- Who
Now a fourth-year doctoral candidate in applied mathematics and computational science in the School of Arts & Sciences and a master’s student in statistics and data science at the Wharton School, Hiroaki (Hiro) Chiba-Okabe came from a very different background: working in international law in Japan.
Growing up in Tokyo, Chiba-Okabe enjoyed an introductory law course in high school and majored in law at Keio University. He took Japan’s preliminary bar examination at age 19, allowing him to take the bar without going to law school, and passed the bar at 20. But Chiba-Okabe says he only knew he was a good law student from doing well on exams. He always felt unsure.
“When I started working as a lawyer, I realized that it is complicated, actually, and that’s because the real world is complicated and there are many different stakeholders,” he says. He worked for two years at a law firm, focusing on business law and international law, and two years for the Japanese government, where he dealt with disputes between Japan and other countries along with international rule-making processes.
- What
Chiba-Okabe now mostly works in two lines of research. One is with biologist Joshua B. Plotkin, using theoretical models to study questions about social norms, behaviors, and institutions.
Chiba-Okabe was the lead author on a theoretical study published earlier this year examining whether different types of institutions with different goals could promote cooperation through wealth redistribution. He and Plotkin found that even an institution that does not share the interests of its population, such as an autocratic regime, can promote cooperation if it is sufficiently forward-looking because it could get a future benefit from taxation.
Chiba-Okabe’s second area of work, with Wharton’s Weijie Su, is related to generative AI. He came up with a quantitative metric and algorithm to modify the outputs of generative AI models so they’re less likely to infringe copyright of existing works, an idea he got from legal theory. He is also working on using probability theory to analyze the core elements of copyright infringement disputes.
“I think the common thread is that I used quantitative or mathematical reasoning to try to extract the fundamental elements or aspects of these rules or norms,” Chiba-Okabe says. He says he can pursue a broad range of interests and approaches because Penn faculty work in diverse fields and are open to collaboration, even with people from different backgrounds and disciplines. He hopes to continue doing research beyond his Ph.D.
- Why
Chiba-Okabe says it’s difficult to pin down a single reason he decided to pursue this Ph.D., but he traces his interest in using mathematical modeling for studying social behavior to reading books on game theory in college.
“I was kind of amazed by how you can use math to study something as complicated as human behavior,” he says. A seminar on antitrust law and international economic law, where quantitative reasoning plays a notable role, also made him wonder about broader connections between law and mathematical modeling.
“I think what math can do is really bring clarity into this chaotic world. If you just try to tackle these problems head-on, there are just too many factors and too many different values and a lot of complexity,” Chiba-Okabe says. “I think what math can do is help you think about what these core elements are and apply these logical, transparent tools that are available.”
