Web3 people facing AI replacement anxiety Don’t panic, can’t smash my rice bowl, can’t ruin my job.

Web3 people facing AI replacement anxiety. Don't panic, can't smash my rice bowl, can't ruin my job.

The subtle relationship between AI and Web3 is best described as a combination of competition and cooperation.

From a capital perspective, the story of AI is obviously more appealing and practical than Web3. The arrival of ChatGPT easily shifted the funds that were originally flocking to Web3 to the field of AI, clearly demonstrating the substitutability of capital. However, from a market perspective, Web3, which has always been advancing with hot trends, is unwilling to let go of opportunities and is incorporating AI into projects on a large scale. The outer shell of Web3 is like a chameleon, changing from the metaverse to AI, just a matter of a tweet.

For the workers in Web3, this relationship becomes even more complex. They worry about being replaced by machines and also worry about not knowing how to use machines and being replaced. Their hesitation towards machines comes and goes like tides. But what is left behind in the poorly regulated Web3 is only various absurd simulations and pseudo-concepts, making descriptions of workers rare.

From a macro perspective, since the emergence of machines, the existential crisis surrounding the coexistence of machines and humans has never stopped. Humans can create things much smarter than themselves, but they will also fear these things. This is both a manifestation of human wisdom and a subconscious instinct to resist those who are different.

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In the field of Web3, where human greed and desires are fully embodied, this conflict can only become more intense.

Will Web3 workers be replaced by AI? With this question in mind, the author interviewed four workers in the industry who are currently using AI. In their different jobs, some expressed pessimism, believing that their work will be replaced in the long term and they need to transition. Others were indifferent, emphasizing that AI is difficult to handle the deceitful nature of humans in Web3. Although opinions differ slightly, the interviewees unanimously believe that AI can never gain the upper hand in the struggle against complex human nature.

It seems that at least in Web3, which is difficult for AI to comprehend, workers are still safe.

01. “AI can only guarantee correct processes” – Ivan, a small-scale asset manager

Ivan works in an asset management institution and can be considered a senior worker to some extent. His main job is to handle a series of tasks related to funds, including storage, appreciation, and operations. However, if we look at it in more detail, it is similar to traditional institutional risk control, which involves monitoring transactions, identifying potential risks, and intervening effectively. From his perspective, AI is far from sufficient to affect his work because AI struggles to identify the problems that humans face. Here is his account:

My job sounds impressive. I work in an institution and handle asset operations to achieve value appreciation and risk control. Before this job, I worked in a local bank in risk control. In terms of the nature of the work, the two are actually not much different. The difference lies in the fact that risk control emphasizes monitoring and early warning, while operations have the need for value appreciation.

After the emergence of ChatGPT, our boss mentioned the need to learn and use it to improve work efficiency. We even invited so-called professional questioners to train us. However, since it was not mandatory, as far as I know, people actually don’t use it very often. But this does not mean that ChatGPT is not useful or to simply criticize it. It is difficult for AI to replace human work in our industry.

For a simple example, many of our large B2B clients transfer millions of dollars, and the risks of using AI for approval are obvious because AI cannot see the processes and conspiracies behind the money. On the surface, it may just be a sum of money, but behind it could be a complex combination of money laundering, distribution, fraud, and other events. This is similar to banks, where seemingly automated processes are audited by human forces in various departments, sometimes even dozens of them, for each node of the transaction.

For retail clients, the degree of automation is relatively higher. AI can automatically identify operations such as witching and double spending, but it cannot be completely entrusted to AI. Just like when we apply for a bank card, we often require a customer manager to verify our identity in person. Why? Because AI finds it difficult to verify humans through processes. AI only needs to ensure that the process is correct, but only humans can identify human problems. Throughout the entire financial industry, despite the digitalization that improves efficiency and the various complex systems, human labor is still the main force. Anything related to money needs to be ultimately responsible to humans. There have been many painful lessons in history.

But you can’t say that AI is completely useless. Otherwise, giants wouldn’t be investing resources in its development. Take myself as an example, when LianGuaiperwork doesn’t want to work, I also use AI and then refine and modify the content. Also, assignments and contracts that everyone thinks can be easily replaced are not that simple. They are templates approved by the legal and financial departments. So you see, humans are the most important.

02. “What is more important is what AI can do in the future” – Iris, Content Media Editor

I work as an editor in a content media company, which is usually considered one of the easiest positions to be replaced by AI. In general, AI, such as GPT, has become quite common in our daily work. Especially in the current industry downturn, when our originality is decreasing, we use AI for translation, news grabbing, and other tasks, which can greatly improve efficiency.

In terms of original content, the role of AI varies depending on the content requirements of the article. For text processing, GPT’s capabilities are quite strong, so for basic drafts with a given outline, the output is generally close to the target. However, due to the industry’s attributes, there are limitations in terms of understanding specialized terms, adapting to human reading habits, and other aspects, so manual adjustments from multiple perspectives are still needed. In-depth articles have relatively weak connections with AI. In-depth articles rely more on personal field visits and investigations, which are difficult for AI to replace. Even if we try to feed AI with data to generate articles, the results are usually poor.

The performance of the lower version of GPT is even more mediocre. A colleague used GPT3.5 to write an article, but without data after 2021, the latest data needs to be fed into the model sentence by sentence for it to learn in advance. After trying for a whole day, he finally produced an article, but most of it was correct gibberish, and there were even illusions of fabricated content. In the end, either major revisions had to be made or it became a useless draft. Of course, this is also due to our personal lack of questioning ability.

Back to your question, will AI replace human labor? I believe that to a certain extent, it definitely will. While it may seem limited in what it can do now and everyone takes it for granted, what is more important is what it can do in the future. No one can possess a learning ability more powerful than AI, nor can anyone understand the black box that AI emerges from. This means that through continuous deep learning and analysis, AI will emerge with more intelligent abilities at some stage. Creative work with a repetitive nature may be replaced earlier, such as coders, editors, and other cultural industry practitioners. This type of work is creative, but it also has elements of learnability and repetitiveness. As long as there is text to learn from, AI will definitely outperform humans. Therefore, humans need to unleash more of their imagination.

Looking back at every technological advancement, there are always positions being replaced. This is the tool revolution brought about by technological revolution, and it is irreversible. The Luddite movement ultimately became a footnote in history. Currently, from the bear market until now, the company has already laid off 40% of its employees, and there are even fewer content creators. Perhaps this is also related to AI to some extent?

Personally, I will try to find the more core parts of work, the parts that are difficult for AI to replace. For example, I will value opportunities to go out and accumulate connections more than before. In any case, these are areas that AI has difficulty accessing.

03. “Legal and ethical risks cannot be avoided” – Vivian, Crypto Lawyer

In fact, this question can be expanded to a broader scope. In traditional fields, can AI replace lawyers? Personally, I don’t think it can, for a simple reason: legal work involves dealing with people, and it involves legal and ethical risks that cannot be avoided.

For example, in litigation, lawyers have a responsibility and duty to keep the information provided by clients confidential. This is not defined by the good or bad intentions of outsiders, but rather defined based on the interests of the parties involved in the case. Unless it involves actions that endanger national security, lawyers should keep the information confidential. The public nature of AI makes it difficult for it to achieve this. It can even send the information you give it to other inquirers at will, which clearly violates the professional ethics of lawyers.

Similarly, in legal consultations and other non-litigation contexts, AI lawyers will also behave in a less empathetic manner. They have difficulty perceiving the true needs or implicit meanings of the clients. In many civil litigations, clients often indirectly ask for advice, and at the core, it’s about how to protect their own interests, even if they are at fault. But AI has difficulty understanding this type of need. If you ask how to reasonably avoid risks, it may ask you to spill everything or even turn yourself in. Therefore, currently, AI can only handle some inquiries with clearly defined questions and established answers, and can only do some non-private desk work. Its limitations are obvious.

Another thing worth noting is that AI can have machine hallucinations, which is a taboo for legal service professionals. Some time ago, a peer fell into a pit. Lawyers from Levidow & Oberman law firm in the United States submitted documents assisted by AI in a dispute, only to be discovered by the judge that some precedents did not actually exist. As a result, the law firm was fined $5,000 for providing false information to the court. Providing false information is a violation of the lawyer’s law and a rule explicitly prohibited in legal practice, but so far, AI hallucinations have not been resolved.

In Web3, the above limitations will be further amplified. Web3 is a very chaotic and ever-changing industry. Although laws and regulations have been introduced both domestically and internationally in recent years, virtual currencies are still a new phenomenon in civil and commercial fields. Based on judgments from various courts, the understanding is not unified either. In this field where fresh concepts emerge frequently, using AI as a lawyer will only bring more complex problems. For example, stablecoins. The regulatory approaches in different regions vary greatly. This field is still a vacuum zone in Hong Kong, but regulatory schemes have been introduced in Singapore and Europe. It is difficult for AI to provide targeted responses.

In addition, lawyers engaged in the virtual currency industry have strong qualifications themselves. In addition to having a deep understanding of the industry, they also need to possess strong financial services regulation and securities law capabilities. They need to act as a connector between the court and the parties involved, reducing information asymmetry and noise. It is not easy to achieve all these, so I believe that AI can assist in handling tasks such as desk research to a certain extent, but it is far from being able to replace human lawyers.

04, “Elimination is just a natural social law” – Leo Developer

In fact, this question arose a few years ago with the emergence of Alpha Go, and since then, many automatic programming software have emerged. This time, due to the impressive performance of ChatGPT, it has caused a panic in the industry.

If this question was asked before last year, I would firmly say that it won’t replace humans, but now, I may think that some programmers are at risk of being replaced. From the perspective of AI’s advantages, AI can already handle technical problems that are slightly difficult, such as arrays/strings and dynamic programming. At the same time, it has certain capabilities in dealing with common problems such as repetitive code generation, documentation and comments, and testing.

In my daily work, I also use Github Copilot. I am not an exception. Previously, GitHub conducted a survey and found that 92% of the 500 developers surveyed used AI coding tools to complete work and other projects. The use of AI tools is not for nothing but because it can effectively improve efficiency. Our work essentially involves translating between machine language and human language, and there are many repetitive specific tasks. In these tasks, AI’s performance in using chain calls is excellent.

However, for developers, the most essential ability is programming logic, and the most difficult point is building requirements, not just simple programming. In this field, AI does not yet have complete engineering capabilities.

In actual software engineering, code is written according to customized requirements. In this complex relationship, the interaction, technical background, and objective laws of the modules are difficult for AI to discover through learned databases. The reason is that this type of data is usually confidential, which means that AI is difficult to compare with human beings in terms of business abstraction, modeling, and architecture. In addition, AI also has issues such as code security and intellectual property rights.

On the other hand, compared to the traditional Internet, Web3 has decentralized differences in the architecture of front-end and back-end. The most obvious example is that after publishing smart contract code, developers cannot simply patch and update it. Web3 is more related to money and has high sensitivity. Leaving out humans as an option will bring many practical problems. It can also be seen in the industry that there are many projects that have run away with funds, and anonymity often makes people feel insecure.

As a common joke in the industry, “when everything is fine, decentralization is the way to go, but as soon as there is a problem, it is necessary to seek centralization.” Therefore, regardless of the situation, humans are very important in this process. However, from the perspective of the programming industry, in the future, programmers who do not use AI or only use limited tools like CRUD will be eliminated as a natural social law.

05. Conclusion

In the competition against machines, humans, made of flesh and blood, are often at a disadvantage. Therefore, not only in Web3, but also in many other aspects, it is not absurd to consider the substitution of humans by machines.

But precisely because of the existence of fragile human nature, the complex network formed by humans and the spiritual connection within it are difficult for machines to penetrate, which in turn benefits human beings themselves.

In the future, perhaps more important is to protect and cherish our own humanity, unleash our creativity, and not become walking corpses in the concrete jungle, ultimately becoming nourishment for AI.

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