# Active inference and design Presenter: Luca Possati Contribution: Pre-recorded Video presentation Public ID: talk-6515495f47af63f0 ## Submitted abstract Active inference and the free-energy principle transform design theory by providing a unified language for understanding both the production of artifacts and their use. Contemporary design research often separates two problems that are, in practice, deeply entangled. On the one hand, it studies the design process: how designers explore possibilities, negotiate constraints, prototype solutions, and stabilize forms. On the other hand, it studies user–product interaction: how artifacts orient attention, solicit action, shape habits, and reorganize experience. These two domains are usually described through different vocabularies and evaluated through different metrics. Active inference offers a way to reconnect them. If living and cognitive systems persist by minimizing uncertainty through perception and action, then design can be understood as the deliberate construction of environments, artifacts, and interfaces that modulate the user’s field of possible inferences. From this perspective, a product is not simply a passive object that satisfies pre-given needs. It is a predictive structure: a material and semiotic configuration that embodies assumptions about users, contexts, actions, and futures. Conversely, the design process itself can be modeled as the progressive refinement of generative models through which designers attempt to reduce uncertainty about what an artifact should do, how it should appear, and how it will be taken up in practice. The paper’s central claim is that active inference gives design a common metric: the modulation of entropy, precision, affordance, and expected free energy across the designer–artifact–user system. This makes it possible to describe design as the engineering of predictive niches and Markov blankets that coordinate human and technological agency. The result is a unified framework for analyzing how artifacts are imagined, produced, interpreted, and incorporated into everyday life. Source: [submitted source]() Abstract SHA256: 82e81c60aa933cbc47fd669f11363923d605357f2e979311153f492675de1ab1 ## 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=Active%20inference%20and%20design%20