Hello book friends, welcome to continue to be a guest in the reading circle of little scholars, and today we will continue to talk about this book. Noise, as I mentioned yesterday, there are many people who oppose noise reduction and think that it is not efficient, but the author believes that noise reduction is imminent. He said it was all just an excuse. We need to weigh the costs and benefits of noise reduction, which is an important reason for conducting noise reviews, and it is often necessary to reduce noise because the cost of noise reduction is much higher than the cost of noise reduction. For example, when recruiting, it is more troublesome, and it seems that the process is extremely cumbersome through more rounds of screening, but it is better than recruiting the wrong person and bringing greater losses to the company, and it is more troublesome to fire an employee than to recruit an employee.
A case where artificial intelligence may replace human editing in the future.
I'd like to give an example.
That's the headline.
Recommend content through AI algorithms.
It helps us see the hot information that is buried in the news.
Let's be honest. When I first saw this pattern.
I also have some doubts.
But we have to admit it.
This trend is very meaningful.
If you think about it, you'll find out.
Our editors' recommendations tend to be geared towards large crowds.
And what the AI algorithm provides.
It is based on the unique needs of each individual.
The longer you use it.
The more accurately the algorithm can recommend your preferences.
And this is the key to our short-term success.
than editing. AI has a deeper and more objective understanding of users.
It is also the reason why the algorithm is able to remove a lot of noise.
It's like we're in the hiring process right now.
It also began to borrow from the operation of the short **.
to judge a person's lifestyle and Xi.
These hidden details.
You can't hide it from the algorithm.
You might say you're a hard-working person.
But the real situation is.
If you are short, there will only be some young ladies dancing**.
So. We see it very clearly.
Algorithms for noise cancellation.
For personalized recommendations.
For a comprehensive understanding of the user.
It's a major trend for the future.
More and more fields are turning to the use of algorithms to process complex judgments.
Although there are inevitably errors in the algorithm.
However. Over time.
Their accuracy is constantly improving.
Compared with. However, there is always an element of uncertainty in human judgment.
Therefore. A lot of devices are now collecting data about our lives.
In fact. In the era of big data.
No one can have privacy anymore.
It's not just a matter of mobile phone numbers and identity information being compromised.
We are already completely exposed to the surveillance of big data.
Our personal preferences and behavioral Xi.
It's all carefully recorded.
There are also concerns.
Reducing noise affects our flexibility.
Here's an example. In certain judicial cases.
Some situations are understandable.
Therefore, judges should be given lenient sentences in accordance with the law.
But. This discretion.
Whether it is really more beneficial to society as a whole.
Or will it hurt us more.
We have to think hard.
Although some cases will be more impartial due to the discretion of the judge.
But the presence of noise.
It could also lead to more unfair cases.
This in turn creates a fertile ground for corruption.
Positions of power have always been closely linked to corruption.
Too much centralization of power.
Corruption is everywhere.
Therefore. Disputed Discretion.
It's more dangerous.
Even if you wish to present a more flexible verdict.
It also needs to be supported by a noise cancellation process.
For example, the use of the judgment opinions of multiple independent persons.
Ultimately, a comprehensive view is developed.
To avoid possible errors.
The rules must be rigorous.
Discretion must not be too tightly controlled.
After all, in the fine text of the law.
It doesn't cover everything.
Vulnerabilities can always appear randomly.
This is the difference between Anglo-American case law and the letter of law.
Case law is more flexible.
Legal provisions, on the other hand, need to be constantly formulated with judicial interpretations.
to close the loopholes.
But it's a real problem.
In order to unify standards.
Eliminate the clutter. But it always creates new chaos.
The same is true for companies.
Your rule is to go to work at 9 a.m.
But there are always people who enter the company at 8:59.
Punch in first. Take a look at the morning market again.
Your rules must be enforced from 9 a.m. onwards.
But. There are also people who enjoy food at this time.
Next, start booting up your computer.
Make another pot of coffee.
rules though necessary.
People are alive.
You're constantly closing holes.
It can end up complicating the rules.
Is it okay to give up the rules?
No. Absolutely not.
Rules are better than no rules.
The author once confessed.
A system full of noise.
It is beneficial for the improvement of employee morale.
But it's not because of the noise.
It's because it allows employees.
Make decisions based on your own judgment.
Other words. Employees have their own room to play.
This is also the necessary foundation for the innovation and development of modern enterprises.
Compared with the high-pressure and militarized management of Japanese and South Korean enterprises.
This approach is actually very bad for innovation.
Employees can also feel deeply depressed.
Therefore. There also needs to be a balance between noise.
It's not that no noise at all is good.
We should keep some of the beneficial voices in place.
Such. You will be able to do as you wish.
Make an informed decision.
Show their initiative.
In real life.
Rules and guidelines have their own meanings.
The point of rules is to dictate how you should behave.
It aims to reduce individual control over power.
The guidelines, on the other hand, give a degree of autonomy to the implementers.
Just like the stated speed limit is 80 km/h.
And the norm may be.
Drive cautiously. Orderly passage.
The implication is the same.
But the guidelines contain a more human element.
The same applies to the investment community.
Rules limit the scope of your investments.
The guidelines teach you to look for valuable investments.
The author once told an example of what he had learned.
Rules are assignments assigned by the teacher.
It must be handed in tomorrow.
And the guidelines are:
Set your own tasks.
Write down all the important work.
This creates competition.
What we sometimes need is standards.
Not rules. Because some rules can't be established.
For example, everyone is equal before the law.
It's an ideal.
It's not a hard and fast rule.
For some other questions.
The absence of guidelines may have a deeper meaning.
Rules go hand in hand with standards.
For example. Carbon neutral.
It limits the amount of contaminants.
But the standard is to reduce air pollution.
Reduced CO2 emissions.
As for how to avoid pollution.
How to ensure compliance with carbon emission standards.
That's where personal wisdom comes in.
There are no overly strict rules.
When it comes to pilots.
There is also a set of rules and standards that need to be followed.
Airlines pay the most attention to the rules.
Because it restricts the pilot's freedom of choice.
Reduce noise distractions.
Reduce the likelihood of errors.
But in some critical situations.
The play of the pilot's individual abilities.
is the key to measuring its value.
Because airlines can't foresee every possible scenario.
So which one is more important.
Is it a rule or a standard?
The first thing to figure out is.
Which will bring more miscalculations.
In the field of innovation.
There should be greater use of standards.
And in the industrial system or in a disciplined army.
are more inclined to adopt rules.
There is no doubt about the importance of rules.
Sometimes, however.
We don't know that noise exists.
This kind of time. We tend to opt for instinctive reactions.
For example, when we are investing.
You may not realize that your judgment is correct.
So sell blindly in market fluctuations.
Due to the influence of emotions.
When we want to make a professional decision.
Only then can we really recognize the existence of noise.
And look for ways to fix it.
The problem with noise is.
We are often unaware of its existence.
Lack of self-reflection.
I always feel that my decision is the right one.
The mistake is not being aware of the noise.
Especially in some groups.
This is more common.
We don't just have to deal with noise.
It is also necessary to face the overall bias.
This also means:
Noise may not be a simple positive or negative offset.
Sometimes it may even be magnified exponentially.
Especially during the market bubble.
That's what happens.
Everyone has a different position.
Some shouted out 10,000 points.
Others expect to reach 20,000 points.
All kinds of ** voices are intertwined.
The bullish voices also vary.
Herein lies the problem.
Emotional disturbances. Can't see the real **.
The way now.
The only way to do this is to use machines for analysis.
Use strategies to complete the investment.
This is the best way to reduce noise.
Machines aren't foolproof, though.
But at least not affected by mood swings.
There will be no big bias.
The algorithm, on the other hand, remains impartial.
Build multiple models.
Synthesis of results from different models.
It can help us see the direction of the market more clearly.
Reduce noise. Although we have been doing so.
After all, I've always emphasized probability.
And the accumulation of this probability.
It is also obtained through many methods of judgment.
When all data metrics point to the same answer.
Then this probability is very high.
But if there are contradictions between the individual indicators.
This most likely means that there is interference in it.
So. We're going to think about it.
Exactly which one is the answer is more certain.
That's what this book is all about, this book Kahneman writes very around, it looks painful, but after the author condenses it for everyone, in fact, that's all there is content, where there is judgment, there is noise, where there is noise, We need to carry out testing, and there are many ways to detect, such as independent judgment and then summary, or the introduction of quantitative lists, or simply use algorithms, after discovering noise and deviation, it is necessary to make timely corrections, and finally get a relatively objective result by adding up the average, of course, some places need to formulate rules to eliminate noise, and some places may need to establish more standards, such as innovation and entrepreneurship, where divergent thinking is needed. It is necessary to establish more standards, and only when there is a need for unified thinking, it is necessary to eliminate noise and try to be regular. In investment, in fact, the author repeatedly emphasizes that strategy is more important than judgment, judgment is full of noise, and strategy is to eliminate noise. That's all. Tomorrow we will start a new Xi.