ヴィヴィアン・ミン（1971年–）は、アメリカの理論神経科学者、AI研究者、起業家。カーネギーメロン大学で心理学の博士号を取得し、神経科学と機械学習を組み合わせて、人間の学習、能力、健康、働き方を研究してきた。複数のテクノロジー企業の創業や最高科学責任者を経験し、人間の潜在能力を研究するSocos Labsを設立。教育、採用、医療などの分野で、AIを人間の判断や成長に役立てるシステムの開発に取り組んでいる。代表作『Robot-Proof: When Machines Have All the Answers, Build Better People』（未邦訳）は、知識や定型的な専門技能をAIが代替していく時代には、好奇心、共感力、創造性、回復力、認知的柔軟性が重要になると論じた書籍である。学校教育や採用を、試験成績や資格による選別から能力を育てる仕組みへ転換し、AIに思考を任せるのではなく、自分の仮説への反論や見落としを探させる「生産的な摩擦」のために利用する方法を示している。
Vivienne Ming (born 1971) is an American theoretical neuroscientist, artificial intelligence researcher, and entrepreneur. After earning a PhD in psychology from Carnegie Mellon University, she combined neuroscience and machine learning to study human learning, ability, health, and work. She has founded several technology ventures, served as chief scientist at multiple companies, and established Socos Labs to investigate the future of human potential. Her work applies AI to education, hiring, health care, and other fields in ways intended to improve human judgment and development. Her representative work, “Robot-Proof: When Machines Have All the Answers, Build Better People,” argues that as AI takes over knowledge-based and routine professional tasks, curiosity, empathy, creativity, resilience, and cognitive flexibility will become increasingly important. The book calls for education and hiring systems that develop human capacity rather than merely screen people by tests and credentials, and recommends using AI to challenge assumptions and reveal blind spots instead of allowing it to replace independent thought.
