What is the AI Kill Threshold?

The AI Kill Threshold is a probability (0-100%) indicating how likely your occupation will be replaced by AI. It is calculated using the Swiss Cheese Barrier Model across four independent dimensions: Learnability, Evaluation Objectivity, Risk Tolerance, and Human Presence.

How is the replacement probability calculated?

Using a Weighted Power Mean with r=-2 across four dimensions. Learnability has weight 0.30, Evaluation Objectivity 0.25, Risk Tolerance 0.20, Human Presence 0.25. An additional E+O interaction bonus applies when both knowledge is explicit and evaluation is objective.

What data sources does AIR use?

AIR aggregates from BLS OES 2023 (798 occupations employment data), O*NET (task structure labels), Eloundou et al. 2023 (LLM exposure measurement across 19,265 tasks), OpenAI GDPval (AI vs human expert blind evaluation), and the World Economic Forum Future of Jobs Report 2025.

How does AIR differ from MBTI?

MBTI measures personality. AIR measures occupational AI-replacement risk. Both use four binary dimensions producing a 4-letter code, but AIR's dimensions are grounded in automation economics literature and the output is backed by employment data from 798 real occupations.

What is the current industry-wide AI replacement rate?

As of 2026, the employment-weighted industry-wide AI replacement rate is 24.7%, calculated as Task Exposure (34.8%, Eloundou et al. 2023) times AI Win Rate vs human experts (71.3%, OpenAI GDPval).

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ESRH

The Oracle

“People trust your judgment with their careers, fortunes, and lives”

Low Risk

대체 확률

15%–30%

예측 연도 범위

2038–2052

리스크 등급

Low Risk

Explicit + Subjective + Rigid + Human: AI can learn knowledge, but subjective quality + high liability + clients trust the person

초능력

Decades of judgment that carries legal and moral weight — AI has opinions, you have authority

약점

AI is accessible 24/7 and costs nothing — some will choose convenience over credentials

네 가지 장벽 차원

학습 가능성 — 명시적 (E)

AI가 당신의 업무에 필요한 지식과 기술을 습득하고 학습할 수 있나요?

평가 객관성 — 주관적 (S)

당신의 업무에 "정답"이 있나요? 성과를 객관적으로 측정할 수 있나요?

오류 허용도 — 엄격형 (R)

AI가 실수하면 그 결과를 감당할 수 있나요? 그 산출물을 신뢰할 수 있나요?

인격 의존성 — 인간형 (H)

당신의 가치는 "무엇을 만드느냐"에 있나요, 아니면 "당신이 누구인지"에 있나요?

왜 노출되었는가

Knowledge is explicit and digitized — AI can learn everything you know from documentation and data. This is your one exposed flank.

자연 방어

Three powerful barriers: subjective quality judgment, irreversible consequences, and personal trust. Think senior partners, consulting leaders, attending physicians — authority that takes decades to build.

대표 직업

Legal (23) — partners, Management (11) — consulting, Healthcare Practitioners & Technical (29) — attending physicians

대표 직업 리스크

Administrative Law Judges
Rule-based adjudication on structured cases — AI can assist research but decisions carry legal weight
15
Arbitrators, Mediators, and Conciliators
Dispute resolution depends on interpersonal trust and contextual judgment
15
Judicial Law Clerks
Legal research and memo drafting increasingly AI-assisted — judgment and synthesis remain human
12
Judges, Magistrate Judges, and Magistrates
Constitutional authority and moral reasoning make judicial decisions irreducibly human
11
Paralegals and Legal Assistants
Document review and case research automating fast — value shifts to complex filings and client contact
6
Lawyers
Professional liability, bar licensure, and client trust create deep structural moats
2

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