Constructed Preferences is preferences aren't retrieved from a stable internal list — they're built on the spot from cues, context, and the elicitation method. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0181, within the Decision family. The core principle: preferences aren't retrieved from a stable internal list — they're built on the spot from cues, context, and the elicitation method. 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
Preferences aren't retrieved from a stable internal list — they're built on the spot from cues, context, and the elicitation method.
Plain-English Definition
Preferences aren't retrieved from a stable internal list — they're built on the spot from cues, context, and the elicitation method.
Feynman Explanation
Ask the same person the same question two different ways; meet two different people.
Core Principle
Preferences aren't retrieved from a stable internal list — they're built on the spot from cues, context, and the elicitation method.
Mechanisms
Pending editorial review.
Preferences aren't retrieved from a stable internal list — they're built on the spot from cues, context, and the elicitation method.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Pending editorial review.
Pricing pages, survey design, and any place a user 'tells you' what they want.
Inputs (Triggers)
Pending editorial review.
Outputs (Behaviors)
Pending editorial review.
Behavioral Signature
Ask the same person the same question two different ways; meet two different people.
Examples
- Slovic, Payne, Bettman: framing, ordering, and elicitation format change the 'true' preference.
- Pricing pages, survey design, and any place a user 'tells you' what they want.
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 element is common enough to feel like human nature and specific enough to be engineered around. The mechanism underneath it is straightforward: preferences aren't retrieved from a stable internal list — they're built on the spot from cues, context, and the elicitation method. You can recognize it in the field by its signature: ask the same person the same question two different ways; meet two different people. 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, pricing pages, survey design, and any place a user 'tells you' what they want. It is amplified whenever pricing pages, survey design, and any place a user 'tells you' what they want. Inside organizations that shows up as pricing pages, survey design, and any place a user 'tells you' what they want. 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 test multiple framings. The first one isn't truth — it's the one you happened to try. Measure the behavior, not the sentiment. A survey will tell you how people feel about this; only observed action tells you whether it changed.
Famous Experiments
Pending editorial review.
Design Principles
- Test multiple framings. The first one isn't truth — it's the one you happened to try.
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.
- Test multiple framings. The first one isn't truth — it's the one you happened to try.
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.
How will I feel about this in 10 minutes / 10 months / 10 years?
Inattention or forgetfulness caused by low attention, hyperfocus, or distraction.
Forgetting to compare an offer with the next-best alternative.
Outcomes that could have happened but did not.
Overthinking a situation so that decision-making stalls.
The first number on the table silently sets the range for every number after it.
Tversky & Kahneman's classic: identical outcomes flip from 'risk averse' to 'risk seeking' when framed as lives saved vs. lives lost.
Our perception is shaped by what we selectively pay attention to.
Favoring suggestions from automated systems over conflicting human judgment.
A color appears different depending on adjacent colors.
Decisions are constrained by available information, cognitive limits, and time.
The ability to focus on one voice in a noisy environment.
Where Constructed Preferences 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.
- ReferenceThe incentive glossary
Definitions for every mental model, bias, and fallacy in the corpus.
- 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 Constructed Preferences
- What is Constructed Preferences?
- Constructed Preferences is preferences aren't retrieved from a stable internal list — they're built on the spot from cues, context, and the elicitation method. It sits in the Cognition dimension (COG) of the Human Behavior Taxonomy™ as element HBT-COG-0181, within the Decision family. The core principle: preferences aren't retrieved from a stable internal list — they're built on the spot from cues, context, and the elicitation method. 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 Constructed Preferences?
- Pricing pages, survey design, and any place a user 'tells you' what they want. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-COG-0181).
- How is Constructed Preferences exploited?
- Pricing pages, survey design, and any place a user 'tells you' what they want.
- How do you design around Constructed Preferences?
- Test multiple framings. The first one isn't truth — it's the one you happened to try.
- Which behavioral dimension does Constructed Preferences belong to?
- Constructed Preferences is classified in the Cognition dimension (COG) of the Human Behavior Taxonomy™, family "Decision", class "Mental Model". Its permanent identifier is HBT-COG-0181 and its evidence grade is B.