How to Find Valuable Content in Information Noise? - Huxiu.com
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Highlights
The more information there is, the more assumptions are formed, leading to worse conclusions. ⤴️ ^958d9c2f
In the end, fear of missing out. ⤴️ ^61f2d5cf
First, whether the information is relevant to your interests and the current problem you are trying to solve. Second, whether the source is credible and whether there is arbitrary fabrication, which is very obvious in terms of data; Third, it must be practical, not just opening up cognition day by day, but not being used; Fourth, whether it can thoroughly explain each part of a problem. ⤴️ ^4ceac2e4
Relevance, credibility, practicality, and thorough explanation of underlying logic.
How to Find Valuable Content in Information Noise?
This article discusses methods for finding valuable content in information noise. The author points out that when faced with a large amount of information noise, it is easy to mistake it for "useful information", and the more information there is, the more assumptions are formed, leading to worse conclusions. The author suggests that problem prepositioning, finding thinking models, and the ability to learn how to learn are effective methods for processing information.
• 🤔 More information does not necessarily mean more useful information, so it is important to filter and find valuable content.
• 📚 Learning thinking models can help us understand and apply knowledge more comprehensively.
• 📝 Writing is an effective way to organize and deepen understanding of knowledge.
In the book "The Black Swan," American author Nassim Nicholas Taleb mentions a thought-provoking experiment:
Researchers brought a photo of a fire hydrant and processed it to the point where it was so blurry that it was unrecognizable, and then showed this photo to two groups of participants.
In the first group, the participants were shown the photo in 10 stages, gradually increasing the clarity each time; in the second group, the photo was shown in only 5 stages, also gradually increasing the clarity.
When both groups saw the photo at the same level of clarity, the experiment paused, and they were asked to identify the object in the photo. Interestingly, the second group was faster and more accurate in identifying the fire hydrant in the picture.
What does this experiment illustrate?
When faced with a large amount of content noise, it is easy to mistake it for "useful information". The more information there is, the more assumptions are formed, leading to worse conclusions.
For me, writing is a long-term commitment. Through exploring various information channels, I gradually realized that information does not carry any value, and understanding of things depends on the quality of information and its application in practice. Therefore, most information is not useful.
01
Many people are confused about the difference between information and content. Simply put, an article, a movie, or a photo are all considered content, while information is a part of it.
Nowadays, content is exploding everywhere, with information and content everywhere. Even if you know the difference between the two, what can you do? Sometimes, it is difficult to find quality content from an article, and similarly, it is difficult to obtain verified knowledge from information.
The emergence of such problems can be divided into four aspects. When these four aspects are combined, they can lead to an information crisis, which not only makes individuals smarter, but also makes the collective more ignorant.
You may have heard of individual phenomena or given them many names, but these are not comprehensive enough. After thinking about it, I think "information doomsday" is a more appropriate term.
First, there is content overload.
Let me talk about my feelings. Every morning when I open my phone, I am surrounded by various information, such as updates from friends, articles from public accounts, hot topics on Weibo, and recommended short videos, etc. The volume is astonishing.
The human brain has limited cognitive capacity. A few days ago, I read a book by American psychologist Herbert Simon, in which he mentioned this. The meaning is: when there is too much information, it is difficult for us to focus on important matters, and our mental resources will be constantly divided and consumed.
Think about it, is it true?
At the end of the day, when the work is done and there is not much to do during the day, the increasing entropy effect caused by the fragmented and chaotic information often makes people feel exhausted.
Next is the information cocoon.
You should be familiar with this term. Simply put, the media and social platforms are constantly expanding. In order to sustain their development, they will split into various small groups, and each company or community will form its own language and culture.
Each individual is divided into a certain space and only knows the information within that space and the information in close proximity. This leads to the perception that each group is different from others. The result is that internal communication seems convenient, but communication with the outside world becomes difficult, and biases and extreme thoughts emerge.
For example:
Investors think that entrepreneurs are always too idealistic and lack realism; entrepreneurs think that scholars and researchers are too theoretical and out of touch with reality; marketers are mistakenly believed to only care about appearances and neglect product value; even best-selling authors are often considered not rigorous enough.
......
This is not the point. The key is that each group lives in its own small world, always thinking that they see the whole picture, and they also impose their own ideas on other groups through criticism. So, social media seems to increase the amount of information people receive, but it actually makes people more isolated and limits their exposure to their chosen circles.
Then, attention is scattered.
In the past, how long could you focus on work at once? One hour, two hours? I remember my friends who write code can sit for five or six hours at a time. But now, most people can't sit still and often need to take a smoke break.
This habit has developed over time.
When you turn on your computer, just open an app or website randomly, and the programmers, growth hackers, and marketers behind it are all trying to grab your attention, because only by obtaining your behavioral data can companies make more money.
Undoubtedly, the people behind the apps are always thinking about how to study behavior models, create models, and increase your click-through rate. What's even more frightening is that with artificial intelligence, there is an increasing amount of fake news and unreliable content online. In order to attract attention, self-media often spreads false information and uses misleading headlines and content that do not match.
In the end, fear of missing out.
Compared to ten years ago, there are more things worth looking at. Having more choices is not necessarily a good thing and can make people feel overwhelmed. There is a psychological term called loss aversion, which simply means that when there are so many good choices, we become uncertain about which one to choose.
For example:
For work, should you read books on data science or improve your communication skills to become a better leader? Should you focus all your energy on making money or balance work and leisure, and learn about the latest fitness methods and dietary habits?
These choices, combined with external reinforcement, leave you unsure of what to do. The content in the media and friends' circles is like junk food for the brain, which cannot be escaped every day.
Therefore, I think these four problems are pushing people towards an "information doomsday". From a god's-eye view, it may not be so terrifying, but indeed, the Internet is creating a personalized small world for each individual, making it difficult for you to break free.
02
So, how do you find valuable things in a sea of information noise?
It mainly depends on four dimensions:
First, whether the information is relevant to your interests and the current problem you are trying to solve. Second, whether the source is credible and whether there is arbitrary fabrication, which is very obvious in terms of data; Third, it must be practical, not just opening up cognition day by day, but not being used; Fourth, whether it can thoroughly explain each part of a problem.
From a rational perspective, I summarize these four principles as "breakthrough knowledge." However, during busy days, rational thinking cannot be readily available, so what can we do? The other side of breakthrough can also be understood as "trigger points."
What are trigger points?
Have you ever had the experience where a single sentence from your parents, friends, or leaders deeply changed your way of thinking and behavior? It could also come from a book, etc.
For example:
In many cases, Warren Buffett often mentions "The Intelligent Investor." He said he read it when he was 19 years old, and it had a significant impact on his investment philosophy; Elon Musk often mentions "The Hitchhiker's Guide to the Galaxy," and he said it helped broaden his thinking and think about bigger questions.
My trigger book is "Poor Charlie's Almanack." Charlie Munger introduced me to the concepts of mental models and thinking, and my book "Compound Thinking" was inspired by it, combining it with my work to write some reflections.
Therefore, breakthrough knowledge may come from a certain "trigger point" that deeply touches you. This is the ultimate leverage effect of learning. Now think about it, have you ever encountered it before?
If you haven't, it's okay. Some people only have it once every ten years, while others have it once or twice a month, bringing about significant or immediate changes. However, because significant breakthroughs are difficult, we can only continue to explore small breakthroughs.
How do you find these small breakthroughs?
As someone who reads regularly, my WeChat Reading bookshelf, Kindle, and computer are filled with high-quality content. Like you, I also have work and life, and I don't have so much time to explore.
What can we do?
Later, I developed a new method to overcome information overload. It is the four principles mentioned above, which are based on rational thinking. This is my personal experience and also the way many entrepreneurs learn.
A train runs fast because of its locomotive. Before using these four methods, you need a locomotive, which is the classic statement by inventor Charles Kettering: "A problem well-stated is a problem half-solved."
03
Therefore, based on this, I propose three solutions.
First: Problem prepositioning
There is a key point here. Inspirational knowledge and knowledge that overturns everything are different. Inspiration deepens understanding of what is already known.
For example, I have read a lot of basic marketing theories in the past, but recently, after studying scientific marketing methods proposed by major companies, I found that the core of this knowledge has many similarities with old theories. This means that in the near future, new knowledge from large companies may be forgotten by me, or only the parts that are different from previous knowledge will remain in my mind.
Breakthrough knowledge is different. It can challenge your basic views of an industry or the world as a whole and provide you with a completely new perspective.
To discover such knowledge is not difficult. Every time I encounter any new media content, I habitually ask myself: Can this thing fundamentally change life or work?
By planting the question in my subconscious, it drives my exploratory power. It allows me to avoid blindly consuming attention due to clickbait or recommended information. The first time I understood the difference between these two types of knowledge was when I watched an interview with Elon Musk, which you may have heard of.
The journalist asked him, "What advice do you have for future entrepreneurs?" Musk replied, "It is important to actively seek and seriously listen to negative feedback. This is something people tend to avoid because it is painful."
When I first heard it, I thought it was too simple, but later I realized that it was deeper than I thought, and it embodies the scientific method.
For example:
Centuries ago, everyone believed that the sun revolved around the earth. As early as the 3rd century BC, someone proposed the opposite view, but no one paid attention to it, after all, everyone saw the sun rise from the east every day. Later, Copernicus, after spending several years making a telescope, overturned this perception.
This example illustrates a point, "evidence that proves you wrong is much more important than evidence that proves you right." Scientists know that science is about being overturned, not confirmed.
Therefore, evidence that can prove your existing views wrong is more valuable than tens of thousands of pieces of evidence that prove you right. This is also why problem prepositioning and the importance of listening to negative feedback.
Second, find thinking models
Information has become an industry. Any popular book found on Amazon search can have several versions, and platforms like Dajia, Ximalaya, Zhihu, and Qingting FM in China gather summaries of many books and provide audio and short content.
The only advantage of summaries is that they effectively compress the core ideas, stories, usage techniques, and conclusions of books through platform operation models, making them appear to be practical knowledge. Now, AI can also quickly generate summaries based on articles.
From ancient times to the present, many philosophers have felt that a pile of books and a pile of ideas are not very useful, and they cannot be read in a lifetime. American psychologists initially said that we need to learn how to deal with this information and use frameworks. Later, they found that even frameworks cannot be learned.
What can we do? By 2013, when there was a lot of content overload, people discovered that "thinking models" are more advanced than learning various frameworks. Thinking models are universal laws that span time, fields, and all aspects of life, and they are more concise than the knowledge in books.
For example:
I like the Pareto Principle. 20% of effort will bring 80% of results. This principle also applies to business, interpersonal relationships, and health.
One of Warren Buffett's key principles is to eliminate ineffective busyness. Usually, we think that 20% of the key tasks account for 80% of the results. Buffett takes it a step further and selects the top 5 out of 20.
Another model I like is opportunity cost: in multiple-choice decisions, people tend to think that they must select the best option. I happen to think the opposite. I believe that the best option among the options you give up is the opportunity cost. Because people tend to make judgments based on first impressions, giving up the best option also means giving up the first impression.
You can try it next time.
By learning various thinking models, they will eventually emerge at the mental level. All the problems I have encountered in terms of making money and work stagnation have been answered by using thinking models and obtaining answers that go against intuition.
04
Third, learn how to learn
You may think, "Isn't it just learning a skill? I have many skills, and companies hire me because of my personal skills." This understanding is not wrong, and these are all obvious skills. However, I want to say that we should cultivate how to learn, which is a smarter way.
Many people know that they need to learn new skills, but few truly master the "learning methods behind learning," which also leads to weak transferability.
For example:
I used to learn design software, and after half a month, I finally learned how to use it. But when the software updates, I don't know how to use the new version anymore because I don't understand the basic principles of the software well enough. If I learn how to apply it and gradually understand its design principles, even if the software updates, I can quickly adapt.
The same goes for reading books.
In the past, I used to read books from cover to cover without missing a word. Later, I found that it took too much time, and I already knew a lot of the content. Now, I am used to looking at the table of contents first, getting a general idea of the content, and then directly reading the parts that I don't understand.
You see, from understanding principles to learning functions, to practical application, from reading from cover to cover to focusing on key points, this is learning "the methods behind learning." So, it is not only about learning skills but also about considering whether the learning methods are effective. This may mean that you need to make changes in your thinking style.
In simple terms, behind anything, besides how to do it specifically, there is also a bigger framework of why it is done this way. Most people also know that learning the methods behind learning is a special skill.
What are the results?
Because they are not aware of this, they cannot effectively use the accumulated scientific methods. For example, the backfire effect, the Dunning-Kruger effect, the halo effect, and group bias. Have you ever wondered why you don't know them?
Because without understanding the deep underlying principles, you don't know why these effects occur and how they affect decision-making. Therefore, deep-level learning skills are crucial for long-term success and one of the important abilities to maintain core competitiveness in a rapidly changing era.
My three strategies for processing information are: problem prepositioning, finding thinking models, and learning how to learn. If I were to add one more, it would be writing. When writing, it is best to focus on a specific field and organize knowledge into a system.
In this way, I can deepen my understanding and help more people learn.
In summary,
Your way of processing information may not be correct.
We cannot control the amount of content we encounter, but we can choose which channels to pay attention to and the quality of the information. Things that seem like practical knowledge may not help you change anything, so you need a set of filtering rules to avoid getting trapped in the whirlpool of information.
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