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Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

2026-05-20 23:52:15 +09:00

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title

Nudge Theory

매 한 줄

"매 choice architecture를 미세 조정하여 freedom of choice를 보존한 채 predictable한 방향으로 행동을 유도.". Richard Thaler · Cass Sunstein의 Nudge (2008) — 2017 Thaler 노벨경제학상. 2026 현재 UX design · public policy · health intervention · LLM safety의 기반 framework.

매 핵심

매 nudge 정의 (Thaler/Sunstein)

매 small change in choice architecture
매 predictable behavior change 유도
매 옵션을 금지하지 않음 (libertarian paternalism)
매 economic incentive 거의 없음 (cheap)

매 mechanism

Default: 매 default option 압도적 영향 (organ donation opt-in vs opt-out — 12% vs 99%).
Salience: 매 정보 visibility 증가.
Framing: 매 동일 정보, 다른 표현 (90% lean vs 10% fat).
Social proof: 매 "X% of users do Y".
Friction: 매 desired action은 쉽게, undesired는 hard.

매 응용

UK Behavioral Insights Team — tax letter "9 of 10 pay on time" → 5% 회수율 증가.
Spotify "Discover Weekly" → 매 default playlist으로 engagement 증가.
Apple Health — 매 default 7000 step goal로 average +500 step.

💻 패턴

Default opt-in for desired behavior

// BAD: opt-in for 2FA
<Checkbox label="Enable 2FA (recommended)" defaultChecked={false} />

// GOOD: default-on with easy opt-out
<Checkbox
  label="Enable 2FA"
  defaultChecked={true}
  helperText="Recommended. You can disable in Settings."
/>

Friction: confirm destructive action

function DeleteAccountButton() {
  return (
    <ConfirmDialog
      title="Delete account?"
      requireType="DELETE my-username"  // typed friction
      cooldownSeconds={5}
    >
      <Button variant="danger">Delete</Button>
    </ConfirmDialog>
  );
}

<PricingCard plan="pro" badge="Most popular — 73% of teams choose this" />

Framing — loss aversion

// BAD (gain frame, weaker)
<p>Save $120/year with annual billing</p>

// GOOD (loss frame, stronger; Tversky/Kahneman)
<p>Stop paying $10/mo extra — switch to annual</p>

Salience — progress nudge

function ProfileCompletion({ percent }: { percent: number }) {
  return (
    <Banner show={percent < 100}>
      Profile {percent}% complete — add a photo to reach 100%
      <ProgressBar value={percent} />
    </Banner>
  );
}

Implementation intention prompt

// "When X happens, I will do Y" — proven habit formation
<Onboarding>
  <p>When will you exercise?</p>
  <Select options={["Morning", "Lunch", "Evening"]} />
  <p>Where?</p>
  <Input placeholder="Living room, gym..." />
</Onboarding>

매 결정 기준

상황	Approach
User benefits from default	opt-out default
User must consciously choose	opt-in, no default
Discourage harm	friction (confirm, delay)
Encourage rare valuable action	salience + reminder
Group conformity helpful	social proof

기본값: transparent default + easy opt-out — 매 dark pattern과의 차별점.

🔗 Graph

부모: Behavioral_Economics · Cognitive_Bias
변형: Choice_Architecture · Habit_Loop
응용: Micro-interactions · Gamification
Adjacent: FOMO (Fear of Missing Out) · Progressive-Disclosure · 매몰_비용_오류_(Sunk_Cost_Fallacy)

🤖 LLM 활용

언제: UX flow 설계, public health/policy, habit-forming product, opt-in/opt-out 결정. 언제 X: high-stakes informed consent (의료, 금융 — 매 explicit choice 필수), regulated decision (legal contract).

❌ 안티패턴

Dark pattern (sludge): 매 친 user가 아닌 친 vendor — Sunstein 본인이 Sludge (2021)로 비판.
Hidden default: 매 user 모르게 enable — opt-in의 transparency 무시.
Manipulation > nudge: 매 deception (e.g. fake countdown) — ethics 위반.
Over-nudging: 매 모든 화면에 nudge — banner blindness.
No measurement: 매 A/B test 없이 nudge — direction 불명.

🧪 검증 / 중복

Verified (Thaler/Sunstein Nudge 2008 / 2021 final ed., UK BIT trial reports, Sunstein Sludge 2021).
신뢰도 A.

🕓 Changelog

날짜	변경
2026-05-08	Phase 1
2026-05-10	Manual cleanup — Nudge theory (Thaler/Sunstein) + UX patterns

4.8 KiB Raw Blame History