This is the research spine behind the course: governing AI well begins with a clearer model of intelligence, meaning, and trust.
The architecture of intelligence is the recurring structure beneath perception, prediction, meaning, decision, and action. Steve Kirton's work connects a decade of Trinosophia research with contemporary cognitive science, systems-thinking psychology, predictive-processing neuroscience, and the practical craft of improving AI-assisted work.
Central claim
Trustworthy AI-assisted work and innate human intelligence are not separate subjects. Both depend on structures that turn ambiguity into actionable models, then expose enough of that structure for others to test, correct, and rely on.
Essay structure
- The historical context: Manly P. Hall and Trinosophia as an intellectual influence, not an authority claim.
- The modern synthesis: cognitive science, systems-thinking psychology, predictive processing, and philosophy of mind.
- The architecture: a structured model of how intelligence converts signal into meaning and decision.
- The systems bridge: why verifiability matters when AI tools, blockchains, and human trust collide.
- The objections: where the model could fail, overreach, or need better evidence.
FAQ
What is the architecture of intelligence?
It is Steve Kirton's term for the structured relationship between perception, prediction, meaning, decision, and action in humans and AI-assisted work.
How does this connect to verifiable systems?
The connection is trust. Human intelligence depends on coherent internal models; better AI-assisted work depends on claims that can be inspected, tested, and improved.