People Shaping the Future of AI seriesFrom questioning an unjust world to building ethical AI

An image with Yuri Nakao in the center and rest of interviewee in the background.

Interview article | 2026-9-30

10 minute read

As AI becomes embedded across business and society, organizations face unprecedented risks. Systems designed to drive efficiency can unintentionally reinforce discrimination, deepen social divisions, and undermine the trust companies have built with customers, consumers, and markets. As these dilemmas become increasingly intertwined, how should we respond?

Among the researchers exploring these questions is Yuri Nakao of Fujitsu, whose work sits at the crossroads of technology, ethics, and society. His work focuses on a key element of Trust in AI: secure and ethical AI, and how it can respond to society’s evolving values.

What is Trust in AI?

Trust in AI is an approach for building confidence in AI. It is built around five key elements: Explainable, Secure & Ethical, Sovereign, Sustainable, and Connected. Together, these elements help organizations adopt AI in ways that are responsible, transparent, and aligned with human values.
In ”People Shaping the Future of AI series", we explore the personal stories, motivations, and research journeys of the people working to make trusted AI a reality. This article highlights the Trust in AI element of ”Secure and Ethical”, showing how one's work contributes to building AI that people, organizations, and society can trust.

An early lesson on human-centric AI

Yuri Nakao's photo when working on Itoshima project.

One of the first projects to shape Yuri’s approach to AI took him to Itoshima, Fukuoka, where Fujitsu was working with the city to encourage relocation and help sustain its local communities. At the time, Itoshima was facing population decline, with many people moving away from the area. To attract new residents and support future growth, the city needed a better way to communicate what made each neighborhood distinctive and appealing. The challenge was that this knowledge was tacit, rather than something AI could readily use. It existed largely in the experience, instincts, and local understanding of city officials and residents.

To make this tacit knowledge explicit and organize it, Yuri spent countless hours speaking with city officials and residents, listening to the stories and observations that shaped their understanding of each neighborhood. He then compared those insights with public data, using large maps to piece together the factors behind seemingly simple descriptions. A phrase such as “popular with families with children”, for example, might reflect the number of childcare facilities, the size of nearby parks, or the safety and visibility of school routes. By identifying those relationships, he was able to translate local knowledge into logic that AI could use. The result was the Relocation Matching System, which recommends suitable neighborhoods based on a few questions about a person’s lifestyle and preferences.

For Yuri, the project represented far more than a technical success. Long before AI became part of everyday conversation, he had seen how knowledge rooted in human experience could be transformed into technology that created real value for society. That experience stayed with him and would go on to shape the direction of his future research.

The roots: confronting an unjust world

Yuri's childhood photo

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Born in Kyoto, Yuri was a child who spent much of his time immersed in books. When he was five years old, he saw television news footage showing the realities of civil wars and famine. The images stayed with him, sparking questions that few adults around him seemed able to answer. “Why do people go to war?” “Why are there children with swollen stomachs when there is no food?”
Yuri was struck by the suffering and unfairness he saw in the world. That early sense of indignation, combined with a deep empathy for others, has remained a defining influence in his life and work.

“Knowledge is something no one can take away from you.” Encouraged by those words, Yuri studied the humanities, hoping to contribute to peace through an organization such as the United Nations. However, in high school, he switched to the sciences, realizing it was his opportunity to build a foundation in mathematics and technology.
A conversation with a visiting politician helped Yuri come to the realization that reducing poverty and inequality would require addressing the gaps in access to information. That realization led him toward information technology.

At university, Yuri initially studied engineering. Yet his curiosity refused to stay confined to a single discipline. Crossing the divide between the sciences and the humanities for a second time, he entered the field of Science and Technology Studies (STS), which examines how scientific and technological advances interact with society.

“What responsibilities do scientists have in shaping the relationship between technology, people, and society, and how can they make those technologies worthy of trust?” While academia sought answers to questions like these, Yuri found himself looking one step further ahead.
"Social science can certainly help identify problems. But identifying problems alone does not change the world," he says. "I wanted to embed ethics and social considerations directly into the technologies we build. I felt that was the more responsible path." That belief ultimately led him to Fujitsu.

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Questioning what fairness means for AI

AI’s performance and behavior depend on data, which reflects the history of human society. Today, Yuri’s attention is focused on a deeper question: “How can AI embody fairness and justice?”
Fairness varies across countries and cultures. For example, in the United States, race is often central to the debate, while gender disparities remain a significant concern in Japan. Attempting to define fairness through a single, top-down standard, Yuri believes, risks oversimplifying a profoundly complex issue. To tackle this challenge, Yuri has partnered with the University of Glasgow in the United Kingdom. Together, they are exploring ways to give direct stakeholders a direct voice in how fairness is defined within AI systems. Through workshops and other collaborative approaches, participants make their values and priorities explicit, allowing those perspectives to be reflected in the design of AI models. When diverse values are incorporated from the earliest stages, fairness becomes something stakeholders help define, rather than a single standard imposed from above.
Yuri is equally convinced that AI should never be viewed as an infallible source of truth. Instead, people must begin with understanding that AI is inherently imperfect. Used appropriately, it can serve as a partner for reflection, helping individuals recognize their own assumptions, challenge their biases, and engage in more thoughtful decision-making.

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Photo of Yuri getting interviewed in office.

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"The ideal future is something closer to hybrid intelligence, where humans and AI grow wiser together," he says. In that sense, Yuri’s research is not only about making AI more trustworthy. It is equally about cultivating the judgment and responsibility needed to use AI wisely.

Building trust through human-centric AI

Yuri's current work is AI alignment: the challenge of ensuring AI systems act in ways that are consistent with human intentions, values, and ethical principles. The goal is simple in principle but difficult in practice.
Human values evolve over time. Ethical standards shift as societies change. AI, however, learns from historical data and can remain anchored to past assumptions. "AI has no inherent understanding of future values," says Yuri. "Ultimately, people must continue to think about those values and continue teaching them to AI." For him, the goal is not for humans to follow AI, but for AI to remain guided by humans. Creating technologies that preserve that relationship is essential to ensuring AI can be trusted in the long term.
This reflects Fujitsu’s human-centric philosophy. “AI should remain a tool for people, and its evolution must proceed in harmony with humanity,” Yuri says. He believes Fujitsu can contribute perspectives beyond the Western frameworks that often dominate AI ethics, helping build more inclusive and adaptable forms of trust.
His efforts extend beyond research activities within Fujitsu. He has also contributed to public discussions on AI governance as a member of government advisory panels focused on AI policy and regulation, helping to shape broader conversations around how trustworthy AI should be developed and deployed.
The child who once questioned the injustices of the world has become a researcher working to develop AI that reflects the evolving values of human society.

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Yuri Nakao holding graphic recording of the whole interview.

Yuri Nakao and the graphic recording

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Graphic recording summarizing the career and philosophy of an AI ethics researcher. Tracing a journey that began with questioning social injustice in childhood, the illustration shows how empathy for human suffering led to a pursuit of fairness and a career in AI governance research. It highlights the belief that AI cannot define ethics on its own and that humans must continue to shape and teach it, reflecting the principles behind Trust in AI.

A close-up view of the graphic recording

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Trust in AI is our framework for building that business can truly depends on. Five elements, Explainable, Sustainable, Connected, Secure & Ethical, and sovereign designed from the start to be trusted.

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