AI Bill of Materials Auditability is tracing AI components for risk and compliance. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0019, within the Governance family. The core principle: tracing AI components for risk and compliance. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
Scientific Definition
Tracing AI components for risk and compliance.
Plain-English Definition
Tracing AI components for risk and compliance.
Feynman Explanation
Provenance is the new audit trail.
Core Principle
Tracing AI components for risk and compliance.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
Provenance is the new audit trail.
Examples
- EU AI Act requirements.
- Compliance and supply chain risk.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
Executives usually notice this element only after it has cost something. By then it looks like a one-off. It is not. The mechanism underneath it operates in the Incentives dimension — what makes behavior more or less likely?. You can recognize it in the field by its signature: provenance is the new audit trail. Every element in the Incentives dimension changes the perceived payoff of an action before the action happens, which is exactly where incentive design has leverage.
How it gets exploited
Left undesigned, compliance and supply chain risk. It is amplified whenever compliance and supply chain risk. Inside organizations that shows up as compliance and supply chain risk. The pattern is the same one Goodhart's Law describes: the measurable proxy attracts the effort, and the purpose behind it quietly loses funding.
How the Lab designs around it
The redesign move is to maintain AI-BOM continuously. Audit periodically. Design against it the way you would design against a known failure mode — assume it will appear, and price the exploit before someone finds it.
Famous Experiments
Pending editorial review.
Design Principles
- Maintain AI-BOM continuously. Audit periodically.
Measurement Approaches
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Evidence
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The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Maintain AI-BOM continuously. Audit periodically.
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Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
Inventory of models, data, tools, and dependencies in an AI system.
Written rules about how AI may be used internally.
Logging of AI inputs, outputs, and decisions.
Cross-functional governance body for AI decisions.
Agents deployed before anyone owns the consequences.
Cryptographic tracking of content origin.
Tracking where training and inference data came from.
Comprehensive AI regulation in the EU.
Why did it produce this? vs. How does it work?
Human review at critical AI decision points.
Human oversight without per-decision review.
Documentation of model purpose, performance, limitations, and risks.
Where AI Bill of Materials Auditability is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- Field guideIncentives: definition, types, examples
The parent field guide for this element.
- ReferenceThe laws of incentives
Goodhart, Campbell, and the Cobra Effect.
- EssayAI Agents Inherit Your Incentives
How this element propagates into automated systems.
- EssayIncentives Under Crisis
How this element behaves under pressure.
- CourseIncentives 101
The free ten-part primer on reading a payoff structure.
- ReferenceThe Periodic Table of Human Behavior
The full 1,267-element map this page belongs to.
Questions about AI Bill of Materials Auditability
- What is AI Bill of Materials Auditability?
- AI Bill of Materials Auditability is tracing AI components for risk and compliance. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0019, within the Governance family. The core principle: tracing AI components for risk and compliance. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
- What is an example of AI Bill of Materials Auditability?
- Compliance and supply chain risk. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-INC-0019).
- How is AI Bill of Materials Auditability exploited?
- Compliance and supply chain risk.
- How do you design around AI Bill of Materials Auditability?
- Maintain AI-BOM continuously. Audit periodically.
- Which behavioral dimension does AI Bill of Materials Auditability belong to?
- AI Bill of Materials Auditability is classified in the Incentives dimension (INC) of the Human Behavior Taxonomy™, family "Governance", class "AI-Behavioral Coupling". Its permanent identifier is HBT-INC-0019 and its evidence grade is C.