Professor Daniel J. Mills
Ritsumeikan University, Japan

Daniel J. Mills, Ed.D. is a professor in the Faculty of Economics at Ritsumeikan University in Shiga, Japan, where his research focuses on financial literacy education, educational technology, and innovative approaches to teaching personal finance. Having lived and worked in Japan for more than twenty years, he has extensive experience working at the intersection of economics education, language education, and technology-enhanced learning.
Dr. Mills’ research examines how digital tools, artificial intelligence, and informal learning communities can improve financial literacy and expand access to financial education. His recent work explores the role of generative AI and emerging technologies in supporting scalable, technology-enhanced financial learning both inside and outside the classroom. His scholarship has been published in leading journals in the fields of educational technology and computer-assisted language learning.
In addition to his academic research, Dr. Mills is the editor of the Scopus-indexed journalCALL-EJ and has been an active contributor to international academic conferences on technology-enhanced learning. He is also a certified financial educator and the founder of The FI Professor, an educational initiative dedicated to helping individuals, particularly Americans living abroad, build financial independence through practical financial literacy education.
Dr. Mills regularly speaks at international conferences and has appeared on numerous podcasts and webinars on financial independence, investing, and financial education. His work uniquely bridges academic research and real-world financial practice, bringing evidence-based insights to the global conversation on financial literacy and lifelong learning.

Frictionmaxxing: Gated AI, Human Skills, and the Case for Keeping Things Mostly Difficult

Abstract: We have spent a generation engineering friction out of everything. When we describe effective technology, we reach for words like seamless, instant, and effortless. Generative AI is the epitome of these ideals. However, some young people have begun to push back. 'Frictionmaxxing' is a growing online trend: the deliberate choice to make life harder again, on the belief that effort is what gives our life meaning and keeps us human. They are onto something, but the answer is not simply to make everything difficult.

In this keynote, I argue for a middle path: a gated AI approach that keeps what is useful about these tools while preserving the human capacities that matter. When the answer arrives with no effort, the abilities we most need begin to fade. Creativity, critical thinking, and ethical judgment are not downloaded. They are built through practice and experience, and a generation that outsources everything will lose the capacity to tell good AI output from bad. If no one can do the human work, the human-in-the-loop becomes a passenger, and the results suffer.

Keeping these skills alive, in ourselves and in the next generation, is now essential work. As AI grows more capable, the people who can still think, create, and judge well will be the ones who remain hard to replace. The goal is not to remove every hurdle, and not to add them back at random, but to design the right ones on purpose..
 

Professor Joo Han Ryoo
Hanyang University, Korea

Professor Joo Han Ryoo, currently serving as a faculty member in the Department of International Studies at Hanyang University, graduated from New York University with a major in Business Administration and a minor in Economics. He earned his Ph.D. in Management from the London School of Economics (LSE).

His main research areas include international market entry, competitive strategy, strategic alliances, mergers and acquisitions (M&A), post-merger integration strategies, and venture management. As of 2015, he has published nine papers in domestic journals and nine in international journals.

He is an active member of the Association of International Business (AIB) and serves as an editorial board member for Asia Pacific Business Review (UK), East-West Studies (Korea), and Dispute Resolution Studies (Korea). He has also contributed approximately 75 articles to major publications such as The Dong-A Ilbo, Dong-A Business Review (DBR), and Harvard Business Review Korea.

Beyond Sensing: Why Human Judgment Is the Last Competitive Edge in the Age of AI

Abstract: For decades, competitive advantage often went to the firm that could see first. The company that gathered better information, scanned the market faster, and spotted a rival's next move held the edge. Generative AI is now changing this. When every firm can ask the same AI the same questions about the same public data, the act of sensing becomes cheap and nearly identical for everyone. The old advantage is being commoditized.

This keynote asks a simple question: if machines now do the collecting, where does advantage go? Drawing on the field of competitive intelligence, I argue that it moves to the part machines cannot copy — interpretation, judgment, and the decision of when to act. Recent evidence shows that AI clearly lifts knowledge work, yet it also fails silently at a "jagged frontier" and pushes many users toward the same answers. The hard task was never gathering data, but reading it without the human biases that distort what we see, such as confirmation bias and mirror-imaging.

As AI removes the effort of collection, these human capacities become the real and lasting edge. The talk closes with practical implications for firms and educators: in a world where everyone holds the same AI, the people who can still interpret, judge, and decide well will be the hardest to replace.