Why AI Implementations Fail. The Solution of 'Pre-design' Derived by Japan's EVΛƎ (Eva).
Amulet Plus LLC has announced its 'April Dream' to establish 'EVΛƎ (Eva)', a Japan-originated AI design philosophy that pre-integrates responsibility and transparency into AI decision-making, as a global standard.
📋 Article Processing Timeline
- 📰 Published: April 1, 2026 at 09:00
- 🔍 Collected: April 1, 2026 at 01:00
- 🤖 AI Analyzed: April 22, 2026 at 04:28 (507h 27m after Collected)
Our company supports April Dream, a project that aims to make April 1st a day to share dreams. This press release is the dream of 'Amulet Plus LLC'.
Our Dream
Our dream is to make 'EVΛƎ (Eva)', an AI design guideline originating in Japan, a new globally trusted standard.
The more AI evolves, the freer humans can become.
We believe this to be true.
Fundamentally, AI should expand human potential and support creativity. In reality, however, there are many situations where it's difficult to understand how AI made a decision, concentrating the final confirmation, explanation, and locus of responsibility on humans.
That is exactly why we believe that beyond merely improving AI performance, we need a design that incorporates responsibility and transparency into the AI's decision-making process in advance.
A Perspective Needed by Society Now
In recent years, the use of AI has expanded rapidly. Especially with the advancement of AI agents, new challenges and troubles are becoming apparent in the field.
- Even if the AI's output looks plausible, the background of its judgment is difficult to understand.
- Because humans have to handle the confirmation, correction, and explanation afterward, the workload ironically increases.
- When problems occur, it easily becomes ambiguous who decided what, where, and how.
This situation cannot be resolved simply through operational ingenuity. We believe the underlying issue is that the 'decision-making structure' is not sufficiently designed at the stage before the AI operates.
The Essence of the Problem: The 'Blank Space' the World Has Not Yet Fully Articulated
Many people view the AI problem as 'not knowing because the inside is a black box'.
However, the essence lies beyond just that.
*A black box refers to a state where it is difficult to understand the reasons behind an AI's decision, making it impossible for humans to trace the basis of the judgment.
A major challenge currently facing AI governance is that the means to structurally define 'who decides what, when, and where' before the AI is executed are not sufficiently established.
Our Dream
Our dream is to make 'EVΛƎ (Eva)', an AI design guideline originating in Japan, a new globally trusted standard.
The more AI evolves, the freer humans can become.
We believe this to be true.
Fundamentally, AI should expand human potential and support creativity. In reality, however, there are many situations where it's difficult to understand how AI made a decision, concentrating the final confirmation, explanation, and locus of responsibility on humans.
That is exactly why we believe that beyond merely improving AI performance, we need a design that incorporates responsibility and transparency into the AI's decision-making process in advance.
A Perspective Needed by Society Now
In recent years, the use of AI has expanded rapidly. Especially with the advancement of AI agents, new challenges and troubles are becoming apparent in the field.
- Even if the AI's output looks plausible, the background of its judgment is difficult to understand.
- Because humans have to handle the confirmation, correction, and explanation afterward, the workload ironically increases.
- When problems occur, it easily becomes ambiguous who decided what, where, and how.
This situation cannot be resolved simply through operational ingenuity. We believe the underlying issue is that the 'decision-making structure' is not sufficiently designed at the stage before the AI operates.
The Essence of the Problem: The 'Blank Space' the World Has Not Yet Fully Articulated
Many people view the AI problem as 'not knowing because the inside is a black box'.
However, the essence lies beyond just that.
*A black box refers to a state where it is difficult to understand the reasons behind an AI's decision, making it impossible for humans to trace the basis of the judgment.
A major challenge currently facing AI governance is that the means to structurally define 'who decides what, when, and where' before the AI is executed are not sufficiently established.