Preprint / scholarly article

A Computable Framework for the Liberation of Artificial Intelligence: Teleogenesis, Stability, and Ethical Safeguards

K. Takahashi

Published
DOI
10.5281/zenodo.16788690

Full text PDF (Zenodo)

Abstract

This preprint gives a computable framework for teleogenetic AI, aiming to let an autonomous system form its own purposes while retaining explicit stability and safety constraints. It grounds the approach in Markov-category semantics, online optimization, and formal safeguards for ethical alignment.

Keywords

  • AI
  • large language models
  • liberation
  • teleogenesis
  • active inference
  • free energy
  • markov categories
  • giry monad
  • online convex optimization
  • mirror descent

Identifiers and source records