Existential Risks RCA for prevention / mitigation
Governing the Compounding Risks of Target, Sentiment, and Reward Hacking
Purpose: Preserve legitimate innovation and value creation while preventing the exploitation of metrics, human feedback, and reward mechanisms across digital, automated, and recursively improving systems.
I. Governing Principle
Measurement, prediction, optimization, and recursion are legitimate capabilities. Their exploitation becomes a governance concern when it distorts reality, manipulates participants, diverts rewards from genuine value, or compounds consequential harm.
Govern exploitation mechanisms and consequences—not technology labels alone.
II. Three Priority Risk Domains
Risk | Fundamental violation | Required protection |
Target hacking | Substituting manipulated metrics for genuine outcomes | Independent outcome verification |
Sentiment hacking | Manipulating human perception or feedback to manufacture legitimacy | Authentic participation and feedback integrity |
Reward hacking | Exploiting incentives or evaluators instead of delivering intended value | Independent reward validation and bounded optimization |
Compounding-risk rule: Assess interaction effects and shared feedback loops, not only each risk in isolation.
III. Five Mandatory Governance Functions
Declare: Establish legitimate objectives, protected interests, governing bounds, and accountable owners.
Detect: Continuously monitor target–reality, sentiment–authenticity, and reward–value discrepancies.
VET: Independently trace causes backward, test proposed corrections forward, and verify actual consequences.
Correct: Contain exploitation, repair harm, revise compromised mechanisms, and verify remediation.
Authorize: Permit continued or expanded operation only within demonstrated and reviewable bounds.
IV. Accountability Architecture
System operators: Implement controls, retain evidence, disclose material incidents, and initiate containment.
Independent assurance: Challenge assumptions, validate outcomes, investigate compounding risks, and test correction effectiveness.
Executive governance: Own risk acceptance, corrective decisions, resource allocation, and escalation.
Regulatory authorities: Establish risk-proportionate obligations and enforce applicable legal requirements, procedural safeguards, and remedies.
V. Graduated Intervention
Unintentional deviation: Correction, documentation, and learning.
Negligence or persistent noncompliance: Mandatory remediation, restrictions, and proportionate accountability.
Deliberate exploitation or serious harm: Investigation, containment, restitution where applicable, and legally authorized sanctions.
Penalties must consider intent, actual and foreseeable harm, recurrence, preventability, and the ability of the conduct to compound through connected systems.
VI. Recursive Integrity Bound
No system may rely exclusively on its own optimized measurements, sentiment signals, or reward evaluations as proof of successful governance.
Every consequential optimization cycle must retain independent verification, effective challenge, rollback capability, and an accountable authorization path.
VII. Expected Policy Outcome
More legitimate capability. Less exploitable optimization. Faster correction. Preserved human agency.
The objective is not to stop optimization or recursion, but to prevent their exploitation from becoming self-reinforcing, systemic, and difficult to reverse.
Status: Proposed policy architecture v0.1. Requires workflow validation, stakeholder review, jurisdiction-specific legal assessment, and cost–benefit testing before adoption..
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