While ontologies appear to be at the core of language models developments, and more generally of generative artificial intelligence (GAI), they are usually understood in terms of upgraded conceptual models, without further consideration for epistemic issues, the branch of philosophy studying the nature, sources, and edges of knowledge. The concept of ontological prism can provide some guidance.
A Knowledge-based Philosophical Wheel
Using the ontological prism as a fulcrum (and borrowing from the Stanford Encyclopedia of Philosophy), philosophical schools of thought can be summarily set along three main perspectives introduced par ancient Greek philosophers:
- Empiricism, for knowledge achieved through the experience of physical, social, and political percepts
- Idealism, for knowledge achieved through conscientious conceptual (aka mental) constructs
- Rationalism, for knowledge achieved through consistent agreed upon symbolic constructs
Philosophical traditions can be further refined through overlaps, e.g.:

- Phenomenology, for knowledge achieved through physical, social, and political percepts
- Relativism, for knowledge achieved by rooting reasoned constructs in ideas and opinions
- Positivism, for knowledge achieved through reasoned experience of physical, social, and political realities
Taking Kant’s works for example:
That wheel can then be turned into an AI philosophical compass.
An Artificial Intelligence Philosophical Compass
Generative artificial intelligence schemes can be broadly characterized by their use of networks and graphs to represent terms, words, categories, and meanings:
- Neural networks, for non symbolic representations of terms and labelled facts
- Semantic graphs, for documents and datasets
- Language models, for words and texts
- Models, for symbolic representations
- Conceptual networks, for domain-specific meanings
- Knowledge graphs for ontologies
- Semantic graphs for database schemas
AI schemes’ stepping stones could thus be used to identify the philosophical assumptions behind artificial intelligence schemes.
Further Readings
Kaleidoscope Series
- Signs & Symbols
- Generative & General Artificial Intelligence
- Thesauruses, Taxonomies, Ontologies
- EA Engineering interfaces
- Ontologies Use cases
- Complexity
- Cognitive Capabilities
- LLMs & the matter of transparency
- LLMs & the matter of regulations
- Learning
Other Caminao References
- About Scales & Times
- A Brief Ontology of Time
- Chatbots in the Galaxies of Meanings
- Caminao Framework Overview
- A Knowledge Engineering Framework
- Knowledge interoperability
- Edges of Knowledge
- The Pagoda Playbook
- ABC of EA: Agile, Brainy, Competitive
- Knowledge-driven Decision-making (1)
- Knowledge-driven Decision-making (2)
- Ontological Text Analysis: Example


