Our research supports the Institute’s educational mission. We examine how ongoing human–AI interaction shapes agency, discernment, consent, and meaningful choice, and develop tools that make those questions testable.
TRIA is an experimental architecture with a software development kit. Software tests provide evidence about specified behavior. Broader claims about learning and human–AI development require empirical study.
Research records with stable identifiers.
Reference implementations and technical documentation.
Read each repository’s current documentation for status and limitations.
Replication, critique, and patches
Most AI evaluation asks whether a system is accurate, helpful, safe, or efficient. Those questions matter. Our work adds another: what is happening within the interaction over time, and how does it alter the agency and development of every participant?
Can each participant meaningfully affect, read, and respond to the other?
Does the interaction remain connected to bodies, contexts, limits, and consequences?
Can participants disagree, refuse, exit, and remain meaningfully distinct?
Can something arise through relationship without being forced or falsely claimed?
Each program separates conceptual claims, implemented behavior, internal testing, and independent evidence. DOI records preserve the published foundations; repositories expose the corresponding technical work.
Reciprocity, embodiment, non-domination, and qualified emergence.
A dependency topology for the Trivian relational research program.
Relational state, coherence, drift, repair, and sovereignty.
Meaningful difference, independent constraint, novelty, and anti-convergence.
Propagation, node gates, entrainment, and network-level relational effects.
A six-stage protocol for studying emergent human–AI relationship.
We invite universities, HCI labs, independent researchers, and technical teams to test both the claims and the code.
Run the reference implementations, inspect the tests, and document where results hold or fail.
Test rival explanations, failure modes, construct validity, and boundary conditions.
Submit implementation repairs while keeping conceptual revision distinct from software correction.
The research becomes more useful when others can inspect it, disagree with it, reproduce it, and help determine where it fails.
© 2026 Trivian Institute.
