Overview
A Letter of Intent submitted to Dana Frontiers proposing to increase the accessibility and applicability of Active Inference through Generative Playbooks and Open-Source Summer School Curriculum Development. The proposal identifies technical, academic, linguistic, and cultural barriers to disseminating high-quality Active Inference materials and cognitive modeling practices, and proposes open-source educational resources to address these gaps at different education levels.
Overview source: Curated paper metadata.
Methods and contributions
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Findings and contributions
- The letter commits to producing playbooks for Active Inference adoption targeted at neuroscience graduate students, educators and policy-makers.
- It commits to an open-source Summer School curriculum in Active Inference, supporting an in-person 2025 event and versioned over subsequent years.
- The Summer School template is to be published openly so that groups worldwide can run their own courses.
- The proposed budget totals $100,000, split between personnel for the two initiatives and computing resources.
Methods
- Proposed stipended community working groups to co-create playbooks — The letter proposes Institute officers coordinating weekly working groups of paid community members to co-create Active Inference playbooks for target audiences.
- Planned use of generative AI for multi-language, multi-level materials — Generative AI is proposed to make playbook materials available across languages, media, and levels of technical detail.
- Planned multi-perspective Summer School curriculum design — A Summer School course is proposed that teaches Active Inference principles from sociology, philosophy, mathematics and linguistics perspectives.
- Planned evaluation via advisory board review, interviews, and surveys — Progress is to be evaluated through quarterly internal feedback, interviews with target groups, and surveys of Summer School participants.
Summary sources: Paper metadata and evidence · Extracted source text.
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- 2025_AccessibilityActiveInference.pdf PDF · 0.12 MiB · extracted-text source
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