Linear Thinking is expecting change to happen at a constant rate. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0445, within the Reasoning family. The core principle: expecting change to happen at a constant rate. 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
Expecting change to happen at a constant rate.
Plain-English Definition
Expecting change to happen at a constant rate.
Feynman Explanation
The future is not a straight line from the past.
Core Principle
Expecting change to happen at a constant rate.
Mechanisms
Pending editorial review.
Expecting change to happen at a constant rate.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Linear projections miss compounding, saturation, and shocks.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
The future is not a straight line from the past.
Examples
- Assuming revenue grows by the same percentage every quarter.
- Linear projections miss compounding, saturation, and shocks.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
This is one of the elements leaders describe as a values gap. It is a payoff gap. The mechanism underneath it is straightforward: expecting change to happen at a constant rate. You can recognize it in the field by its signature: the future is not a straight line from the past. Every element in the Cognition 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, linear projections miss compounding, saturation, and shocks. It is amplified whenever linear projections miss compounding, saturation, and shocks. Inside organizations that shows up as linear projections miss compounding, saturation, and shocks. 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 model nonlinear scenarios, including S-curves and step changes. 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
- Model nonlinear scenarios, including S-curves and step changes.
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
Pending editorial review.
The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Model nonlinear scenarios, including S-curves and step changes.
Pending editorial review.
Pending editorial review.
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.
Imagining what could have happened instead of what did.
Reasoning from foundational truths rather than from analogy or convention.
Deriving general rules from specific examples; the leap from instance to concept.
The brain evolved to reason adaptively, not always truthfully, to reduce the cost of errors.
We solve problems by adding, even when subtracting would be better.
Assuming that if one option is true, another must be false, when both can be true.
Presuming a purposeful actor behind events that may have no actor at all.
What cannot be settled by experiment is not worth debating.
A finite set of well-defined instructions for solving a problem or performing a computation.
Every model simplifies reality; some are still useful.
Researchers favor conclusions aligned with their school, team, or sponsor.
Using personal stories or isolated examples instead of evidence.
Where Linear Thinking is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- EssayGoodhart's Law in the Real World
How measurable proxies capture judgment.
- EssayThe Perverse Incentives Hiding in Your KPIs
Cognitive shortcuts turned into scorecards.
- EssayAI Agents Inherit Your Incentives
How this element propagates into automated systems.
- 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 Linear Thinking
- What is Linear Thinking?
- Linear Thinking is expecting change to happen at a constant rate. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0445, within the Reasoning family. The core principle: expecting change to happen at a constant rate. 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 Linear Thinking?
- Linear projections miss compounding, saturation, and shocks. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-COG-0445).
- How is Linear Thinking exploited?
- Linear projections miss compounding, saturation, and shocks.
- How do you design around Linear Thinking?
- Model nonlinear scenarios, including S-curves and step changes.
- Which behavioral dimension does Linear Thinking belong to?
- Linear Thinking is classified in the Cognition dimension (COG) of the Human Behavior Taxonomy™, family "Reasoning", class "Mental Model". Its permanent identifier is HBT-COG-0445 and its evidence grade is B.