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ESFP

The Taste Maker

“AI generates a thousand options — you know which one is right”

High Risk
대체 확률
55%–72%
예측 연도 범위
2029–2035
리스크 등급
High Risk

Explicit + Subjective + Flexible + Product: AI can learn, errors are tolerable, only results matter, but quality is subjective

초능력

Aesthetic judgment and cultural intuition machines can't learn from data

약점

AI is already generating content that passes the taste test

네 가지 장벽 차원

E
학습 가능성 — 명시적 (E)
AI가 당신의 업무에 필요한 지식과 기술을 습득하고 학습할 수 있나요?
S
평가 객관성 — 주관적 (S)
당신의 업무에 "정답"이 있나요? 성과를 객관적으로 측정할 수 있나요?
F
오류 허용도 — 유연형 (F)
AI가 실수하면 그 결과를 감당할 수 있나요? 그 산출물을 신뢰할 수 있나요?
P
인격 의존성 — 성과형 (P)
당신의 가치는 "무엇을 만드느냐"에 있나요, 아니면 "당신이 누구인지"에 있나요?

왜 노출되었는가

Knowledge is learnable, errors are tolerable, and only output matters — AI can iterate endlessly at near-zero cost in these three dimensions.

자연 방어

Quality is subjectively judged — "good" depends on taste, context, and cultural nuance. AI struggles with the moving target of subjective standards.

대표 직업

Arts, Design, Entertainment, Sports & Media (27) — design/planning, Computer & Mathematical (15)

대표 직업 리스크

  • Software Developers
    AI coding assistants accelerating productivity — and also changing what developers need to know
    39
  • Software Quality Assurance Analysts and Testers
    Test generation and regression automated — exploratory and edge-case testing still requires humans
    22
  • Computer User Support Specialists
    Tier-1 troubleshooting increasingly automated by AI; complex issues still need human diagnosis
    21
  • Data Scientists
    Automated ML pipelines lower the bar — data scientists shift toward problem framing and interpretation
    20
  • Computer Systems Analysts
    Requirements translation and integration work — business context requires humans in the loop
    18
  • Network and Computer Systems Administrators
    Infrastructure monitoring increasingly automated — complex configurations and security still need humans
    16
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