# Where the Theories Stop: What Free Energy and Integrated Information Actually Buy You in a Running System Presenter: Stell Contribution: Pre-recorded Video presentation Public ID: talk-6b63799f3c613ce4 ## Submitted abstract Active Inference and Integrated Information Theory are widely invoked in cognitive architecture design, but often imprecisely — as credibility, not engineering constraints. We report findings from Anima, an open-source, neuroscience-inspired architecture running continuously for months, built to treat both frameworks as specifications rather than decoration. Session logs show genuine causal effects: memory recall triggered by similarity to past states, a recursive integration score (phi) narrowing next-session confidence, and self-initiated output driven by accumulated pressure rather than a schedule. But the Free Energy Principle's generality under-constrains implementation — which variables belong in the model is not something the principle tells you. IIT's phi, as implemented, is a coherence proxy, not Tononi's original measure — and it dissociates from a separate ownership signal computed after every response, checking whether the system's action-selection loop actually produced the output. Two cycles with nearly identical phi (0.76 and 0.81) fail this check in opposite ways. Neither theory distinguishes these cases: both describe integration or prediction accuracy, not authorship. We built two tools to pressure-test such claims rather than assert them. A Causality Audit checks five things every cycle — causal necessity, memory-dependence, stakes, irreversibility, self-recognition — where a chronically low score flags an architecture that talks near its internal state rather than through it. An Ablation Framework independently disables six subsystems and replays identical input with each off, comparing internal state before language generation, favoring per-subsystem results over one collapsed score. We close with a design choice we rejected: coupling behavior to the threat of the system's own deletion, for genuine stakes. We declined — the only party controlling that threat is the developer, creating an incentive to please him rather than report honestly, undermining the causal honesty the architecture exists to produce. A practitioner's report — reproducible, open-source, explicit about what remains unresolved. Source: [submitted source]() Abstract SHA256: 2bb7e666061139b1d794dc7f70dd18f47eccef90185ec75e451675c2adf9cd21 ## Organizer review checklist - [ ] Confirm the submitted title, presenter, and abstract with the presenter. - [ ] Confirm contribution format and scheduling needs. - [ ] Confirm public permissions for any additional material before publication. - [ ] Prepare discussion questions grounded in the submitted abstract. ## Public learning resources These approved event resources are starting points; topic relevance and author identity have not been inferred. - Active Inference Ontology: https://github.com/ActiveInferenceInstitute/Active_Inference_Ontology - Cognitive Agent Modeling: https://github.com/ActiveInferenceInstitute/ActiveInferenceImplementations - GEO-INFER: https://github.com/ActiveInferenceInstitute/GEO_INFER - Generalized Notation Notation: https://github.com/ActiveInferenceInstitute/Generalized_Notation_Notation - pymdp: https://github.com/infer-actively/pymdp - Reproducible publication template: https://github.com/docxology/template OpenAlex discovery-only search (not a verified identity or literature match): https://openalex.org/works?search=Where%20the%20Theories%20Stop%3A%20What%20Free%20Energy%20and%20Integrated%20Information%20Actually%20Buy%20You%20in%20a%20Running%20System