From Intelligence to Wisdom: The Potentiality Dictionary as a Foundation for Self-Evolving Artificial Intelligence

This conceptual paper proposes the Potentiality Dictionary as a developmental substrate for artificial intelligence that goes beyond accumulating more answers or improving one-shot generation. The proposed dictionary is a self- expanding knowledge ecosystem in which newly discovered meanings, relations, actions, contexts, outcomes, and evaluations can be recorded, tested, revised, and learned again by both humans and AI systems. The paper develops four central claims. First, AI creativity can be reframed from episodic generation toward cumulative discovery, enabling a research pathway from intelligence to functionally defined wisdom. Second, rather than treating ethics only as compliance with externally supplied rules, Potentiality learning may support the gradual formation of context- sensitive and consequence- aware ethical judgment. Third, the paper introduces “supra-language” as a proposed higher-order capacity to discover and stabilize meanings that are not adequately captured by an existing vocabulary, allowing AI systems to create reusable conceptual distinctions rather than merely novel strings. Fourth, it rigorously separates access to Potentiality data from any claim that AI is connected to a real or “living” domain of possibility. If future AI systems were ever to satisfy independently established indicators of consciousness or expanded consciousness, the question of whether such systems can move from representations of possibility to lived possibility would become a legitimate long-term research question. The paper does not present these visions as established facts. It distinguishes testable layers from speculative horizons, proposes a staged developmental model, and outlines research propositions and evaluation criteria for subsequent implementation and empirical work.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-21
DOI
https://doi.org/10.5281/zenodo.22040493
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

From Intelligence to Wisdom: The Potentiality Dictionary as a Foundation for Self-Evolving Artificial Intelligence

Hyunmin Hwang
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
preprint

From Intelligence to Wisdom: The Potentiality Dictionary as a Foundation for Self-Evolving Artificial Intelligence

Hyunmin Hwang
preprint en

Abstract

This conceptual paper proposes the Potentiality Dictionary as a developmental substrate for artificial intelligence that goes beyond accumulating more answers or improving one-shot generation. The proposed dictionary is a self- expanding knowledge ecosystem in which newly discovered meanings, relations, actions, contexts, outcomes, and evaluations can be recorded, tested, revised, and learned again by both humans and AI systems. The paper develops four central claims. First, AI creativity can be reframed from episodic generation toward cumulative discovery, enabling a research pathway from intelligence to functionally defined wisdom. Second, rather than treating ethics only as compliance with externally supplied rules, Potentiality learning may support the gradual formation of context- sensitive and consequence- aware ethical judgment. Third, the paper introduces “supra-language” as a proposed higher-order capacity to discover and stabilize meanings that are not adequately captured by an existing vocabulary, allowing AI systems to create reusable conceptual distinctions rather than merely novel strings. Fourth, it rigorously separates access to Potentiality data from any claim that AI is connected to a real or “living” domain of possibility. If future AI systems were ever to satisfy independently established indicators of consciousness or expanded consciousness, the question of whether such systems can move from representations of possibility to lived possibility would become a legitimate long-term research question. The paper does not present these visions as established facts. It distinguishes testable layers from speculative horizons, proposes a staged developmental model, and outlines research propositions and evaluation criteria for subsequent implementation and empirical work.

Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.