refactor(topics): 멀티 에이전트용 지식 재편 — _Common(공통 기본기) + Domain_* 구조
에이전트 8종(대화형/프로그래머 C·S/디자이너/설계자/기획자/QA/PD/PM)에게 [공통 기본 능력 + 롤별 Specialty] 2층으로 지식을 주입하기 위한 재분류. 문서 내용·포맷은 무수정, 폴더 이동만 (6,372개 문서 수 보존 확인). - Topic_Programming → Domain_Programming (내부 구조 보존) - Topic_Graphic → Domain_Design - Topic_Business → Domain_Product - Topic_General → Domain_General - _Common 신설: Math(구 Topic_Math_Specialty), Reasoning(구 General/From_Thinking & Reasoning), Reasoning_Creativity(구 General/From_창의성), Communication(Poetic_Blog_Writing + From_writing) - 타 도메인의 From_* 폴더는 유지 (출처 표기일 뿐, 이미 도메인에 맞게 분류된 문서) - 빈 폴더 정리 (memory/procedures) - 에이전트→폴더 매핑은 workspace의 .astra/agent-knowledge-map.json (9개 에이전트) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Antigravity Agent
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---
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id: wiki-2026-0508-universal-basic-income-ubi
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title: Universal Basic Income (UBI)
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [UBI, Basic Income, Citizen's Income]
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duplicate_of: none
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source_trust_level: B
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confidence_score: 0.8
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verification_status: applied
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tags: [policy, ai-economy, ubi, automation, future-of-work]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: na
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framework: policy-economics
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---
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# Universal Basic Income (UBI)
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## 매 한 줄
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> **"매 unconditional cash transfer to every citizen, regardless of work or means"**. 매 18세기 Thomas Paine 부터 Friedman의 negative income tax 까지 historical roots. 매 2020s LLM-driven labor displacement 이 debate를 mainstream으로 — Sam Altman (OpenAI), Andrew Yang, Yuval Harari 의 advocacy. 매 2026 현재 GiveDirectly Kenya, Stockton SEED, Sam Altman의 Worldcoin / OpenResearch 등 실증 pilot data 축적 중.
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## 매 핵심
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### 매 4 defining features
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1. **Universal**: 매 citizen 모두 (means-test 없음).
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2. **Unconditional**: work requirement 없음.
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3. **Cash**: in-kind voucher 가 아닌 현금.
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4. **Regular**: monthly / quarterly recurring (one-shot 이 아님).
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### 매 motivation 의 spectrum
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- **Left**: poverty elimination, labor decommodification.
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- **Libertarian** (Friedman, Hayek): replace welfare bureaucracy with simple transfer.
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- **Tech / AI**: automation displacement → redistribute productivity gains.
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- **Feminist**: unpaid care work 의 recognition.
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### 매 funding mechanisms
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1. **Carbon tax dividend** (Alaska Permanent Fund model).
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2. **VAT** (Andrew Yang's "Freedom Dividend" proposal).
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3. **AI / data dividend** (compute tax, data tax).
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4. **Land value tax** (Georgist).
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5. **Sovereign wealth fund returns**.
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### 매 evidence (modern pilots)
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- **Finland 2017-18**: 2000 unemployed, €560/mo. wellbeing↑, employment ~neutral.
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- **GiveDirectly Kenya 2017+**: 12-year RCT, 20K+ recipients. asset/business creation↑.
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- **Stockton SEED 2019-21**: $500/mo. full-time employment↑ (28% → 40%).
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- **Sam Altman OpenResearch 2020-23**: $1000/mo, 3 years, 3000 people in TX/IL.
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- **Wales basic income for care leavers 2022+**: £1600/mo for 18-yr-olds out of foster care.
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### 매 AI-induced unemployment debate
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- **Optimist (Karl Benz argument)**: new jobs emerge (jevon's paradox 의 extension).
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- **Pessimist (Acemoglu, Hinton)**: cognitive automation 은 historical pattern 다름.
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- **Empirical 2024-26**: software engineering, customer service, translation 의 measurable wage compression. 그러나 net unemployment 는 not yet structural.
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### 매 응용
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1. Poverty floor.
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2. Bargaining power for low-wage workers (exit option).
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3. Entrepreneurship enablement.
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4. Caregiver / artist subsidy.
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5. AI displacement insurance.
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## 💻 패턴 (policy design)
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### Pattern 1: Negative Income Tax (Friedman)
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```text
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benefit = max(0, (threshold - income) × rate)
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# threshold = $30K, rate = 50%
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# income $0 → benefit $15K
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# income $20K → benefit $5K
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# income $30K → benefit $0
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# Phase-out automatic, but not "universal".
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```
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### Pattern 2: Pure UBI flat
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```text
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benefit = $1000/month for every adult citizen
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funding = 10% VAT + carbon dividend
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# Universal, but expensive. ~$3T/yr in US.
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```
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### Pattern 3: Alaska Permanent Fund (real-world precedent)
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```text
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oil_revenue → sovereign_fund (1976-)
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annual_dividend = fund_5yr_avg_return × payout_ratio
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# 1982-2024: $1000-$3200 per resident annually.
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# 매 only true unconditional cash transfer at scale 의 sustained example.
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```
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### Pattern 4: AI / compute dividend (proposed, 2020s)
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```text
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tax = compute_used × rate // foundation model training
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fund = sovereign_AI_fund
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dividend = fund_return / population
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# Not yet implemented. Sam Altman의 OpenAI public benefit proposal.
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```
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### Pattern 5: Pilot RCT design
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```text
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1. Random assignment: treatment ($500-$1000/mo) vs control.
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2. Duration: ≥3 years (recover Hawthorne, capture habit formation).
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3. Outcomes: employment, wellbeing, health, education, household formation.
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4. Pre-registration: avoid p-hacking.
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5. Heterogeneity analysis: by income, age, family structure.
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```
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## 매 결정 기준
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| 정책 목표 | Approach |
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|---|---|
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| Poverty elimination only | Targeted transfer / NIT |
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| Reduce welfare bureaucracy | NIT or UBI replacing means-tested |
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| AI displacement hedge | UBI + retraining stipend |
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| Resource curse (oil, gas) | Sovereign fund dividend (Alaska) |
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| Care work recognition | Targeted caregiver UBI |
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**기본값**: NIT for fiscal pragmatism, full UBI for radical simplicity (high cost).
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## 🔗 Graph
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- Adjacent: [[Technological Unemployment]]
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## 🤖 LLM 활용
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**언제**: AI economic impact 분석, automation policy 토론, welfare reform 비교.
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**언제 X**: pure macro forecasting (UBI 의 macro effect 의 unsettled).
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## ❌ 안티패턴
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- **"UBI fixes everything"**: housing / healthcare 의 supply constraint 는 cash transfer 로 해결 X.
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- **Confounding NIT with UBI**: means-tested 와 universal 의 혼동.
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- **Ignoring inflation**: $1000/mo 이 housing-supply-constrained 시장에선 rent 로 흡수.
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- **Cherry-picking pilot results**: short pilot 은 long-term 행동 변화 capture 못 함.
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- **Replacing all welfare**: disability, healthcare 의 specialized support 까지 cash 로 대체 시 vulnerable 그룹 손해.
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## 🧪 검증 / 중복
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- Verified (OpenResearch 2024 final report; GiveDirectly RCT 2024; Stockton SEED 2-yr report 2021; Hoynes & Rothstein review NBER 2019).
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- 신뢰도 B (정책 영역, contested empirical evidence).
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — UBI definition, pilot data, AI displacement context |
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