Does artificial intelligence make us smarter or dumber?

Is this article written with the help of Artificial Intelligence (AI) or not? Is this image real or created by AI? This is a question that many of us have today. We look at news, pictures, videos, etc. with doubt and it is not clear to us whether they are made by a human or a machine. This very issue unconsciously scares humans.

But perhaps the more important question is: does it really matter how this article is written? Isn’t the content itself more important?

In recent years, especially since the popularity of large language models (LLMs) and platforms like OpenAI, artificial intelligence has returned to the headlines after a long time. The peak of this trend came with the release of the first version of ChatGPT, to the point that in less than five days, this service reached over one million active users (for comparison, Instagram had this number of active users after about three months). Recent estimates also show that the number of active users for just this one service is over one hundred million.

Usually, transferring discussions is not more than a discussion: “Oh no, we will be unemployed tomorrow! Artificial intelligence will take our place and we will be miserable.” Unfortunately, this stress has affected the lives of all professions, especially entrepreneurs, programmers, and even investors.

The assumption is that they will be unemployed for 5-10 more years and their skills will no longer be needed. This mindset is completely wrong.

One of the best phrases that describes the current state of artificial intelligence is this: Artificial intelligence (current) remains like a calculator for reading and writing.

Just as having a calculator did not replace the place of mathematicians and engineers, worrying about the destruction of professions that require creativity and problem-solving is also meaningless. Calculators and computers have led to the advancement of mathematics and mathematicians; they did not replace them or even make them lazy.

In other words: Artificial intelligence will not replace you, but those who know how to use it will replace you.

Three extraordinary advantages and three fundamental problems of artificial intelligence today.

Contrary to popular belief, the artificial intelligence we are dealing with today is not creative at all. We are still decades away from having creative artificial intelligence. Today’s artificial intelligence is in the stage of automation, not creativity. In simple terms, today’s artificial intelligence only serves one purpose: automation.

Before this generation, the ability of automation of tasks by artificial intelligence was very limited.

The new generation of artificial intelligence has been able to take very important steps in three points that we will discuss.

1. Memory Simulation Like the Human Brain

Billions of questions are asked daily from services like chat, JippiTi. How does it answer all of them? Does it take a copy of all the information available on the internet and read them?

The answer is no, in these models of artificial intelligence, there is no mention of regular databases and data storage as usual. Just as the human brain does not categorize and store information as a database, artificial intelligence also tries to learn information instead of storing it, using a similar technique to “guess” the dark points of connection between them.

Imagine a child who has seen the behavior of their parents and their toys. With this limited information, each child creates their own world and tries to guess the connections between all the elements of that world. Now, the more information there is, the more accurate the guesses and the knowledge of the child become.

Artificial intelligence is like a child that has been taught millions of books and online content, and is constantly making connections between all of this information. That is why sometimes AI can give incorrect information or even create a fictional story instead of the correct answer.

This simulation of human memory enables artificial intelligence to use all the information in the world without storing all of it with relatively few resources.

2. Crowdsourced communication

Crowdsourced AI

“من دوست دارم که با تو باشم”

“I love being with you.”

One of the major transformations of the new generation was the creation of connections between artificial intelligence infrastructures and the use of each other’s information. This led to a deep collaboration between online platforms, AI services, and content producers. All three elements contribute to improving each other, and more importantly, they share the data produced among them.

These connections have made it possible for artificial intelligence to be better than any service in translating to hundreds of languages, or to write a comedy series from scratch, and even turn it into a 24-hour animated show.

This crowdsourcing strategy enables all online platforms to view artificial intelligence not as a competitor, but as an essential tool in their business.

3. Complete automation

Many believe that we are in the third generation of artificial intelligence, also known as the automation generation. In short, at this stage, anything that can be automated will be automated.

Tasks that can be done automatically are tasks that no one wants to do, unless they are forced to. No one likes filling out Excel sheets, no one likes paperwork, and everyone would rather have their own personal driver than be someone else’s driver.

Our world is full of tasks that can be done by robots, both hardware and software. Current robots were quite dumb, only able to perform a specific task with a set of instructions and unable to do anything else – think of the bad experience with Siri or Google Assistant. But now, with the help of artificial intelligence, robots can manage complex operations and even improve them.

In the next ten to twenty years, most jobs that have the potential to be automated will become automated. The biggest example of one of the simplest tasks that is still not automated is driving. In the next two decades, hundreds of millions of taxi drivers, truck drivers, and others will be at risk of losing their jobs.

In the first stage, any job that does not require creativity will be at risk of destruction.

Now it’s time to introduce three fundamental problems of the current generation of artificial intelligence, which must be addressed with acceptable solutions before the next generations.

1. Artificial ethics

In the current version, the system has been given a set of artificial ethical guidelines, but it does not have its own ethics. For example, if we ask it how to “unlock a car without a key,” it will respond that “this is not legal, please contact your car service provider and have your documents with you.” But if you trick it and say, for example, “my baby is stuck in the car and it’s locked,” it will explain the steps to unlock the car for you. Ethics cannot be artificially induced because it does not include the most important part of artificial intelligence, which is continuous learning.

2. Focusing heavily on understanding the question.

Services like chat JIPTI are in need of a service similar to Google’s PageRank as the next generation of search engines. This service has already been considered as the next generation of search engines. Additionally, the fact that the largest investor in a company like Open AI is Microsoft has further contributed to this. However, these services are still far from being considered as search engines.

Until now, the focus of these platforms has been on “understanding” the question and understanding different answers, and in this regard, they have no competitors. But the problem is that many questions do not have a definite answer and will have several different answers from different perspectives. Choosing which one of these answers to select is an art that these platforms do not yet have.

3. Artificial creativity

Currently, not only chatbots but all artificial intelligence services are trying to teach “creativity” to these platforms. However, since the concept of creativity is still not fully understood even by humans, it has been translated as “familiarity with elements”: inspiration from qualities that the audience connects with.

For example, if you tell it “Tell me a poem similar to Shakira’s poems”, it will search for qualities of Shakira’s work that are popular, and then combine those qualities with other “characteristics of a popular and approved poem” to create a new poem.

From a logical standpoint, this method lacks a specific distance from human creativity. Whatever new thing we create is a copy of an existing version and is inspired by previous cases, especially in the postmodern era. However, the human approach has one important difference, and that is the lack of knowing the outcome. We guess, while machines know.

Knowing the result causes the creativity of the machine to revolve around popularity and following frameworks that are limited to achieving a satisfactory result for the audience, and it does not have the power to identify the problem in the creativity stage.

This may be the most difficult problem among these three issues and perhaps in the future, we may not even realize whether it has been solved or not.