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HBT-INC-0166 · Dimension INC · Incentives

Job Redesign

Redesigning roles around AI capability.

Adoption·AI-Behavioral Coupling·Grade C·draft· enriching…
In one paragraph

Job Redesign is redesigning roles around AI capability. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0166, within the Adoption family. The core principle: redesigning roles around AI capability. 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

Redesigning roles around AI capability.

Plain-English Definition

Redesigning roles around AI capability.

Feynman Explanation

Bolting AI onto existing jobs leaves both half-broken.

Core Principle

Redesigning roles around AI capability.

Mechanisms

Psychological

Pending editorial review.

Behavioral Economic

Pending editorial review.

Neurological

Pending editorial review.

Evolutionary

Pending editorial review.

Sociological

Pending editorial review.

Computational

Pending editorial review.

Systems

Pending editorial review.

Inputs (Triggers)

Pending editorial review.

Outputs (Behaviors)

Pending editorial review.

Behavioral Signature

Bolting AI onto existing jobs leaves both half-broken.

Examples

Everyday
  • Customer service roles fundamentally redesigned around AI augmentation.
Modern (Organizational)
  • Where productivity gains actually materialize.
Historical

Pending editorial review.

Lab Commentary

Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.

Why this element matters to incentive design

Most organizations meet this element as a personnel problem. It is not one. 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: bolting AI onto existing jobs leaves both half-broken. 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, where productivity gains actually materialize. It is amplified whenever where productivity gains actually materialize. Inside organizations that shows up as where productivity gains actually materialize. 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 don't add AI to old jobs. Design new ones. The test of any redesign here is simple: after the change, can you name what the organization is now doing less of? If not, the payoff structure did not actually move.

Famous Experiments

Pending editorial review.

Design Principles

  • Don't add AI to old jobs. Design new ones.

Measurement Approaches

Pending editorial review.

Evidence

Evidence Grade
C (A strongest → E speculative)
Replication
★★☆☆☆
Intervention Confidence
3 / 5
Consensus
Pending editorial review (HBT v1.0 auto-seed).
Limitations
Pending editorial review (HBT v1.0 auto-seed).
Open Research Questions

Pending editorial review.

Primary References

Pending editorial review.

Signature Section

The Perverse Incentive Lens™

How this behavior is exploited — and how to redesign around it.

Exploitation
Where productivity gains actually materialize.
Amplifying Incentives
Where productivity gains actually materialize.
Org Failure Modes
Where productivity gains actually materialize.
Societal Failure Modes
Pending editorial review (HBT v1.0 auto-seed).
Ethical Considerations
Pending editorial review (HBT v1.0 auto-seed).
Redesign Strategies
Don't add AI to old jobs. Design new ones.
Diagnostic Questions
  • Don't add AI to old jobs. Design new ones.
Warning Signs

Pending editorial review.

Red Flags

Pending editorial review.

Intervention Playbook
Individual
Don't add AI to old jobs. Design new ones.
Team
Pending editorial review (HBT v1.0 auto-seed).
Organization
Pending editorial review (HBT v1.0 auto-seed).
Policy
Pending editorial review (HBT v1.0 auto-seed).
AI Implications
Detection
Pending editorial review (HBT v1.0 auto-seed).
Measurement
Pending editorial review (HBT v1.0 auto-seed).
Mitigation
Pending editorial review (HBT v1.0 auto-seed).
Responsible Use
Pending editorial review (HBT v1.0 auto-seed).

Interactive Mini Network

Click any neighbor to re-center the graph and follow the threads of connection.

HBT-INC-0166 · INC
Job Redesign
JRACAdoption Curve (AI)AAAlgorithmic AversionCACargo-Cult AdoptionPPPilot PurgatoryRMResistance MappingSASandbagging AdoptionSAShadow AISTStatus Threat (AI)AUAcceptable Use Polic…AgAgent

Knowledge Graph Neighbors

Where Job Redesign is cited in the corpus

Questions about Job Redesign

What is Job Redesign?
Job Redesign is redesigning roles around AI capability. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0166, within the Adoption family. The core principle: redesigning roles around AI capability. 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 Job Redesign?
Where productivity gains actually materialize. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-INC-0166).
How is Job Redesign exploited?
Where productivity gains actually materialize.
How do you design around Job Redesign?
Don't add AI to old jobs. Design new ones.
Which behavioral dimension does Job Redesign belong to?
Job Redesign is classified in the Incentives dimension (INC) of the Human Behavior Taxonomy™, family "Adoption", class "AI-Behavioral Coupling". Its permanent identifier is HBT-INC-0166 and its evidence grade is C.

Version History

v1.1.0 · 2026-06-28Initial auto-seed from corpus.