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→ effective → observed → reviewed → closed ``` Side states: - `deferred` - `delegated` - `cancelled` - `expired` - `superseded` - `revoked` The key boundary is `committed`.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