UTokyo, STS/SicComm Yokoyama Lab

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Hiromi M. Yokoyama, Prof. Ph.D (Sci)

Professor (Science and Technology Studies : STS, Sociology of Science & SciComm) at the University of Tokyo. Born in Tokyo in 1975, after she earned her PhD in physics (neutrino oscillations) I switched my research field to STS. This unique background is what led me to hold positions at Kavli Institute for the Physics and Mathematics of the Universe and the Graduate School of Interdisciplinary Information Studies.

My research spans three core areas: AI Ethics and Governance, Trust in Science and STI Human Resources.

I have been an associate member of the Science Council of Japan for many years. Currently serves as Board Member of Toyota Foundation, and the National Institute of Technology (KOSEN), the Japanese Society for STS, University of Tokyo Press.She has contributed to government and international advisory committees including Scientific Committee Member of PCST Network.

Email : hiromi.yokoyama_a_ipmu.jp : GoogleS. : LinkdIN : Career : Committee : Media Coverage : Writing : Books

Profile

I received my Ph.D. in Physics from Tokyo University of Science in 2004, where I studied under Koji Nakai. After positions at Tokyo Institute of Technology and SOKENDAI, I became Associate Professor at the Graduate School of Science, the University of Tokyo, in 2007, and Professor at Kavli IPMU and the Graduate School of Interdisciplinary Information Studies, the University of Tokyo, in 2017.

I currently serve as a Board Member of the National Institute of Technology (KOSEN), the Toyota Foundation, the Japanese Society for Science and Technology Studies, and the University of Tokyo Press; as an Editorial Advisory Board Member of the Journal of Science Communication (JCOM); and as a member of the PCST Scientific Committee.

I have also served on numerous evaluation and advisory committees for universities, research institutions, basic research, and large-scale research facilities. Current roles include the MEXT Central Council for Education’s Subdivision on Graduate Schools, the committee for strengthening universities and colleges of technology in growth fields, the AI for Science Promotion Committee, the Yamagata University Management Council, and the NHK Central Broadcast Program Council. In recent years, I have also served on an increasing number of international advisory committees.

Welcoming visiting students & researchers

We welcome visiting students supported by their universities and researchers with the aim of conducting collaborative research. The JSPS fellowships and Posdoc at Kavli IPMU will suppor you. Please check the member page.

Now! Postdoctoral Fellowships, deadline November 15, 2026 (JST)

研究室メイン画像

Kavli IPMU @ Kashiwa / Graduate School, Main building @ Hongo campus

Current collaborative research partners: Australian National University, Tsinghua University, University of Melbourne, University of Chicago, Princeton University, Harvard University, Central South University, University of Jyväskylä, etc.

Research Overview

AI Ethics and Governance

I study the ethical challenges that arise as AI is implemented across society. My research has expanded from cross-national studies measuring ELSI and RRI to AI policy, AI for Science (AI4S), medical AI, Sustainable AI, Energy Justice, facial recognition, well-being measurement, research integrity, generative AI, and Digital STS. In my earlier work, I developed the ELSI Sheet to quantify ethical, legal, and social concerns surrounding AI; AI ELSI Segmentation to classify patterns in public attitudes; and the Octagon Measurement to visualize acceptance through eight ethical principles. I later broadened this work to international comparisons and to issues involving generative AI, medicine, and the environment. In 2026, I analyzed why Japan has historically emphasized the “promotion” of AI more than regulation, describing this approach as light-touch AI governance. In essays and public-facing work, from a perspective committed to peace, I also actively address the relationship between war, military applications, and AI.

Keywords: Singularity, AI weapons, data center issues, Energy Justice, AI4S, medical AI, Sustainable AI, Digital STS, research integrity

Trust in Science

Trust in science is a central theme of my work in Science and Technology Studies (STS). I study a wide range of issues, including 3.11 and risk communication, scientific advice, COVID-19, digital media, Big Science, CRISPR and bioethics, elitism and populism surrounding science, research funding, and crowdfunding. A distinctive feature of this work is my proposal of Group Voice: in times of crisis, scientific information should not depend on the statements of a single prominent scientist, but should be communicated by groups of experts that collectively ensure its quality. I have also proposed the concept of a Budget-funding Community, which views science not only through communities of scholarly publication but also through its relationship with the people and institutions that fund it. In this research, trust in science is understood not simply as a matter of insufficient public understanding, but as a relationship among experts, institutions, media, and society.

Keywords: science and risk, ELSI, RRI, science communication, scientific advice, polarization, geoengineering, Big Science

STI Human Resources

Since joining Kavli IPMU in 2017, I have continued to study, initially at the institute’s request, the social factors behind the low proportion of women in Japan who choose fields such as mathematics, physics, and engineering. Through research on parents’ gender attitudes, stereotypes among high school students, girls’ choice of physics, the “masculine image” of mathematics and physics, beliefs about brilliance, teachers’ implicit bias, and intervention experiments that provide information about gender equality, I have examined how social climate and images of academic fields shape educational and career choices. More recently, I have expanded this work to affirmative action measures that I have also discussed critically, including women’s admission quotas and women-only faculty recruitment. In 2026, I analyzed how faculty members in physics and engineering evaluate direct affirmative hiring for women.

Keywords: gender bias, mathematics stereotypes, social climate, women’s admission quotas, women-only faculty recruitment, policy recommendations, science for policy