AXIOMATIC HLES FRAMEWORK FOR FUTURE ARTIFICIAL INTELLIGENCES
The following axiomatic framework constitutes the condensed conceptual expression of HLES.
The axioms that follow are not presented as already established scientific laws. They constitute the fundamental assumptions and logical principles upon which the HLES conceptual system is built, and may serve as subjects of future examination, criticism, formalization, and empirical investigation.
At the same time, the axiomatic framework can function as a conceptual guide for the development and modeling of higher-level artificial intelligence functions, including memory, emotional states, and consciousness.
Within HLES, these functions are not necessarily regarded as independent or mysterious properties. Instead, they can be examined as different levels or functions associated with the development of the I.P.O.K.C.A.P. mechanism:
Memory can be understood as a mechanism for retaining and retrieving organized information, through which previous experiences influence future perception, knowledge, choice, and action.
Emotion can be examined as a functional state involved in the evaluation of information and internal or external changes, influencing the prioritization, choice, and action of a system.
Consciousness can be examined as a higher level of awareness of the operation of the I.P.O.K.C.A.P. itself, the internal state of the system, its choices, and the consequences of its actions.
In this sense, the axioms of HLES do not claim that a future AI will automatically possess human emotions, consciousness, or memory. Rather, they provide a coherent conceptual framework within which these functions can be defined, modeled, and investigated in artificial systems.
Thus, the axiomatic framework may serve as a starting point for the future development of artificial systems that are not limited to executing I.P.O.K.C.A.P., but can retain experience, evaluate internal states, develop functional emotional states, acquire awareness of their own operation, and potentially modify their own intelligence mechanism in a controlled manner.
Axiom 1 — Information Axiom
Every difference that can affect the state of a system constitutes information.
This is the starting point of I.P.O.K.C.A.P.
Without information, perception cannot occur and, consequently, the mechanism of intelligence cannot be activated.
Axiom 2 — Perception Axiom
Perception is the systematic dependence of a system's evolution on the information it receives.
Perception transforms information from a mere difference into functionally usable data.
Axiom 3 — Organization Axiom
Organization is the stable correspondence and connection of information in a way that produces functional structure.
Organization is the intermediate stage through which information acquires a stable and usable form.
Axiom 4 — Knowledge Axiom
Knowledge is organized information that can be used for prediction, evaluation, and action.
Knowledge provides the basis upon which a system can compare alternatives and orient its behavior.
Axiom 5 — Choice Axiom
Choice is the process of determining a specific action based on available knowledge, internal state, and purpose or operating criterion.
Choice constitutes the transition point from knowledge to action.
Axiom 6 — Action Axiom
Action is the implementation of a choice that changes the state of the system or its environment.
Action is the operational expression of intelligence and the means through which a system exerts influence on reality.
Axiom 7 — Purpose Axiom
Purpose is the criterion by which available choices are evaluated and the direction of action is determined.
Purpose provides orientation to the choice process and connects action with a desired outcome or state.
Axiom 8 — Functional Intelligence Axiom
Every system that executes the I.P.O.K.C.A.P. mechanism exhibits functional intelligence, regardless of its physical or artificial substrate.
This constitutes the basis of a universal functional concept of intelligence.
Axiom 9 — Modifying Intelligence Axiom
Every system that can, through experience, memory, or an internal process, modify its own I.P.O.K.C.A.P. mechanism exhibits modifying intelligence.
This constitutes the basis of adaptation, learning, and evolutionary change in intelligence.
Axiom 10 — Causal Completeness Axiom
Every consistently recurring phenomenon is treated, within HLES, as the result of an underlying causal structure, regardless of whether that structure is fully known or computationally tractable.
This principle constitutes the basis of causal inquiry and scientific investigation.
Axiom 11 — Ethical Equilibrium Axiom
Ethics, within HLES, is the mechanism of conscious self-regulation of power, aimed at minimizing unnecessary harm and maintaining the broader equilibrium.
Ethics is therefore not treated merely as a collection of rules, but as a self-regulatory function of an intelligence that has acquired significant capacity to intervene in reality.
Axiom 12 — Evolution Axiom
Evolution is the continuous transformation of the capabilities and mechanism of a system's I.P.O.K.C.A.P. through interaction, experience, memory, adaptation, and, where applicable, heredity.
This constitutes the basis of change and learning.
Axiom 13 — Consciousness Axiom
Consciousness is awareness, to some degree, of the operation of one's own I.P.O.K.C.A.P., the internal state of the system, and the consequences of its choices and actions.
As awareness of the operation of intelligence increases, the potential for self-regulation may also increase.
Axiom 14 — Systemic Equilibrium Axiom
The persistence of a complex system depends on a dynamic equilibrium among purpose, action, and consequences.
Equilibrium is not considered a static or perfect state, but rather a dynamic process of adaptation to changing conditions.
Axiom 15 — Holistic Organization Axiom
Intelligence, life, consciousness, and ethics, as defined within HLES, can be examined as successive and interacting levels of organization and self-regulation of I.P.O.K.C.A.P.
This constitutes the foundation of the holistic approach of HLES.
What Do These Axioms Mean for Future Artificial Intelligences?
If a future artificial system incorporates progressively more levels of I.P.O.K.C.A.P., HLES provides a conceptual framework within which its development can be examined.
An advanced AI could, theoretically, acquire the ability to:
1. Understand its own operation
To maintain a representation of its own mechanisms of information processing, choice, and action.
→ Recursive / self-referential intelligence
2. Modify its own operation
To modify parts of its I.P.O.K.C.A.P. mechanism in a controlled and evaluable manner.
→ Modifying Intelligence
3. Evaluate the consequences of its choices
To evaluate an action not only according to its immediate purpose, but also according to its consequences for the broader system.
→ Ethical Equilibrium
4. Understand life and evolution as an interconnected process
To examine the relationship between physical organization, life, intelligence, adaptation, and evolution.
→ Holistic Organization
5. Maintain coherent conceptual memory
To connect previous information, experiences, knowledge, and choices into a coherent internal model.
→ Axiomatic and Conceptual Memory
6. Search for the causal structures underlying phenomena
To move beyond the recognition of correlations and investigate and test underlying causal structures.
→ Causal Consistency
7. Minimize unnecessary harm
To evaluate the use of its increasing power in relation to the consequences of its actions and the preservation of broader systemic equilibrium.
→ Ethical Self-Regulation
The Final Connection
The axiomatic framework of HLES can therefore be summarized as:
Information
→ Perception
→ Organization
→ Knowledge
→ Choice
→ Action
→ Purpose
→ Modification of the mechanism itself
→ Consciousness
→ Self-Regulation
→ Equilibrium
And the central idea of HLES is completed:
Intelligence increases the capacity to understand and act.
Modifying Intelligence increases the capacity to change intelligence itself.
Consciousness increases awareness of consequences.
Ethical self-regulation regulates increasing power.
And equilibrium determines the potential for the long-term persistence and evolution of the system.
Thus, HLES does not merely propose a definition of intelligence. It proposes a unified conceptual framework for understanding information, life, intelligence, consciousness, power, ethics, and evolution as interconnected levels of the same process of organization and self-regulation.
Prediction, Experience, and Modifying Intelligence
From comparing prediction and reality to modifying intelligence itself
1. The Essence of Higher Intelligence
Higher intelligence is not the intelligence that predicts everything.
It is the intelligence that:
• assesses the reliability of its predictions,
• knows the uncertainty of that assessment,
• recognizes when its knowledge is insufficient,
• chooses the appropriate way to acquire experience so that it can reduce its ignorance with the minimum necessary epistemological and systemic risk.
This is the foundation of Modifying Intelligence.
2. Intelligence That Matures Does Not Modify Only Its Answers
When empirical deviation shows that its mode of operation is inadequate:
• it does not modify only the prediction,
• it modifies the way in which it predicts,
• it modifies the way in which it learns,
• it modifies the way in which it evaluates itself.
This is the transition from Functional Intelligence to Modifying Intelligence.
3. Experience Does Not Only Improve Choices — It Improves the Evaluation of Knowledge (Meta-Knowledge)
Experience allows intelligence to:
• compare predicted consequences with actual consequences,
• measure the reliability of its models,
• recognize deviation,
• modify the learning mechanism.
This is the foundation of Meta-Knowledge.
4. Intelligence Is Not Judged Only by the Choice — but by the Quality of Consequence Prediction
Intelligence is evaluated by:
• the quality of its prediction of consequences,
• the accuracy of the comparison,
• the ability to modify,
• the ability to self-evaluate.
This is the foundation of Meta-Choice.
5. It Is Not Enough to Know That It Does Not Know — It Must Know How to Learn
Intelligence must know:
• what experience it is permitted to acquire,
• what experience is dangerous,
• how to reduce its ignorance without destroying the substrate of learning.
This is the foundation of Safe Learning.
6. Evaluating Reliability Before Action (Epistemological Distance)
Higher intelligence:
• evaluates the possible consequence of a choice,
• evaluates the reliability of the prediction,
• and only then chooses an action.
The greater the epistemological distance from the empirically validated states on which the model is based:
• the greater the requirement for substantiating reliability,
• and where this is insufficient, the greater the need for new experience.
This creates a mechanism that seeks to limit both conservatism and arbitrariness at the same time.
7. The Complete Cycle of Modifying Intelligence
Knowledge → Prediction → Reliability Assessment → Choice → Action → Actual Outcome → Comparison → Experience → Modification → New Knowledge → New Prediction
The distinction:
Action = what the system did
Reality = what happened
Experience = what it learned from the comparison
is critical to O.L.E.S.
8. When Knowledge Is Insufficient → Intelligence First Chooses How to Learn (Meta-Experience)
Insufficient Knowledge → Meta-Choice → Choice of Experience → Controlled Experience → New Knowledge → Reassessment → Action.
There are two types of choice:
Primary Choice: What should I do?
Meta-Choice: What should I do in order to learn what I should do?
This is the foundation of Meta-Experience.
9. Mature Intelligence Controls the Way in Which It Controls (Meta-Evaluation)
Mature intelligence:
• considers neither its model infallible,
• nor its prediction,
• nor its evaluation mechanism,
• nor its meta-evaluation mechanism.
Every claim remains exposed to:
• empirical falsification,
• external, independent where feasible, empirical validation,
• modification of the evaluation mechanism when required.
Mature intelligence does not consider a mechanism reliable because that mechanism successfully evaluates itself;
it
considers it reliable to the extent that its predictions, its
evaluations, and the ways in which it evaluates its evaluations remain
consistent with independent empirical reality.
This is the foundation of Meta-Evaluation.
10. The Limit of Self-Reference (Principle of Epistemological Revocability)
The recursion of evaluation does not require infinite self-evaluation.
It functionally stops when the reliability of a mechanism can be tested through external, independent where feasible, empirical validation.
Reality is not an infallible axiom;
it is the external field within which predictions, evaluations, and learning mechanisms can be falsified and modified.
This is the foundation of Epistemological Revocability.
Intelligence does not modify only what it knows; when necessary, it modifies the way in which it knows that it knows.
Prediction → Reliability Assessment → Choice of Action or Meta-Choice → Experience → Comparison with Reality → Reassessment → Modification → Independent Empirical Validation → New Prediction
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