The advent of the AI ​​era: what is the vision for the future of society?

What's AI

AI is an abbreviation for artificial intelligence. It is a technology that allows computers to perform inferences, judgments, learning, etc. by imitating human intellectual abilities.

It has been almost two years since the release of OpenAI's AI service "ChatGPT," which answers questions as if it were having a conversation with a human.

Our society has been greatly shaken by the emergence of AI that can be easily used by ordinary people who are not IT engineers, and answers questions in the language we use at a search speed that humans can never catch up with.

The foundation of ChatGPT is an AI technology called generative AI. Conventional AI was researched with a focus on automating specific actions due to the limitations of computer performance. However, in today's world, where the evolution of machine power has made it possible to collect and process larger amounts of data, AI is now able to learn more than ever before.

The word generative, which is translated as generation, also means to create life. Generative AI can analyze trends from randomly collected data and literally generate completely new conclusions.

Let's take a concrete example. Previous AI could learn about cats by studying tens of thousands of images and literature related to cats, and classify, organize, and understand the concept of cats. However, generative AI takes a completely different approach.

By reading all kinds of data and learning the relationships and patterns in the data, it creates its own conclusion that a pet animal that has two eyes, walks on four legs, and has pointed ears at the top of its face is likely called a "cat." The more information it reads, the better it understands the information.

Even if it cannot distinguish between dogs and cats at first, the more it learns, the more it will understand the difference between dogs and cats. Therefore, generative AI can build its own theory of data classification and produce conclusions that humans would never imagine.

And those conclusions could lead to clues to solving environmental problems, energy problems, human rights problems, and other issues that humans have not been able to reach even after years of trying. While we are excited about the time-savings of office work, there is also this background behind the fact that large companies and countries are investing large amounts of money in researchers of generative AI.

However, since generative AI has the property of learning independently, there is a risk that it will evolve on its own out of our control. Mega clouds such as Microsoft's cloud service "AWS" provide a service that blocks information provision so that generative AI does not learn confidential information when a company uses generative AI.

This is now commonplace for mega cloud vendors. The fear of AI leaving human control is particularly strong in the West.

The background to this is the cultural background in which social norms have been created in accordance with the words of God written in the Book of Genesis in the Old Testament: "Be fruitful and multiply, and fill the earth and subdue it; have dominion over the fish of the sea, the birds of the air, and every living thing that creeps on the earth." Although it is not widely reported in Japan, demonstrations calling for an end to the development of generative AI are occurring all over the place, regardless of age.

By the way, don't you think that the generative AI system, which does not involve humans in the final decision (I'm not sure if I can call it that), is extremely compatible with the spirit of Web 3.0, which is to realize projects through connections between individuals without the intervention of a central administrator?

Unlike our Web 3.0 industry, which is still far from being beyond the realm of ideas, the time will definitely come when generative AI will become the center of the world. That is how fast generative AI has evolved in the past few years, and it has been accepted by the world.

This speed of adoption reminds me of when Windows 95 was released. Until then, personal computers were called microcomputers and were only for a few geeks, but they quickly spread throughout the world under the nickname of personal computers.

When personal computers first appeared, some media in Japan were quite vocal about the claim that "high-end machines like personal computers will never spread to ordinary offices, let alone homes." They said that machines that specialize in one function, such as word processors, are more cost-effective and more popular than expensive machines that can do everything.

Thirty years have passed since then. With the advent of smartphones, it has become commonplace for everyone to have a computer and be connected to the Internet. Even people in poor African countries cannot survive without the Internet.

If the concept of Web 3.0 is a kind of ideology that speaks of the future of the world, generative AI technology is likely to become established as the infrastructure that will support the world in the future. That is why it is important to know the current state of generative AI technology, its use cases, and the challenges it faces in order to explore business opportunities.

AI Glossary

• LSTM: Abbreviation for "Long Short Term Memory". It is now possible to improve efficiency by retaining part of the input information while performing the next learning.
• CNN: Abbreviation for "Convolutional Neural Network". An algorithm mainly used in the field of AI image recognition.
• DNN: Abbreviation for "Deep Neural Network". A computer reproduces a network that mimics the neural circuits of the brain, enabling human-like learning.
• NLP: Abbreviation for "Neuro Linguistic Programming". A series of technologies developed to allow computers to process natural language used by humans.
• LLM: Abbreviation for "Large language Models". Translated as "large-scale language model". By analyzing the probability of occurrence of sentences and words from a large amount of natural language, it is possible to output more natural language.

▶ Tesla's Elon Musk, a current leader in the IT industry, has also begun to actively participate in politics.

AI and blockchain will complement each other

In the recent US presidential election, a mountain of fake videos were produced in which candidates' faces were replaced and processed by generative AI to make it appear as if they said things they did not actually do. There are probably few people who have not seen these videos on various social media sites.

Since the emergence of ChatGPT, our society has clearly changed. With generative AI becoming so established, it is nonsense to regulate it, and we should consider that we have entered a phase where it is much more constructive to think about how we can coexist with it.

There is no malice in the generative AI currently circulating in the world. It is simply writing out products purely at the request of humans. There is no point in banning generative AI itself just because the products produced as a result contain lies. That is why blockchain technology, which can prove that it is unique and original data, shines.

If the AI ​​industry is like the stars of infrastructure construction such as roads and railways, then Web3.0 projects will play a role like water and gas pipes, supporting these brilliant results behind the scenes. However, in the real world, these industries will grow very steadily and steadily because there will never be a lack of demand.

In the past, when people talked about Web3.0, they had an image of extreme investment markets, such as crypto assets increasing by a certain percentage or losing tens of millions of yen overnight. However, as the Japanese government continues to develop laws in the Web3.0 field and Trump has made the slogan of becoming a crypto asset superpower, the Web3.0 industry has moved into a phase where solidity is required rather than flashiness.

The history of generative AI as an industry is still in its infancy, and there are many challenges, such as personal information protection and security. Coincidentally, blockchain holds the clue to solving these weaknesses.

At the same time, as generative AI progresses to AGI and ASI, we will be required to change our awareness of the work that humans must do. Currently, generative AI is limited to taking over clerical work and coming up with draft proposals.

This alone is starting to change the way we work, but it is entirely possible that in the future, AI will be able to do all the work that was previously thought to be only human. In that case, the question arises of what humans should do.

AI developers are trying to establish a basic income system, thinking of the people whose jobs will be taken away by AI, but if it evolves to the ASI level, it is entirely conceivable that even AI developers will no longer have jobs. At such a time, what should people do to interact with society?

Since I became involved in the production of this magazine, I have met people from IT venture companies in various fields, not just AI. When I talk to them, I feel that they are masters of "play." "I want to work efficiently so I can play," "I want to do big work because I want money to play," "I want to retire early and focus on play."

Decision makers who are considering introducing AI for digital transformation should reconsider what they intend to provide to their employees after introducing AI and improving time efficiency.

For hobby fishermen, it is enough if they can catch enough fish to eat, but that is not the case for fishermen. Since when did humans start to think of work and play as separate entities?

This may sound extreme, but the spread of AI is such a revolutionary event that we have to think about such philosophical things at the level of salaried workers. We need to be aware that we are witnessing this era by chance.

At least Sam Altman has already begun to design systems on his own, thinking about what will happen after society advances due to AI. We must not let this social revolution proceed based only on the thoughts of a few geniuses. Because we will also be part of the society that will live after AI has brought about a revolution.

The recent House of Representatives election ended with a shocking result of the ruling party's major defeat. This is the result of our serious consideration of how we want to transform society. How generative AI will change society is still in the midst of the process.

The time has come to clearly express our intentions about what kind of society we want to create with AI. Fortunately, we have a tool called blockchain, which allows decision-making without a central authority.

Many people say that the advent of AI has improved the efficiency of their work and has brought many benefits. However, we forget that the current generative AI is still evolving and has not yet reached the specifications that developers envisioned. When the Industrial Revolution occurred, one of the major changes in the UK was the increase in pubs throughout the city.

When you think of the UK, you think of pubs, which have now become tourist attractions, but it is said that this originally started when factory workers who were forced to work 24-hour shifts began to seek alcohol as a way to forget the hardships of work. We cannot know what will happen after social change begins until it is actually observed.

However, the change has already begun and there is no turning back. In that case, the only thing you can do is try out a generative AI service yourself and experience the essence of why people are making a fuss about it changing the world.

If you try it out for yourself, you will find that the current generative AI service is not complete, so you will find some difficulties in using it and some issues. Some of these issues have the potential to become the seeds of business in the coming AI era. You can put it up for approval within your company, or you can set up a DAO and discuss solutions together.

What is clear is that current generative AI cannot generate things from scratch and always requires human prompts. In other words, it is still possible to initiate changes based on ideas found by humans.

What is needed in the coming age of AI is not a craftsman-type worker who perfectly completes any request that is received. It is a leader-type person who can present the questions and ideas that arise, even if they do not have the skills, and hopefully recruit others to find a solution.

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