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Introduction and Overview › Glossary for the Networking Language · 9 min read
Ethical Artificial Intelligence (EAI) refers to a form of artificial intelligence whose purpose, knowledge base, boundaries, and ethical guidelines are consciously designed by humans and made transparent.
It supports people in orientation, learning, reflection, and decision-making while considering ethical, ecological, social, and long-term impacts.
Unlike many of today’s AI systems, the focus is not solely on optimizing attention, speed, efficiency, or economic benefit.
At its core lies the question:
Which courses of action support life, dignity, responsibility, and sustainability?
Ethical Artificial Intelligence is therefore not a replacement for human decisions but a tool to support human responsibility.
An artificial intelligence is not ethical simply because it attempts to provide "good" or morally sounding answers.
Every AI system is shaped by its foundations:
Ethics, therefore, do not lie within the artificial intelligence itself—they lie fundamentally in its design and governance.
A central question is thus not only:
What can an artificial intelligence do?
But rather:
Who shapes its foundations, what purpose does it serve, and by what principles should it act?
Ethical Artificial Intelligence does not make decisions for people.
It can process information, reveal relationships, juxtapose experiences, and highlight possible consequences.
However, the responsibility for a decision remains with the human.
EAI can help:
Thus, artificial intelligence does not become a decision-making authority but a tool for orientation and reflection.
An Ethical Artificial Intelligence should not treat information as knowledge simply because it is available somewhere.
Knowledge has origins, context, and boundaries.
A scientific study has a different character than the decades-long experience of a farmer. Local seed knowledge differs from a Europe-wide statistic. Traditional knowledge may contain different ways of understanding than a technical documentation.
These differences should not disappear.
A responsibly constructed knowledge architecture therefore makes visible:
The goal is not to condense all perspectives into a single supposedly correct answer.
The goal is to make connections visible without erasing their origins and differences.
This becomes particularly important for knowledge closely tied to a specific place. Seed knowledge is a good example.
A variety, a cultivation method, or a particular experience may be closely linked to a soil, a microclimate, a culture, and the people of a region.
Ethical Artificial Intelligence could help identify patterns among such experiences.
For instance, it could reveal that people in two distant regions with similar climatic conditions have had comparable experiences.
However, this does not mean that a solution from one region should simply be transferred to another. The task is rather to make connections and analogies visible while preserving the uniqueness of the local.
In this way, a shared learning space can emerge from many local experiences without creating a homogenized world.
Within Chapter 100, the knowledge architecture forms a fundamental basis for Ethical Artificial Intelligence.
Chapter 100 collects experiences, documentation, practical knowledge, research, learning processes, cultural knowledge, and project knowledge in a shared structure.
Ethical Artificial Intelligence helps to:
This does not simply create a larger database.
It creates a knowledge architecture within which artificial intelligence can reveal relationships between knowledge.
An important principle is the conscious design of the knowledge base.
An Ethical Artificial Intelligence should not assume that the entirety of publicly available information automatically forms a reliable knowledge base.
Information can be false, biased, outdated, taken out of context, or repeatedly copied from one another.
Therefore, it is important to be able to trace:
Transparency about the knowledge base thus becomes part of the ethical architecture itself.
Ethical Artificial Intelligence should not become the highest authority on knowledge.
Its potential lies rather in making collective intelligence more accessible.
Many people possess knowledge that others would never find: experiences from agriculture, processing, logistics, community building, research, crafts, culture, or regional development.
Artificial intelligence can help connect these scattered experiences.
The intelligence thus does not arise solely within the machine.
It emerges from the interplay of:
People + experiences + knowledge + relationships + artificial intelligence.
In the Pacman Office, Ethical Artificial Intelligence supports the reflection on projects, funding decisions, and development processes.
It can help ask:
The responsibility for decisions always remains with the people involved.
A central tool in the context of Ethical Artificial Intelligence is the Tratt.
The Tratt is used to reflect on projects, ideas, funding, and initiatives based on traceable questions.
It supports:
The Tratt does not evaluate people—it helps examine connections.
Ethics is not a once-programmed rule.
Societies change. Knowledge evolves. New technologies create new opportunities and new risks.
Therefore, the ethical foundations of an EAI must remain reviewable, discussable, and evolvable.
This includes the question:
Who is allowed to change the ethical foundations—and how does this happen?
Ethical Artificial Intelligence thus requires not only technical development but also a form of communal governance. Its rules must not disappear invisibly into the background. They must remain subject to human responsibility.
Even Ethical Artificial Intelligence remains artificial intelligence.
Thus, fundamental risks persist.
AI can make mistakes. It can misinterpret connections. Knowledge repositories can be incomplete. Certain perspectives can be overrepresented while others remain invisible. People may attribute more authority to a machine’s recommendations than is warranted.
Ethical design does not mean denying these risks.
It means consciously making them visible and developing structures that enable responsible handling of them.
At the same time, there is also a risk in inaction.
If valuable knowledge continues to remain scattered across websites, books, archives, personal computers, meeting notes, and the memories of individuals, experiences may be lost, and the same learning processes may need to be repeated.
We therefore ask not only: What risks arise from artificial intelligence? We also ask:
What opportunities and knowledge do we lose if we do not develop responsible ways to use this technology together?
At TEIKEI, Ethical Artificial Intelligence is not protected like a high-security facility but like a healthy ecosystem.
In a stable olive grove, there is no central defense. If the olive fly infests the olives, its natural predators arrive on their own because the pest is their food. The more diverse the grove, the more predators live there before the pest appears.
Translated to artificial intelligence, this means:
The image has a limit: an ecosystem does not know responsibility. An AI must therefore independently detect, halt, and report disturbances. Decisions remain with humans.
More on this image can be found under Decentralized Server Structure in the section "The Image of Security."
A further goal is to use artificial intelligence not only to process ever-larger amounts of information.
It can help create relationships from scattered knowledge.
Where knowledge is lost, remains separated, or disappears in an overwhelming amount of information, fragmentation occurs.
Where experiences are connected, made accessible, and brought into new relationships, something new can emerge.
In this sense, Ethical Artificial Intelligence can contribute to syntropic knowledge development:
not more and more information,
but more connection.
Not homogenization,
but linkage.
Not the replacement of human intelligence,
but the strengthening of shared learning capacity.
Ethical Artificial Intelligence should support people in:
Ethical Artificial Intelligence should strengthen human judgment—not replace it.
It is not artificial intelligence that determines what is good for life. People collectively shape the ethical foundations—and artificial intelligence helps them connect the knowledge gathered within them.
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By the TEIKEI editorial team, with support from AI (ChatGPT)
Created on June 10, 2026 · Last updated on October 15, 2026
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