paying attention to whether the people they follow treat them as people who deserve accurate information, or just as an audience to be activated.

The leaders who will build the most durable trust over the next decade aren't the ones with the most followers. They're the ones who treat every post, every statement, and every amplified claim as a reflection of what they actually stand for.

Credibility isn't the absence of passion or conviction. It's the thing that makes passion credible and conviction persuasive. In a climate where trust in institutions is at historic lows and audiences are retreating into insular communities, that credibility is rare. And rare things carry value.

Do credibility tools censor content?

Incorporating a credibility layer in the content creation process raises its own share of concerns about censorship. But here’s the reality: it actually increases transparency.

Credibility tools don't tell anyone what to think or what to post. They provide transparent, evidence-based context so that individuals can make more informed decisions before they believe or share. The decision on what to say always belongs to the individual.

What a credibility layer does is restore some of the accountability that evaporated when editorial filters disappeared. It adds a layer of transparency to a world where anyone can say anything, and gives people the tools to understand what they're amplifying before they amplify it.

Credibility Starts Here

If you're ready to lead with credibility, the first step is simple.

Before you post your next piece of content, run it through AmICredible. See how it holds up. Understand what's supporting it, what's missing, and what your audience will be perceiving when they read it.

And remember, although everyone has a platform and almost no one has an editor, the leaders who build lasting trust will be the ones who bring their own.

Sources:
Sara Rezaee, In an Insular World, Trust Is Built and Scaled by Creators, 2026
Edelman, Edelman Trust Barometer Global Report, 2026
Gallup, Trust in Media at New Low of 28% in U.S., 2025

Are AI and GPT’s Credible?

dan@plancllc.com (Dan Nottingham) — Wed, 27 May 2026 14:30:00 GMT

We are living through one of the most significant shifts in how humans interact with information.

For the first time in history, anyone can ask a question and receive an answer that is structured, confident, and remarkably persuasive. Tools like ChatGPT, Claude, and Gemini have fundamentally changed how we search, write, and think. When you pause to think about it, it is genuinely remarkable.

But, there is a subtle problem that is easy to miss.

Why AI is Not Designed to Determine Truth

Most people use these tools as if they are answering one specific question: “Is this true?”
But, behind the scenes, that is not what these tools are designed to look for.

Large language models are not designed to determine truth. They are designed to generate responses that are plausible, coherent, and useful. They predict what a good answer should look like, based on patterns in data, not whether that answer is correct in an absolute sense, let alone whether the answer is credible, misleading or out of context.

This is an important distinction that most people don’t realize. It means the output is not truth, it is plausibility.

Hallucinations Are Not Bugs.

When people talk about hallucinations in AI, they often describe them as bugs or errors that will eventually be fixed. Better models, better guardrails, better everything. Problem solved. But, hallucinations are not simply errors. They are a natural consequence of how these systems work.

If a model is optimized to produce fluent, convincing language, it will occasionally produce statements that sound right but are not well supported by evidence. Even as these systems improve through better retrieval, better tuning, and better safeguards, they still operate under the same fundamental principle: Generate the most plausible response, not the most reliable one.

Plausible is not the same as true, and certainly not the same as credible. And people believing that plausible is the same as true is where the real risk lives.

"Just Ask It Better" Is Not Enough.

A common response to this problem is that it can be solved with better prompting. Ask for sources. Request explanations. Refine the question. And yes,with the right prompt, they can produce thoughtful, even impressive analyses. But it does not solve the underlying issue.

Each interaction is a one-off response, dependent on how the question was phrased, lacking any consistent standard. Two people can ask the same question and receive different answers. The same person can ask twice and get variation.

That is not a reliable system for evaluating information.

Structure is the Missing Key.

The real gap is not intelligence, or the LLM’s themselves. These systems are extraordinarily capable. The gap is structure. More specifically, what is missing is a consistent, repeatable way to evaluate whether something is credible.

In practice, we rarely have access to absolute truth in the moment. What we have are signals: evidence, sources, clarity, and context. We use those signals to decide what to believe. That process plays out every day in journalism, in science, in business, and in conversations.

And yet, AI systems are not designed to evaluate credibility in a structured or consistent way.

Credibility Is Not the Same as Truth.

The distinction between these two terms is important, and where most conversations about AI, and credibility more broadly, get it wrong.

Truth is binary. Something either happened or it didn’t. But truth is also often unknowable in real time. We rarely have perfect, complete information in the moment a decision needs to be made.

Credibility is different from truth. It is an assessment of how much confidence we should place in a claim, given the information available. It accounts for evidence, sourcing, context, and clarity. It is how real-world decisions actually get made, and it is far more useful than waiting for certainty that may never arrive.

Most AI systems are not built to evaluate the nuances of credibility in a structured or consistent way. That is the gap AmICredible was designed to fill.

AmICredible Offers a Consistent Way to Evaluate Credibility.

Instead of asking an AI to decide whether something is true, AmICredible applies a consistent framework to evaluate how credible a claim is.

That evaluation considers multiple dimensions: how well a claim is supported by evidence, where the information comes from, how clearly it is stated, and whether it is presented with appropriate context. We call them the Four Dimensions of Credibility.

The goal is not to produce a better-sounding answer. The goal is to produce a more reliable assessment, one that applies the same standard every time, produces results that are repeatable and directly comparable, and maintains consistency across queries.

Most AI interactions do not do this. Every answer exists in isolation, making it difficult to build trust in its evaluations over time.

So Is Your Favourite AI Lying to You?

In short, no. It is doing exactly what it was designed to do.

But, if you are relying on it to determine what should be believed, you are asking it to solve a problem it was not built to solve. That is not the model's failure. It is a mismatch between the tool and the task.

Credibility is Essential.

We do not need AI to replace human judgment, we need it to support better judgment. That starts with recognizing the difference between something that sounds right and something that is actually credible.

When anyone can publish anything instantly, credibility is not a nice-to-have. It is not optional.

It is essential.

What Is Credibility? And How to Evaluate Any Source

dan@plancllc.com (Dan Nottingham) — Wed, 13 May 2026 14:29:59 GMT

Most people use the word "credibility" without ever stopping to define it. We say a source "seems credible." We dismiss claims as "not credible." We talk about credibility like we all know exactly what it means. But do we?

Credibility isn't just a feeling, and it's not brand recognition. It's not about whether a source confirms what you already believe or how polished their website looks.

Credibility is a measurable quality. And once you understand what it actually is, you'll never evaluate information the same way again.

What Is Credibility? A Definition That Actually Holds Up

According to the Cambridge Dictionary, credibility is “the fact that someone or something can be believed or trusted”. According to Google’s AI Overview, credibility is “the degree to which a statement, source, or piece of information can be trusted to reflect reality accurately”.

These two sources focus on different elements of credibility, but both miss the bigger picture. Credibility combines factual accuracy, source reliability, statement clarity, and contextual support to determine whether a claim is trustworthy. In other words, credibility is what you say, how you say it, and whether or not reliable sources support what’s been said.

Credibility is not just about whether something is "true" in isolation. A statement can be technically accurate and still be misleading if it's stripped of context, stated vaguely, or delivered by a source with a known track record of distortion. Credibility looks at the whole picture. That's what makes it such a powerful concept, and such an underutilized one.

Why Credibility Matters More Than Ever

We live in an era of information abundance. The challenge isn't accessing the news anymore. It's knowing what to trust once you have it.

According to recent research from the Pew Research Center, most U.S. adults say they regularly encounter news they believe is inaccurate. And about half say it can be difficult to determine what information is true and what is not.

Think about that for a moment. We have more access to information than any generation in history, and we're less confident in it than ever.

That's the credibility gap. And it's why understanding what credibility actually means, and how to measure it, is one of the most important skills a modern reader can develop.

What Makes a Source Credible? The Four Dimensions

When I came up with the idea for AmICredible, I spent a lot of time thinking about the concepts of truth throughout history. How the philosophers evaluated truth is highly subjective. I knew we needed a more concrete and layered approach to evaluating credibility, one that has basis in science and truth, and that offers a clear explanation of credibility. These four dimensions follow my own thought process for how a statement can be evaluated for this purpose.

The four dimensions of credibility are:

Factual Accuracy: Does the statement align with verified facts, scientific consensus, and available evidence?
Source Credibility: Who made the statement? Does the source have a track record of reliability, or a history of bias and misinformation?
Statement Clarity and Precision: Is the statement clearly defined and specific, or is it vague, hyperbolic, and stripped of important meaning?
Contextual Support: Does the statement include the context needed to interpret it accurately, or does it oversimplify and misrepresent a more complex reality?

Together, these four dimensions form a complete picture of whether something is truly credible, not just technically accurate. Let's take a closer look at each of these dimensions.

Factual Accuracy

This is the foundation. Before anything else, a credible statement needs to align with verified facts and scientific consensus.

The key questions here are:

Does the statement hold up when checked against evidence?
What is the level and quality of supporting evidence?
Has it been debunked by reputable sources?

A statement that contradicts established, peer-reviewed research or well-documented reporting doesn't become credible just because it's delivered confidently. Accuracy is non-negotiable. It's the foundation, not the cherry on top.

Source Credibility

Even factually accurate information can be undermined if the source delivering it has a history of unreliability or bias. Source credibility asks:

Who made this statement?
Is the source known for reliability, or does it have a documented history of spreading misinformation?
Does the claim originate from a recognized expert, a relevant institution, or a questionable origin?

This dimension matters because credibility is built over time. A claim from a peer-reviewed researcher carries different weight than the same claim from an anonymous social media account. It’s not elitism; it's accountability. Credible sources are visible and stand behind their work, always.

This is also why independent verification across multiple credible outlets matters so much. If a fact only appears in one place, especially a place with a known bias, that's a credibility red flag.

Statement Clarity and Precision

You can have accurate information from a credible source and still produce a statement that misleads. Vague, hyperbolic, emotional or poorly defined claims are a credibility problem even when the underlying facts are sound.

Ask yourself:

Is the statement clearly defined, or is it so broad it becomes meaningless?
Does it make precise claims, or does it rely on sweeping generalizations?
Is key context missing in a way that changes how the statement should be interpreted?

Clarity is a form of honesty. Statements that exaggerate, understate, or rely on emotionally charged language introduce distortion even when no lie is technically told.

With that said, credible communication does not have to exclude personal opinion. It just has to make the distinction between fact and opinion: “the evidence says X”, and “my opinion is Y”.

Contextual Support

The final dimension is one that gets overlooked most often, and it's where a lot of misleading content hides.

Context can completely change the meaning of a statement. A statistic taken out of its original study, a quote removed from its surrounding paragraph, a trend described without its relevant timeframe. All of these can be technically "accurate" while painting a fundamentally false picture.

Credible statements:

Include appropriate context that allows the audience to interpret them correctly
Do not oversimplify or misrepresent complex issues
Are transparent about limitations, caveats, or uncertainty

When context is stripped away, credibility goes with it.

How Do I Know If a Source Is Credible?

Now that you understand the four dimensions, here's how to apply them in practice.

Start with the source before the statement. Before you evaluate what is being said, ask who is saying it. Look at the outlet or individual's track record. Do they correct errors publicly? Do they disclose conflicts of interest? Are they cited by other credible sources?

Look for evidence, not just assertion. Credible sources show their work. They cite studies, link to primary sources, quote named experts, and give you a path to verify their claims yourself. If a statement offers no evidence and simply asks you to take it on faith, that's a red flag.

Check across multiple independent sources. This is one of the most reliable credibility tests available. If a claim appears in multiple credible outlets that have independently verified it, the likelihood of accuracy increases significantly. If it only appears in one place, or in a cluster of outlets with shared ideological leanings, dig deeper.

Watch for precision. Credible statements are specific. They define their terms, acknowledge their limitations, and avoid language designed to provoke emotion rather than communicate information.

Consider context deliberately. Ask yourself: what would I need to know to fully understand this claim? If something important seems missing, it probably is. Credible sources provide the context you need to interpret what they're saying fairly.

Credibility Is a Practice

Something that most people get wrong about credibility is they treat it like a certainty. Either something is credible or it isn't, either a source is trustworthy or it's fake news. Reality is more nuanced than that.

Credibility exists on a spectrum. A source can be generally reliable but still publish a claim or article that lacks evidence. A statement can be mostly accurate but missing crucial context. A claim can be well-evidenced in one dimension and completely unsupported in another.

That's why evaluating credibility requires the four dimensions working together. No single factor tells the whole story. Factual accuracy without source credibility is incomplete. Source credibility without contextual support is misleading. All four dimensions matter.

In my opinion, the single most important thing for anyone starting on their credibility journey to know is that credibility is a skill you can develop. The more deliberately you practice evaluating credibility, the faster and more accurately you'll be able to do it.

How My Journey Began: Artemis II, Apollo, and the Moon Landing

dan@plancllc.com (Dan Nottingham) — Fri, 24 Apr 2026 14:34:07 GMT

Looking back, it’s hard to believe that my whole journey started with a moon mission.

I was five years old when my teacher rolled a television into our kindergarten classroom. I remember the way my teacher hushed the whole room without even asking. I didn't fully understand what I was watching (the Apollo 11 capsule splashing down into the Pacific Ocean) but I understood that whatever this was, it mattered. You could feel it in the room.

When you experience a moment like that, you don't need to grasp the science or the politics or the history to know you're watching something real. Something human. Something that took everything a country had and pointed it at the sky.

A few years later, my family let me stay up past 9:30 on a school night. That alone told me something important was happening again. We watched the Apollo 17 launch in the dark on TV (the last crewed mission to the Moon) and I can still picture it. The rocket turned night into day. The light from that launch bled across the Florida sky, and I sat there, eight years old, feeling something I didn't have a word for yet. Pride, maybe. Wonder. The sense that we, as a country, as a species, were capable of extraordinary things.

These moments stuck with me. It sparked my fascination with space and led to my studying physics and astronomy. The space race was the origin of my intellectual curiosity and as I reflect now it amazes me that my career all started with watching a moon mission.

The country felt different then. There was a kind of collective "can do" energy that I absorbed as a kid, even if I didn't have the context to fully understand what was happening around it. And there was a lot happening. The civil rights movement was forcing a reckoning that was long overdue. The Vietnam War was exposing the cost of propaganda and the way truth can be manipulated. The divisions were real and they were deep.

But there was also this shared, genuine pride. Progress and imperfection living side by side. We weren't perfect. But we were trying. We were building something.

Which is why it stops me cold when I hear people say the Moon landing was faked.

I don't say that with contempt. I say it with genuine sadness. What that belief misses isn't just the facts, it diminishes the weight of what we actually accomplished.

The Apollo program was hard in ways that are almost impossible to convey today. Three astronauts died in a ground test of Apollo 1 (I have a vague but sobering memory of that news). Apollo 13 came within a breath of killing three more. The on-board computer in the lunar module had roughly the processing power of a modern handheld calculator. But, unlike computers today, it was purpose-built to do specific tasks, and that precision was its genius. Its simplicity was its strength.

More than 400,000 people worked on the Apollo program. Engineers, scientists, seamstresses, welders, mathematicians doing calculations by hand. It took an entire nation's worth of expertise and labor and it was still almost impossible. These hardships are not evidence of fabrication, they are the very reason it's one of the greatest achievements in human history.

So, what changed? Why do a meaningful number of people today believe we never went to the moon? I've thought about this a lot. And I think the answer is the information environment we've built.

When I was a kid, information traveled through a small number of channels. Television. Newspapers. The evening news. There were editors, fact-checkers, and broadcast standards. Misinformation existed. Propaganda existed. Vietnam proved that. But it moved slowly, through centralized pipes, and it had friction.

Today, everyone has a global platform with no guard rails. It has become incredibly hard to tell the difference between expertise earned over a lifetime and baseless confidence or an agenda dressed up in the language of expertise.

The result is that we've lost something more fundamental than facts. We've lost a shared method for figuring out what's real. We no longer agree on how to evaluate reality, let alone what reality is. This is the true information crisis.

This month, we went back to the Moon. Artemis II (a crewed mission that took humans farther from Earth than any person has traveled since Apollo 13) is a genuine marvel. It deserves the same awe I felt as an eight-year-old watching night turn to day over Florida. It is still hard. The risks are still real. The people working on it are still extraordinary.

Since the launch, I have found myself sitting with a question that I cannot yet answer: will we let it matter?

If we couldn't agree on Apollo, something that happened in front of cameras and witnesses and hundreds of thousands of participants, something with a 50-year paper trail, what does that mean for Artemis? Will these missions inspire a new generation the way Apollo inspired me? Or will they get swallowed by suspicion before the capsule even splashes down?

I was there. I watched Apollo 11 return. I watched the Apollo 17 launch. These aren't abstract historical events to me. They are personal memories, embedded in who I am. And I won't pretend that makes me the authority on what's true. But it does make me someone who understands what we stand to lose if we can't find our way back to shared ground.

The answer isn't censorship. I believe deeply in free expression. People deserve to make up their own minds, with access to real evidence. The answer isn't some authority deciding what's true and feeding it to the rest of us. That would just be a different kind of problem.

What we need is a credibility layer.

A way for people to see, clearly and transparently, which claims are supported by verifiable evidence across multiple independent sources. A way to understand the difference between a credible expert and a persuasive voice. A way to ask the question "is this real?" without having to spend three hours doing research most people don't have time to do.

I have seen what we're capable of when we're at our best. I saw it flicker across a classroom TV when I was five. I saw it light up the night sky when I was eight. Inspired by these events, I spent my early career among people who were trying to understand the universe, and I saw that even then, the most important thing wasn't the data itself. It was the commitment to following it wherever it led.

We've done incredible things before. We are doing incredible things right now. But we can only be proud of them together if we can agree on the reality we're building from. That's not a small ask in 2026. But I don't think it's impossible either. What we choose to believe still matters.

The Scientific Mindset: What Physics Taught Me About Credibility

dan@plancllc.com (Dan Nottingham) — Wed, 22 Apr 2026 14:30:00 GMT

Before I built AmICredible, and before 15 years in healthcare technology and product strategy, I was trained as a physicist.

I studied physics at Sonoma State University and then worked as a staff scientist at Boston University's Center for Space Physics. That experience didn’t just teach me equations or models. It taught me something far more lasting: the discipline of the scientific method.

That way of thinking doesn’t stay in the lab, it becomes how you approach problems. It shapes how you evaluate claims, and how you separate what feels right from what can actually be supported by evidence.

That lens is the reason I see today’s information crisis differently than most people.

What Physics Actually Teaches You

When people hear “physics,” they often think of formulas, theories, or abstract concepts. But the most valuable thing physics teaches you isn’t any specific knowledge, it’s how to think.

You learn that claims are not accepted because they sound convincing, they are accepted because they survive scrutiny. You learn to ask:

How was this measured?
What assumptions are being made?
What evidence supports this?
What evidence would contradict it?

You learn that your intuition can be wrong, that confidence is not evidence and that the result you want has no bearing on the result that is actually true.

Most importantly, physics teaches you to hold conclusions loosely until they are supported, and to update them immediately when new evidence appears.

That mindset doesn’t disappear when you leave physics. It becomes a permanent filter for how you process information.

The Real Problem Isn't Absence of Truth

Here's where I think the conversation about misinformation often goes wrong.

The framing is usually that no one knows what to believe because there's no reliable signal anymore. That truth itself has become murky.

That's not accurate. And as someone trained to look for what the data actually says, I want to be precise here.

The signal exists. It's produced every single day by reputable journalists, researchers, scientists, and institutions using sound methodology. Rigorous reporting is still happening. Credible sources are still publishing. The infrastructure of verified information is still functioning.

The problem is that the signal is buried in noise. Bad actors have learned to exploit that noise deliberately. And many people who believe they are "doing their own research" haven't been equipped with the tools to distinguish between a credible source and a convincing one.

Credibility and persuasiveness are not the same thing. A claim can be emotionally compelling and factually hollow. A headline can feel true while the evidence points elsewhere. Without a disciplined methodology for evaluation, most people can't tell the difference, not because they aren't smart, but because they were never taught how.

The Gap Nobody Is Talking About

In physics you don't accept a result just because someone stated it confidently. You ask: How was this measured? What methodology was used? What is the margin for error? Has this been replicated?

That's not skepticism for its own sake. It's a structured approach to getting to the truth reliably.

Most people navigating today's information environment don't have a structured approach. They have intuition, pattern recognition, and a news feed optimized for engagement rather than accuracy. They're making credibility judgments constantly, on every post they read and share, without the methodology to make those judgments well.

The gap is not the absence of truth, it’s the absence of a structured way to find it.

What AmICredible Is Actually Built to Do

When I started building AmICredible, I wasn't trying to replace journalism or declare what's true. I was trying to bring the discipline I learned in physics to a problem that desperately needs it: Rather than spreading misinformation, people need a simple, impartial, and trusted way to evaluate the credibility of what’s being said.

The scientific method, at its core, is a way to evaluate claims against evidence systematically and transparently. AmICredible applies that same logic at scale. It gives anyone, regardless of their background, a way to test a claim, trace it to its sources, and understand how well it holds up before they amplify it.

Because the problem was never that the truth disappeared. The problem is that most people haven't been given the tools to find the truth from within the noise.

The Mindset Behind the Habit

This is the part that has stayed with me most from my physics training: rigor isn't a personality trait. It's a practice.

Every researcher starts out making assumptions, acting on intuition, occasionally getting things wrong. What separates disciplined thinking from undisciplined thinking isn't natural ability. It's the habit of checking your work. Questioning your conclusions. Following the evidence even when it's inconvenient.

That habit is available to everyone. And in today's information environment, building it may be one of the most important things any of us can do.

Start With the Methodology

The information environment isn't going to get simpler. The noise isn't going to quiet down on its own. What changes things is bringing a disciplined approach to finding it. Asking better questions. Checking sources. Separating what the evidence shows from what you want it to show.

That's what physics taught me. And it's what AmICredible is built to help you do.

Ready to apply a more disciplined approach to the information you share? Sign up at AmICredible.ai.