Introduction
Summary of the book Calling Bullshit by Carl T. Bergstrom, Jevin D. West. Before we start, let’s delve into a short overview of the book. Imagine standing in a room crowded with voices, each person shouting out statements they swear are true. Everywhere you look—on your phone, in the news, on social media—there are claims rushing toward you. Some of these claims might sound amazing. Others might sound scary. Many people believe them just because everyone else seems to. Yet hidden among these waves of information are twists, distortions, and slippery half-truths that can fool even the smartest among us. This is the world of bullshit—statements that sound convincing but aren’t supported by honest evidence. And it matters because if we accept these shaky stories, we might make poor decisions or harm others without even realizing it. In the chapters ahead, we’ll explore how bullshit grows, how people use it to influence us, and how we can learn to see through it. Get ready to open your eyes and sharpen your mind.
Chapter 1: Exploring How Ancient Patterns of Clever Trickery Evolved into Modern Bullshit Tactics.
Long before smartphones, social media, and breaking news alerts, people were already skilled at twisting words to win arguments. In ancient times, philosophers like Plato complained about sophists—individuals who cared less about truth and more about sounding right. These clever talkers knew how to dress up weak ideas, making them seem strong enough to impress crowds. But while ancient trickery took place in small groups or public forums, today’s world is more complicated. We live in a time when information flies around the planet in seconds, and that makes the old art of crafty persuasion more powerful than ever. Once upon a time, a false claim might travel slowly through a single village. Now, a questionable story can spread from one side of the Earth to the other with the click of a button, leaving confusion and misinformation in its wake.
Modern bullshit doesn’t wear a big sign announcing itself. Instead, it sneaks in disguised as trustworthy facts, scientific studies, or eye-catching statistics. The reason this happens so easily is that we have unprecedented access to data and knowledge. Every day, people perform experiments, gather numbers, and publish research. This sounds great, right? More information should mean more truth. Yet, ironically, the more data we have, the easier it is for someone to pick and choose just the right numbers to support whatever they want you to believe. Back in the old days, a person spouting nonsense had fewer tools. Today, they can point to expert opinions or data-driven results that, without proper checking, look perfectly convincing. In other words, our modern tools for spreading knowledge have also created fertile ground for spreading carefully packaged nonsense.
What’s truly alarming is how quickly false claims or twisted facts become deeply rooted beliefs in the minds of ordinary people. Take, for example, a discredited medical study linking vaccines to autism. Although it was thoroughly debunked and retracted, its influence stuck around. The anti-vaccine movement it helped ignite continues causing harm, lowering vaccination rates and allowing diseases to return. This shows that bullshit can have serious real-world consequences. It’s not just harmless chatter—people’s health and lives can be affected. Ancient tricksters might have persuaded a handful of followers in a public square. Today’s cleverly packaged nonsense can move entire communities or even nations. Our digital world allows falsehoods to go viral, entangling even smart readers in webs of misinformation that are tough to escape.
As we move through these chapters, we’ll learn to recognize the old patterns hidden beneath the shiny surface of modern lies. We’ll see how the ancient art of convincing others, regardless of truth, has been supercharged by technology and the speed of global communication. Recognizing this pattern is the first step. Once you see that modern bullshit often relies on timeless persuasion tricks, you can begin to resist it. Instead of being dazzled by flashy charts, scientific-sounding language, or popular rumors, you can slow down and ask the right questions: Who said this? Why should I believe it? What evidence do they really have? Understanding that today’s misinformation draws on ancient roots helps sharpen our senses, making it easier to spot nonsense dressed up as truth.
Chapter 2: Why Present-Day Bullshitters Don’t Care About Truth Yet Sound So Convincing.
Not everyone who spreads false claims is a simple liar. A liar knows the truth but decides to tell the opposite. A bullshitter, on the other hand, doesn’t care whether something is true or not. Their main goal is to impress, persuade, or mislead, so long as they win their audience over. This subtle difference matters. Bullshitters often sound extra confident because they aren’t weighed down by the need to stick to facts. They feel free to say whatever supports their argument, throwing out fancy words, statistics, or scientific-sounding terms to dazzle listeners. Since they don’t care about correctness, they can talk circles around skeptics, leaving people too confused or overwhelmed to challenge them effectively.
Because bullshitters don’t rely on honesty, they have a huge advantage in today’s crowded information world. They can cherry-pick numbers that look good for their point, ignore important details, or twist a study’s findings. Imagine a magician who shows you a deck of cards and claims it’s totally random, but secretly hides the right cards up his sleeve. That’s what a bullshitter does with facts. And in an environment full of headlines, tweets, blog posts, and endless news feeds, it’s easy for them to throw out multiple claims quickly. Most people don’t have the time or energy to fact-check every detail. By the time someone uncovers the truth behind one claim, the bullshitter has already spread three more questionable statements, keeping the audience off-balance.
Our modern tools make it easy to create convincing images, graphs, and videos. A bullshitter can use these tools to dress up their claims, making them appear more solid. For example, if a person wants you to believe that a certain health product works wonders, they might show you a glossy chart proving dramatic results. Without understanding how the data was gathered or what the chart really represents, viewers might just nod and accept it. People tend to trust visuals, and a bullshitter knows this. By stacking their presentation with confident language and eye-catching designs, they craft a story that feels real, even if it’s hollow inside.
If you wonder why such tactics are effective, consider human psychology. Many of us don’t want to look foolish or untrusting, so we hesitate to call someone out. Others might already share the bullshitter’s beliefs and welcome any evidence that seems to support them. This opens the door for nonsense to spread easily. Another trick is to rely on complicated language or high-level math that the average person can’t easily decipher. If you can’t understand the process behind a claim, you’re less likely to question it. Knowing that bullshitters don’t care about the truth but focus on sounding believable helps us guard against falling under their spell. Once we realize that looking trustworthy and caring about truth aren’t the same thing, we can start pushing back.
Chapter 3: How Correlation and Causation Confuse Our Minds and Fuel Deceptive Claims.
Imagine someone saying, Every time I wear my lucky socks, my basketball team wins! This statement mixes up two concepts: correlation and causation. Correlation means two things happen at the same time, while causation means one thing actually causes the other. Just because your team won on days you wore those socks doesn’t mean the socks caused the victory. Yet this confusion pops up everywhere and helps spread nonsense. In the world of bullshit, people often use correlations to claim causation. They’ll point to numbers that show two trends rising together and say, See? One caused the other! This trick works because our brains look for patterns and connections, even where none really exist.
News articles, blogs, and social media posts are full of claims linking unrelated things. A study might show that in certain cities, as house prices go up, the birth rate goes down. From just that observation, a sloppy thinker might say, High house prices are making people have fewer babies! But maybe the truth is different. Perhaps people in those cities decide to have children later for reasons like career, education, or personal preference. The numbers show a correlation, but they don’t prove a cause. This kind of misunderstanding can lead to silly or harmful beliefs. If the public accepts these false causes, bad policies and poor personal decisions might follow.
Sadly, the media often simplifies scientific findings. A cautious researcher might say, We found these two variables are linked, but we cannot confirm a cause. When the headline appears in a newspaper or pops up online, it might read, Study shows X causes Y! The subtlety disappears. Editors know dramatic claims draw more readers. This makes it easy for bullshit to spread, as people pass along these shaky claims without questioning them. If you see a surprising claim that one thing directly causes another, take a moment to think it through. Could other factors be involved? Is it only a coincidence that they occur together?
Learning the difference between correlation and causation is like putting on a special pair of glasses that helps you see through nonsense. It teaches you to ask, Is this just a coincidence, or is there real evidence that one event led to the other? Many bogus claims fall apart when you apply this simple test. Don’t be dazzled by big numbers or fancy graphs showing two lines moving together. Sometimes it’s as meaningless as noticing that ice cream sales and sunburn cases both rise in summer—of course they do, but ice cream doesn’t cause sunburns. By training your mind to look deeper, you become better at spotting when someone’s using a correlation to trick you into believing they’ve proven a cause.
Chapter 4: When Media Outlets Twist Facts and Statistics to Shape Our Worldview.
We rely on journalists and the news media to keep us informed about important events and facts. Unfortunately, not all news outlets care about accuracy. Some are more interested in getting attention, pleasing advertisers, or pushing a political viewpoint. This can lead them to present numbers and statistics in a misleading way, sometimes turning real data into something scary or dramatic that fits their chosen story. For example, an article might say, Over 2,000 people in this group committed crimes! without telling you that the total group size was huge, making that number actually quite small. By choosing what details to highlight, media outlets can steer your emotions and beliefs without actually lying.
There’s also the problem of fake news sources that deliberately spread nonsense. Some online platforms publish completely unverified stories, often with made-up quotes, events, or statistics. Others might take a kernel of truth and twist it until it supports a narrative that attracts more clicks and shares. Thanks to social media, these stories travel fast. When people see a headline popping up repeatedly, they start to think, Well, it must be true, everyone’s talking about it. But in reality, everyone might just be repeating the same questionable information. This creates a cycle where false claims gain strength through repetition rather than evidence.
Even traditional, respected news sources can unintentionally spread nonsense. Sometimes reporters don’t understand the data they’re given. Other times they rush to break a story, not double-checking the facts. They might oversimplify complex research or remove important context. These mistakes can plant seeds of misinformation in the public’s mind. For example, a scientific report might clearly warn, We are not sure this treatment works yet. The news headline might then read, New Treatment May Cure Disease! By the time doctors clarify the truth, the bold claim has already spread.
Understanding that the media can shape our worldview with twisted facts helps us be more careful. Instead of just accepting every headline at face value, take a moment to ask questions. Who published this story? Did they provide solid evidence or just a few numbers without context? Is there another reputable source that confirms or challenges these claims? Checking multiple sources and looking for original research can help you dodge the traps of clever storytelling and misleading headlines. News stories are often your first window into what’s going on in the world, but remember that this window can be foggy. Wipe it clean by staying curious and always seeking the full picture.
Chapter 5: Revealing the Strange Power of Numbers to Make Nonsense Seem Reasonable.
Numbers have a special power. They feel solid, objective, and reliable. After all, two plus two equals four, right? But while basic math is honest, the way people present numbers can be very tricky. A product might say it’s 99.9% caffeine free, making it sound super pure. But if you compare it to an everyday cup of coffee, coffee is already about 99.9% caffeine free by weight. So the claim isn’t as special as it seems. By choosing certain numbers, percentages, or ways of comparing data, a speaker can make a small difference look enormous or a big problem seem tiny. It’s like holding a funhouse mirror up to reality, stretching and shrinking facts to create a desired impression.
Political campaigns, advertisements, and even some scientists know how to use numbers to shape opinions. If someone wants you to think a problem is huge, they might say, 10,000 people are affected! But if that’s out of a population of millions, it might not be so large. On the other hand, if they want to downplay a serious issue, they might say, Only 0.5% are at risk, even if that actually represents a lot of people. Understanding the difference between absolute numbers (like total counts) and relative numbers (like percentages) is crucial. Sometimes what sounds like a huge jump in risk is actually just going from 1% to 1.5%, which is a 0.5 percentage point increase—a much smaller deal than it first appears.
Another common trick is switching between percentages and raw numbers depending on what sounds more dramatic. A headline might warn that a certain crime rate doubled from one year to the next. Doubling sounds terrifying, right? But what if it went from 1 in a million to 2 in a million? That’s still incredibly rare. The dramatic language takes advantage of people’s natural tendency to worry about big increases without asking what the original amount was. This sort of number manipulation can make an audience feel fear, excitement, or outrage where it’s not truly justified. It’s a form of bullshit that doesn’t require outright lying—just careful selection and presentation of figures.
Whenever you see a shocking statistic, train yourself to ask: Compared to what? Check whether the number is being taken out of context. Are they showing actual numbers or percentages? Are they leaving out important details, like the size of the total group or how frequently something happens in general? If someone claims that a small change is huge or a large problem is tiny, digging deeper into the math often reveals the truth. Numbers can be friends that help guide us, but in the hands of a bullshitter, they become tools of confusion. Learning to question them puts you back in control. Instead of letting numbers mislead you, you can use your critical thinking to understand what they really mean.
Chapter 6: Hidden Dangers of Biased Data Samples and Misleading Research Results.
Imagine you want to know what an entire country thinks about a new law. If you only ask people in one small, wealthy neighborhood, your results won’t represent everyone’s views. This is selection bias: when the group you study isn’t a fair snapshot of the whole. Selection bias can sneak into scientific research, opinion polls, and news reports. It happens when researchers, often unintentionally, pick data that leans in one direction. As a result, the final conclusions are skewed. This can lead to ridiculous outcomes, like a study proving a nonsense link just because the sample wasn’t broad enough or was chosen poorly.
This issue can appear in many fields. For example, consider studies that try to show a relationship between attractiveness and personality. If you remove all the people who are extremely unpleasant and all those who are extremely unattractive, leaving only a certain middle group, you might suddenly see a pattern that wasn’t there before. It looks like hot people are meaner, but this correlation might be an illusion caused by how you selected your sample. The same goes for drug trials: if participants who suffer bad side effects drop out, the final results might make the drug look safer than it really is. The missing data creates a false picture.
Companies also exploit selection bias. Car insurance ads love to say, Switching to us saves people $500 on average! Of course it does, because the only people who switch are those who actually save money. People who wouldn’t save anything never bother to switch and thus never show up in that statistic. This kind of bias in data collection gives a false impression of easy savings. Without realizing it, viewers might assume everyone who switches benefits, which simply isn’t true.
Knowing about selection bias helps you be more cautious. When confronted with research or claims based on studies, ask: How did they choose their data? Who was included and who was left out? If a study’s sample doesn’t represent the broader population, its conclusions might not hold. Being aware of selection bias means you’ll never just accept a number as fact. You’ll look behind the scenes at how that number was created. By doing this, you free yourself from the trap of misleading research results. The world of data is full of these subtle pitfalls, but once you know they exist, you can navigate around them, refusing to be fooled by carefully selected facts that don’t tell the whole story.
Chapter 7: Inside the Mysterious Black Boxes of Algorithms Generating Bogus Conclusions.
Today, many decisions are influenced by algorithms—complex computer instructions that process huge amounts of data. These algorithms can suggest movies you might like, diagnose health problems, or even predict crime. They often work like black boxes: you see the input (data) and the output (the result), but what happens in the middle remains hidden and mysterious. If the data they’re fed is flawed, the algorithm’s conclusion can be nonsense dressed up in technological glory. And because we trust technology so much, we’re tempted to believe the machine’s results without questioning them.
Consider a study that claimed an algorithm could identify criminals just by looking at their faces. This sounds impressive, yet the data it used was biased. The criminal faces came from official ID photos, where people rarely smile, and the non-criminal faces were cheerful headshots. The algorithm wasn’t finding a criminal look. It was just noticing differences in expression due to how the photos were taken. Such flawed data led to a bogus, even harmful, conclusion. But without understanding how the algorithm worked, many people might have believed it, thinking that technology must be right.
Algorithms also fail when they look for patterns that don’t relate to what they’re supposed to measure. For example, a machine learning system trying to detect health problems in chest X-rays might learn to recognize not the medical issue, but some text on the image that always appears in certain cases. Another famous attempt by a big tech company tried to predict flu outbreaks by tracking certain Google searches. For a while it looked promising, but over time it got worse at predicting flu because it confused unrelated seasonal searches (like for basketball) with illness trends. The black box didn’t understand the meaning behind its data; it just matched patterns blindly.
The lesson is that technology is only as good as the data and assumptions guiding it. Algorithms can be powerful tools, but they’re not magic truth machines. Just because a computer spits out a number or a prediction doesn’t make it correct. To avoid swallowing algorithmic nonsense, ask whether the data was fair, whether there’s good reason to trust the machine’s learning process, and whether independent experts have tested the results in multiple ways. If something feels fishy, remember that you have the right to question the black box. Technology might speak with a voice of authority, but it can produce nonsense too. Understanding this will help you stay alert and not be dazzled by fancy digital claims.
Chapter 8: Why Imperfections in Modern Science Let Deceptive Information Slip Through.
Science is a method for slowly uncovering truth by testing ideas over and over. Over time, weaker ideas should fade away, and stronger evidence-based truths should stand. But real science doesn’t always work as smoothly as textbooks suggest. Researchers need to publish results to advance their careers, and journals love surprising findings. That means boring studies or failed experiments often go unnoticed. This creates publication bias, where positive or exciting results are overrepresented. Scientists are human, and they sometimes use questionable methods—like p-hacking, where they massage their data until it looks like it supports their hypothesis. This doesn’t necessarily mean they’re evil; they might just be under pressure to produce impressive findings.
As a result of these imperfections, even scientific literature can contain bullshit. A few flawed studies can spark huge misconceptions if the media picks them up. That’s how nonsense like the vaccine-autism link spread. Once an idea is out there and gets attention, many people remember it, even after it’s debunked. The scientific community often tries to correct itself, but the correction doesn’t always spread as widely as the original claim. This leaves misleading ideas floating around, ready to be used by anyone who wants to sow doubt or push an agenda.
Some low-quality journals will publish almost anything if the author pays a fee, leading to a flood of questionable studies. Meanwhile, the media, hungry for attention-grabbing headlines, may report on these shaky papers as if they are groundbreaking discoveries. Readers who don’t know how to evaluate scientific sources might accept these claims at face value. Without careful scrutiny, the scientific process can appear more authoritative than it actually is, leaving space for bullshit to creep into what we think we know about the world.
It’s important to remember that science is a tool, not a religion. Good science acknowledges mistakes, adapts, and improves methods over time. When you encounter a big scientific claim, ask where it was published and whether other researchers have confirmed it. Has it been replicated? Was the data collected fairly and analyzed honestly? By staying curious and careful, you protect yourself from adopting false beliefs just because they wear the costume of science. Scientists have a responsibility to do better, and the public has a responsibility to stay informed and ask questions. The more we understand these flaws, the less likely we are to be fooled by the veneer of scientific authority.
Chapter 9: Spotting Flaws in Headlines, Viral Stories, and Manipulated Photographs Easily.
The internet is a wild jungle of images, headlines, and stories. Every day, pictures and claims flood our screens, many aiming to shock, inspire anger, or pull at our heartstrings. Some of these items are genuine, but many are manipulated or taken out of context. A photo might show something dramatic, but maybe it’s from a different time or place than the caption suggests. A headline might scream, Proof of a Miracle Cure! while the actual article quietly admits no real evidence exists. To survive in this jungle, you must learn how to check details, ask questions, and remain calm instead of instantly reacting.
One common tactic is to tell a heartbreaking story attached to a photo. Perhaps the story claims a child in the picture suffered a tragedy due to a controversial event. If you dig deeper, you might find that the child was never involved in that event, and the photo is from a completely different situation. But by the time you discover the truth, thousands of people may have shared the false story, believing they are spreading important news. This shows how easily bullshit travels when emotional hooks are used to bypass our critical thinking. Our empathy can be weaponized by dishonest storytellers.
Another problem is the blending of facts and opinions. A headline might say, Experts Agree: New Tax Will Destroy Jobs. Inside the article, you might find only one so-called expert, who is actually a spokesperson for a political group. Or you might discover the study they refer to has been strongly criticized for poor methods. False authority and twisted facts can fool even careful readers if they’re not paying attention. The best defense is to be curious: look up the people mentioned, search for other sources, and consider whether the claim feels too neat or too dramatic.
Remember that calling bullshit doesn’t just mean shouting Fake! at everything. It means taking the time to understand the source, the context, and the evidence. If a story seems suspicious, you can do a quick image search to see where else the photo appears. If a headline feels too shocking, see if trusted news organizations confirm it. If a claim seems one-sided, look for opposing views and reasons why someone might present it the way they did. Learning to spot flaws in headlines, viral stories, and manipulated photos gives you the power to steer clear of nonsense and help others do the same. You become a guide, shining a light on the hidden corners where deception thrives.
Chapter 10: Practical Techniques and Mental Tools to Sharpen Your Bullshit Detection Skills.
So how can you arm yourself against bullshit? Start by thinking like a journalist. Ask three basic questions when you encounter a claim: Who is behind this information? How did they get it? What are they trying to achieve by sharing it? These questions force you to look beyond the surface and consider motives, methods, and intended outcomes. Just this simple mental shift can make a huge difference. Instead of passively accepting what’s thrown at you, you become an investigator, looking for clues to understand the claim’s origin and purpose.
Another useful technique is the Fermi estimation, a quick mental check to see if numbers are reasonable. Say someone claims there are 200,000 people with a rare skill in your small town of 50,000. Without doing precise math, you can guess that can’t be right because the number of people with that skill can’t exceed the total population. Such a rough calculation helps you see if claims are wildly off the mark. You don’t need to be a math genius; you just need to estimate whether something sounds plausible.
Being aware of confirmation bias is also crucial. Confirmation bias is our natural tendency to believe things that align with what we already think and doubt things that challenge our views. If you read a claim that perfectly fits your beliefs, pause and double-check. Are you accepting it too eagerly because it makes you feel correct? Try to look at evidence from multiple angles. Consider sources you disagree with. By stepping outside your comfort zone, you strengthen your bullshit detection skills. It may feel uncomfortable at first, but it helps prevent you from being tricked.
You can also practice slowing down. Bullshit often succeeds because it catches people off guard and rides the wave of emotion. If something makes you angry, excited, or fearful, that’s the perfect time to take a deep breath. Don’t share it instantly. Don’t jump to conclusions. Investigate. Another key method is to learn some basic statistics: understand averages, percentages, and margins of error. This knowledge works like a shield, protecting you when someone tries to spin data. Ultimately, sharpening your bullshit detection skills isn’t about never trusting anyone. It’s about trusting with caution and always being ready to ask, Why should I believe this? When you have the tools to analyze claims, you hold the power over what you accept as true.
Chapter 11: Becoming a Thoughtful Skeptic and Politely Exposing Unreliable Information Everywhere.
Calling out bullshit doesn’t mean being rude or starting fights. In fact, politeness and understanding can make you more effective. When you see someone sharing nonsense online, instead of angrily insulting them, you can gently point out the evidence, share a reliable source, or explain why the claim might be flawed. People are more likely to listen if they don’t feel attacked. Approaching others with respect not only keeps conversations civil, but also increases the chances that they’ll actually consider what you’re saying.
Remember that everyone can make mistakes, including you. Being a thoughtful skeptic means remaining open to correction. If someone shows you convincing evidence that you were wrong, admit it. This honesty sets a good example and prevents you from becoming a bullshitter yourself. It’s easy to get trapped in pride, stubbornly defending a wrong idea because you don’t want to look foolish. But true strength lies in seeking truth, not in pretending to be right all the time.
As you gain confidence in spotting and challenging nonsense, you’ll discover that you’re helping create a healthier information environment. Each time you politely challenge a false claim, you’re encouraging others to think more carefully. Over time, more people might develop these critical thinking habits. This doesn’t mean the world will suddenly become free of nonsense, but it does mean that bullshit may spread more slowly. Instead of being easily tricked, communities become smarter, healthier, and more resistant to misleading stories.
You don’t need to be a genius or a professional scientist to stand against misinformation. Your everyday curiosity, skepticism, and willingness to learn are powerful tools. By examining claims, testing whether they make sense, and calling out nonsense when you see it, you become a guardian of truth. You help others see the importance of evidence and fairness in discussions. And as more people join in, we build a world where truths have a better chance of shining through the shadows. In the end, we can’t fully prevent bullshit from existing, but we can become much better at recognizing it and preventing it from shaping our minds and our decisions.
All about the Book
Uncover the art of critical thinking in ‘Calling Bullshit.’ This essential guide reveals how to identify misinformation and propaganda, empowering readers to navigate the complex digital landscape with confidence and clarity.
Carl T. Bergstrom and Jevin D. West are esteemed scholars in data science, dedicated to educating the public about misinformation and the significance of scientific thinking.
Data Scientists, Journalists, Educators, Policy Makers, Marketing Professionals
Reading, Critical Thinking, Data Analysis, Public Speaking, Social Media Literacy
Misinformation, Data Misinterpretation, Digital Literacy, Scientific Illiteracy
In an age of information overload, it is our duty to discern truth from falsehood.
Neil deGrasse Tyson, Bill Gates, Malcolm Gladwell
Best Non-Fiction Book Award 2020, Data Literacy Award 2021, Critical Thinking Award 2022
1. How can you identify misleading statistics in news? #2. What are common traits of bullshit in media? #3. How do algorithms influence the information we see? #4. What techniques debunk fake scientific claims effectively? #5. How do cognitive biases affect our judgment? #6. Why is critical thinking essential in today’s world? #7. What makes a source reliable or untrustworthy? #8. How can data visualization be manipulated deceptively? #9. Why question causation in correlational studies? #10. How does confirmation bias impact our beliefs? #11. What role does language play in spreading bullshit? #12. How can we detect pseudoscience in public discourse? #13. Why are peer-reviewed studies more credible? #14. How do echo chambers reinforce misinformation online? #15. What strategies counteract professional misinformation spreaders? #16. How does social media amplify bullshit effectively? #17. Why is fact-checking important for credibility? #18. What signs indicate a cherry-picked data example? #19. How does expertise differ from authority in arguments? #20. Why scrutinize overly simplistic explanations in complex issues?
Calling Bullshit, Carl T. Bergstrom, Jevin D. West, critical thinking, media literacy, data literacy, misinformation, bullshit detection, statistics, science communication, debunking myths, cognitive biases
https://www.amazon.com/Calling-Bullshit-Truth-Lessons-Misinformation/dp/0593137361
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