433 lines
7.3 KiB
Markdown
433 lines
7.3 KiB
Markdown
# Decision Canon v0.1
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## 1. Purpose
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The Decision Canon provides a coherent conceptual system for describing decisions, decision processes, and decision-governed ecosystems.
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It intentionally separates:
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1. **Decision situation** — why a decision exists.
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2. **Decision modelling** — how the relevant world is represented.
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3. **Decision analysis** — how alternatives are evaluated.
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4. **Decision taking** — how an authorized commitment occurs.
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5. **Decision execution** — what is done because of the commitment.
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6. **Decision observation** — what happens afterwards.
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7. **Decision learning** — what should change in beliefs, models, or rules.
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8. **Decision governance** — who may decide and under which constraints.
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9. **Decision evolution** — how policies and constitutional rules reshape future decisions.
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## 2. Unified lifecycle
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```text
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Situation
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↓
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Decision need
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↓
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Frame
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↓
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Alternatives / interventions
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↓
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Evaluation
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↓
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Commitment
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↓
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Effect / execution
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↓
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Observation
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↓
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Learning
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```
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For policy-bearing decisions:
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```text
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Decision
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↓
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Policy / Rule / Constraint / Delegation
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↓
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Changes future decision spaces
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↓
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Future decisions
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↓
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Observed ecosystem evolution
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↓
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Policy review
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↓
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Revised decision
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```
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## 3. Decision kinds
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Initial decision kinds:
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- `choice`
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- `bet`
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- `experiment`
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- `commitment`
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- `delegation`
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- `allocation`
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- `authorization`
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- `exception`
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- `policy`
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- `constitutional`
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These may overlap.
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### Choice
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Select among alternatives.
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### Bet
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Accept unresolved uncertainty for expected benefit.
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### Experiment
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Act primarily to acquire information.
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### Commitment
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Reduce future optionality.
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### Delegation
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Transfer or constrain decision authority.
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### Allocation
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Assign scarce resources.
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### Authorization
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Permit or prohibit an action.
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### Exception
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Override an existing rule within bounded scope.
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### Policy
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Create reusable rules that govern classes of future decisions.
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### Constitutional
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Change the rules by which authority, policy, or governance may themselves change.
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## 4. Decision state
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Suggested lifecycle:
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```text
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noticed
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→ framed
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→ open
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→ recommended
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→ committed
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→ effective
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→ observed
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→ reviewed
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→ closed
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```
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Side states:
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- `deferred`
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- `delegated`
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- `cancelled`
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- `expired`
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- `superseded`
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- `revoked`
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The key boundary is `committed`.
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Before commitment, the system is considering possibilities.
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After commitment, the system has adopted an intention.
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## 5. Decision formality levels
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### D0 — Ephemeral
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Unrecorded or transient choice.
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### D1 — Recorded
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Captures question, choice, and reason.
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### D2 — Structured
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Adds alternatives, owner, context, and constraints.
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### D3 — Analyzed
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Adds evidence, values, uncertainty, and explicit analysis.
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### D4 — Governed
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Adds authority, approvals, delegation, escalation, and auditability.
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### D5 — Executable
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Adds machine-readable rules, conditions, triggers, and actions.
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### D6 — Policy
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Creates reusable rules that constrain future decisions.
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### D7 — Constitutional
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Changes authority structures, policy-creation rules, or foundational ecosystem constraints.
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These are not maturity rankings in the sense that D7 is always better than D1.
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They indicate the degree and kind of formalization appropriate to the decision.
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## 6. Decision method families
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The canon should allow multiple methods rather than prescribe one.
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### Informal / human
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- intuition
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- expert judgment
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- heuristic
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- checklist
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- recognition-primed decision
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### Comparative
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- pairwise comparison
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- weighted scoring
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- MCDA / MAUT
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- AHP
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- outranking
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### Probabilistic
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- expected utility
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- Bayesian decision analysis
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- value of information
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- decision trees
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- influence diagrams
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### Optimization
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- linear programming
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- mixed-integer programming
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- constraint programming
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- stochastic optimization
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- robust optimization
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### Sequential / adaptive
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- dynamic programming
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- MDP
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- POMDP
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- optimal control
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- reinforcement learning
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### Causal
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- structural causal models
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- intervention analysis
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- counterfactual analysis
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### Strategic
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- game theory
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- bargaining
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- mechanism design
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- scenario analysis
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### Complexity-oriented
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- probing
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- real options
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- safe-to-fail experiments
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- robust decision making
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### Collective
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- vote
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- consent
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- consensus
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- deliberation
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- committee decision
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### Machine-assisted
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- rule engine
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- DMN
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- optimization service
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- recommendation model
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- AI-assisted synthesis
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- autonomous policy selection
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## 7. Decision authority
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Authority should be represented independently from capability.
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Canonical modalities:
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```text
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can technically capable
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may authorized
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should normatively preferred
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will committed
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did observed
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must mandatory
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```
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This permits distinctions such as:
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```yaml
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actor: autonomous-deployment-agent
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can: true
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may: false
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```
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or:
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```yaml
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actor: tenant-operator
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may: true
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scope: tenant
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```
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## 8. Decision criticality
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The canon should support a measure of required rigor.
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A conceptual function:
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```text
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RequiredRigor =
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Stakes
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× Irreversibility
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× Uncertainty
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× DurationOfEffect
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× ScopeOfImpact
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× AuthorityDepth
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```
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This is not yet intended as a literal equation.
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Its purpose is to formalize the principle that more consequential decisions deserve more explicit modelling.
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## 9. Policy effect primitives
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Initial policy primitives:
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- `permit`
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- `prohibit`
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- `require`
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- `constrain`
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- `default`
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- `prefer`
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- `incentivize`
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- `delegate`
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- `escalate`
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- `observe`
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- `review`
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- `expire`
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These primitives should be sufficient to express a large portion of operational governance.
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## 10. Decision relationships
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Canonical graph relationships:
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- `derived-from`
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- `implements`
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- `governed-by`
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- `delegated-by`
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- `authorized-by`
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- `triggered-by`
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- `depends-on`
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- `challenges`
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- `reviews`
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- `supersedes`
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- `revokes`
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- `exception-to`
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- `resulted-in`
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- `learned-from`
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## 11. Decision lineage
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Decision lineage is the ability to explain an observed action by traversing its decision and authority history:
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```text
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Observed action
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↑
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Execution
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↑
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Decision
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↑
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Delegated authority
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↑
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Policy
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↑
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Policy decision
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↑
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Constitutional decision
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```
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The inverse traversal should answer:
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> What downstream decisions and actions did this policy enable, prohibit, or shape?
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## 12. Decision quality
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Decision quality and outcome quality must remain distinct.
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### Ex ante
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Was the decision reasonable given:
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- frame,
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- evidence,
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- beliefs,
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- alternatives,
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- values,
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- uncertainty,
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- available analysis,
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- and authority?
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### Ex post
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What actually happened?
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The difference between expectation and outcome produces learning.
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## 13. Canonical deep structure
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A useful abstract representation is:
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```text
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D = (F, K, A, V, M, G, C, E, O, L)
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```
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where:
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- `F` — Frame
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- `K` — Knowledge
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- `A` — Alternatives
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- `V` — Values
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- `M` — Method
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- `G` — Governance
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- `C` — Commitment
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- `E` — Effect / Execution
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- `O` — Observation
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- `L` — Learning
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A lightweight decision may instantiate only:
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```text
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(F, A, C)
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```
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while a constitutional decision may instantiate the entire structure.
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## 14. Central invariant
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> A Decision Object records an authorized commitment made from a particular frame, knowledge state, and value system, together with its intended effects and sufficient lineage to observe and learn from what follows.
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