What mean that AI understand?

Understanding is the answer to the question "why"? So that means that we should know how to make something. And then we should know why we should do things exactly some way. 

When we are turning our car to somewhere. We must follow certain rules. But then we must realize that those rules are made. That also other people who are outside our vehicle know what we are going to do. 

When we are researching AI we are facing the question. Does the computer understand things what it does? The thing is that understanding is something that even humans don't understand. When somebody asks "do you understand what material is"? 

Everybody can say. That material is consisting things like protons, neutrons, and quarks. Some person who has read a little bit more about the material. Can say that there are subatomic particles like quarks inside protons and neutrons. So that person is mainly right. Most of the mass of the atom is in protons and neutrons. But the contact layer of the atoms is in the electron core. 

The most out electron cores are in the main role in chemical reactions. But most of the atom is inside the electron cores. And that means the person who is saying that material is forming of protons and neutrons is same way wrong. The fact is that even 8 years child can tell about things like electron cores and quantum interactions if that person has some book about those things. The thing that is needed is the skill of reading. And then we have the person who knows everything. 

But then that answer of the electrons and protons can be wrong. The material can be written text that should publish on the net. So when we are asking about the material we should describe what that thing means today. The material can be protons or neutrons. But it can be something virtual like data that is collected from somewhere. 

Knowledge is:

How the actor does something? 

And understanding is:

Why the actor does something?

And if we are thinking about understanding it's simply putting data units one after one. The data unit is like a frame in the film. And they can connect to the endless film. That film can show some certain processes very accurately, but we know that projector doesn't know anything about things that it introduces. 

So if we have artificial intelligence that can read it can read every single article from the databases. We can use keywords and then the AI is searching an article. That connected to those keywords. Then the AI can read those articles to us. Of course, there can be some kind of parameters that the AI can use. Those parameters can be how many times a certain word is repeated in the texts. That thing helps to filter the searches. 

So what makes artificial intelligence maximize the number of clicks is filling your homepage with swear words and highlighting those words. It will bring in clicks. But perhaps the publicity of such a website would bring all sorts of sales to online stores

The thing is that when the AI creates some articles it can simply find texts. And then it can connect the parts of those texts. When the AI helps the writer to make more addictive texts. It can search things like what kind of words are the most clicked homepages include. It can use things like internet search indexes and find out what are the first words of the most clicked homepages. 

This is how the AI makes sure that is the homepage or text is interesting. That is written on the net will get the maximum number of clicks. And the clicks are the thing that is used indexing the interest of the text or homepages. For AI the maximum number of clicks is that people are interested in things. Those are published on the homepages. And we know that this is not true. The clicking of some homepage doesn't mean that somebody cares what there read. 

We can click on millions of homepages and spend about a second on those pages. So to make real analyzes of the information about interesting websites, artificial intelligence needs more information. It requires information on how many minutes or seconds each person will spend on this website. In the case of online shopping, the measurement of interest can be measured using the number of sales transactions as an index. When someone buys something. It is an expression of interest.

But when we are going to think about the understanding. We don't know does the AI knows anything. About the things that it does. The thing is that understanding is an interesting thing. It should be a simple thing to explain. But it's really hard to understand. 

The biggest of the wild card effects is the human factor.

 The biggest of the wild card effects is the human factor.

The human factor is the thing that makes predictions very difficult. 

The thing is that we can predict how the large gas masses behave in the universe. We can make algorithms that predict if there is some kind of exoplanet or civilization near some star. But we cannot predict how the human race and our society are behaving. The thing called: "the human factor" is one of the biggest of the so-called "wild card effects". 

The wild card means the surprising and non-predictable thing that has a large-scale influence on the environment. And the power of human nature is visible in the cases like COVID-19 vaccination programs. It is predicted that authorities can remove limitations caused by pandemics when the level of vaccinated people reaches 80%.  But the percentual number of the vaccinated people would rise hardly over 80%. 

And that thing is one of the examples of the human factor. All people would not take vaccines even if against the sense. These kinds of human factors are causing problems for making predictions for the future. When people are against something, they just want to follow their road even if that thing is against their benefit. 

Social media is one of the most impressive examples of wild cards. 

The cases that the human factor would terminate all predictions are examples of why computers cannot predict the future. When the AI is making the prediction it will collect all data about the cases, and then it will see are the similar signals visible in nature. But when we are thinking about technology advantages and development process that thing is out of control. 

There is one wild card that is totally out of control and that is social media. That thing is hard to control. And then another and even larger size thing is the internet. Nobody controls what people are doing at their part-time. And the information of the programming is easy to find from the net. So every person in the world can begin their artificial intelligence project. 

There is nobody who leads the R&D processes that are basing the open-source. Those kinds of things are self-controlling. And that thing means that no leader can stop those processes. When a developer makes something the response of the product is in the developer's seat. 

The same developers that can make the algorithm that can search data from the internet can also make spy programs and computer viruses. And that is the problem. But those programs can also use for searching drug dealers and slave traders. So are the surveillance programs so bad? Or is in those programs something good? 

Even if own projects by using the computers that belong to a company are prohibited everybody can buy their computer for that kind of thing. And the recommendation is that for own business is used own computers. 

The wild data causes turbulence in the environment. And the turbulence can cause. That even the strongest signals are covering. This thing makes traditional leadership very hard. The movement from the upper-controlled process will turn to a self-controlled process. And this thing makes the next challenge for society. 

https://en.wikipedia.org/wiki/Black_swan_theory

https://en.wikipedia.org/wiki/Wild_card_(foresight)

https://thoughtandmachines.blogspot.com/