Active
Institutions and Intelligence
How organizations learn and decide
How institutions learn, remember, decide, govern and transform.
Institutional architecture · Governance · Education institutions · Decision rights
Explore areaResearch & Evidence · knowledge library
Research Library
Browse research areas, questions, working groups, initiatives, working notes, frameworks, and evidence. Use Research & Evidence when you want a guided journey.
You are here in the ATRISI system
Library is organized by research areas and questions first. Working Groups appear as operational homes.
Library content will expand as more notes and frameworks are published. Browse here; act on /research.
Research areas
Public discovery groupings
Active
AI-Native Systems
How work changes when AI participates
How systems and workflows change when AI becomes a first-class participant in work.
Opportunity Discovery · AI-native systems practice · Human–AI collaboration · Enterprise workflows
Explore areaActive
Domain Intelligence
How methods apply in a specific field
How research methods apply inside a concrete domain — starting with imaging.
Imaging Intelligence · Healthcare workflows · Explainability evidence
Explore areaEmerging
Evidence, Capability and Trust
How capability claims become trustworthy
How capability, outcomes and decisions can be observed and trusted.
Capability claims · Verification · Public Impact · Evidence practice
Explore areaEmerging
Human Capability and Learning
How people build capability with AI
How people build, demonstrate and extend capability in AI-native environments.
Amplify · Resonance · Faculty development · Career transitions
Explore areaQuestions
Questions worth investigating
Institutions and IntelligenceActive
How should institutions evolve when AI becomes embedded in everyday work?
What durable pieces of institutional design — capability, evidence, decision rights, ownership — must be redesigned before AI tooling proliferates?
Understand this questionEvidence, Capability and TrustOpen
How should capability be observed and trusted?
How can institutions and employers observe capability claims with evidence that is portable, auditable, and resistant to theatre?
Understand this questionAI-Native SystemsOpen
How should humans and AI divide responsibility?
Where must humans retain judgment, accountability, and authorship when AI participates in work, learning, and decisions?
Understand this questionInstitutions and IntelligenceOpen
How can institutions learn from their own operations?
What memory and feedback lets an institution compound learning from everyday work rather than only from reports?
Understand this questionAI-Native SystemsActive
How should AI opportunities be discovered before systems are built?
How do organizations identify high-leverage problems worth solving with AI without jumping to tools or vendors first?
Understand this questionDomain IntelligenceActive
How can medical imaging intelligence be developed and validated responsibly?
How should imaging AI systems be designed and evidenced without claiming clinical diagnostic authority they do not hold?
Understand this questionInstitutions and IntelligenceOpen
Should assessment be a core design piece or an evidence byproduct?
Does assessment belong in institutional architecture as its own building block, or primarily as evidence produced by capability and practice?
Understand this questionInstitutions and IntelligenceOpen
Can an AI-native university exist without departments?
If capability, evidence, and decision design become primary, what institutional role do departments still play?
Understand this questionHuman Capability and LearningOpen
Should capability replace curriculum as the primary organizing object?
Should curriculum remain primary, or should learner and faculty capability become primary with curriculum as pathway structure?
Understand this questionHuman Capability and LearningOpen
How should builders demonstrate capability beyond certificates?
What evidence should prove that a person can build with AI — beyond attendance, badges, or self-report?
Understand this questionInstitutions and IntelligenceSynthesizing
What must an institution own when AI is in the stack?
Which capabilities must remain institution-owned for trust and exit readiness — and which can be platform-enabled?
Understand this questionDomain IntelligenceOpen
Which imaging evidence patterns transfer beyond a single site?
Which explainability and workflow evidence patterns generalize across institutions without claiming diagnostic authority?
Understand this questionWorking groups
Operational units
Forming · open invitationWorking Group WG001
Institutional Architecture for Education
Flagship working group for universities and academic systems that need an architecture for intelligence transformation, not isolated AI tools. Forming in public with an open research agenda.
Open Institutional Architecture for EducationActiveWorking Group WG002
Imaging Intelligence
Active applied research working group producing prototypes, working notes, and pilot evidence around imaging knowledge platforms.
Open Imaging IntelligenceResearch roadmap
Agenda by year
2026 · active
Institutions · Systems · Domain Intelligence
Active work across institutional architecture, AI-native systems practice, evidence and trust, and imaging intelligence — education is one application, not the boundary.
2027 · planned
Capability · Faculty · Evidence Models
Expand human capability, faculty intelligence, and evidence models as distinct research questions across areas.
2028 · horizon
Autonomous Institutions · Policy · Digital Twins
Longer-horizon questions on autonomous institutions, policy intelligence, and institutional digital twins — opened when earlier primitives stabilize.
Operating loop
01
Question
A durable research question worth co-solving.
02
Area
Public research area that situates the question.
03
Working Group
Operational unit that owns investigation and artifacts.
04
Research
Experiments, notes, and critique — not doctrine by default.
05
Evidence
What implementation and review actually show.
06
Framework
Reusable models distilled from evidence.
07
Adoption
Institutions and systems change practice.
08
More Evidence
Adoption feeds the next research cycle.
Artifacts
Working notes & frameworks
WG001-WN001
WG001-WN001 — Why Institutional Architecture Matters
Opening working note for the Institutional Architecture Working Group: architecture is the missing layer between AI ambition and institutional compounding.
WG001-WN002
WG001-WN002 — Canonical Primitives of an AI-Native Educational Institution
Review draft of institutional primitives — contributors submit examples, objections, missing concepts, and constraints.
Framework
Institutional Intelligence Framework
ATRISI framework for converting fragmented institutional activity into reusable intelligence across workflows, governance, research, and platforms.
Framework
AI Readiness Framework for Higher Education
A readiness model for universities evaluating AI adoption across faculty capability, assessment, governance, research, and institutional systems.
Framework
Research OS Framework
A research operating system model for AI-native knowledge continuity, artifact tracking, evidence synthesis, and reusable research workflows.
Catalogued questions: 12 · Areas: Institutions and Intelligence (5) · AI-Native Systems (2) · Domain Intelligence (2) · Evidence, Capability and Trust (1) · Human Capability and Learning (2)