Yufei Yuan, a professor of information systems at DeGroote, has researched AI, neural networks, and automated reasoning since the 1990s.
However, he has been interested in emerging technologies all his life.
At age 25, with a bachelor’s degree in mathematics, he designed a numerically controlled machine built using semiconductor technology. By the age of 30, he had developed a computer system using small integrated circuits for banks. This was during the Cultural Revolution, when China was closed to the West, and Chinese banks were still using abacuses. “We wanted to break through those barriers. We spent three years building computers, building operating systems, and writing programs,” he says.
“Each of these experiences reinforced the central question that has guided my academic research ever since: How can we harness the new wave of information technology to generate meaningful benefits for society?”
Yuan believes that AI can complement human labor, but humans will need to adapt. “AI will not ‘take away’ jobs, but people who know how to use AI will replace those who don’t,” he says.
His most-cited paper, with a whopping 1182 citations at the time of writing, was published in 1995 on “Fuzzy Decision Tree Induction,” a technique used in machine learning to classify inaccurate or ambiguous human information.
Thirty years later, Ewan is still publishing furiously. His latest research considers how AI can be used to improve research and services, including using AI to support risk analysis and AI-powered social media marketing. He also conducts research on AI-assisted medicine to address medical issues in the elderly. Primary care physicians don’t have time to listen to their elderly patients for hours and can miss important information. “But ChatGPT is very patient,” Yuan says.
We asked Yuan about his career and his views on the role of AI in the workforce.
Looking back at your career trajectory, what are the key questions you have always considered in your work?
Throughout my career, I have been driven by a deep curiosity about how emerging information technologies can transform human lives and organizational practices.
When I had the opportunity to study for a PhD in the United States, I intentionally chose the then-new field of computer information systems. Because it allows us to explore not only the technical aspects of computing, but also its organizational and social implications.
Through decades of technological change, from early computing to the internet, mobile systems, and now AI, I have remained focused on understanding how innovation can be used thoughtfully, responsibly, and creatively to improve the way people work and live.
Why did you personally become interested in AI?
AI fascinates me because it is one of humanity’s most ambitious intellectual undertakings. It is an effort to design systems that emulate aspects of human cognition and can perform tasks once thought to require uniquely human intelligence. The possibility of building tools that can perceive, reason, and learn is both inspiring and humbling. My interest lies not only in the technology itself, but also in what it reveals about human ingenuity and our continued efforts to expand our capabilities through innovation.
My involvement with AI began early in its modern history. I developed a fuzzy logic rule induction algorithm for machine learning and built an expert system to support kidney transplant allocation. This experience showed me how computational reasoning can assist in making complex, high-stakes decisions.
We then evaluated the performance of neural networks for financial analysis and investigated how machine learning models can discover patterns beyond traditional statistical methods. Most recently, my research has focused on understanding how AI agents impact knowledge workers and how generative AI can be used to support qualitative data analysis.
Across these various stages, my interest in AI has remained consistent. I am fascinated by the ways in which AI can enhance human intelligence, expand problem-solving capabilities, and open new possibilities for research and practice.
How can AI assist humans rather than replace them?
AI is a human creation, and humans, not technology, ultimately decide how it is used. When I say “jobs will not be replaced by AI,” I mean that technology itself does not eliminate the jobs that humans do, by choosing how we use technology and by reorganizing jobs around technology. AI is a tool, not an independent entity. They do not have any agency or decision-making rights regarding the labor market.
Humans decide where AI is applied, how workflows are redesigned, and what new skills are valuable.
Here’s how to understand technology changes more accurately.
- Tasks, but not entire professions, are automated.
- Roles don’t disappear, they evolve.
- Workers who learn how to use new tools often replace those who don’t.
In this sense, AI does not “take away” jobs. Instead, people who know how to use AI will replace those who don’t. This pattern has been repeated throughout history, from the introduction of calculators to spreadsheets to the Internet. Each wave of technology has changed the nature of work, but it has also created new opportunities for those who have adapted.
What role do you think AI ideally plays in the workforce?
Ideally, AI should take over repetitive, time-consuming and analysis-intensive tasks, allowing people to focus on higher-order tasks such as creativity, judgment, empathy, and strategic thinking. When used well, AI is a partner that increases productivity, expands what individuals and organizations can accomplish, and opens up new opportunities for innovation. The goal is not to replace human intelligence, but to augment it.
What can AI offer researchers?
AI offers great potential to improve both the efficiency and quality of academic research. It helps researchers process large amounts of information, identify patterns, generate ideas, and explore new directions faster than ever before. These tools also accelerate literature reviews, support data analysis, and help scholars communicate research findings more effectively.
But the essence of research—curiosity, critical thinking, theoretical insight, and the pursuit of new knowledge—remains fundamentally human. AI can support our research, but it cannot replace the intellectual rigor, creativity, and ethical judgment that define academic research. What excites me most is the potential to combine human insights with AI-powered capabilities to push the boundaries of what research can achieve.
