By Hsiao Hsi-hue 蕭錫惠
Artificial intelligence (AI) has transformed modern industrial operations and knowledge production models, but higher education in Taiwan has been slow to respond. Since taking off in 2023, generative AI has become more than just a tool and is influencing entire knowledge structures. Entering this year, advancements in physical AI have seen the transition from virtual-world generation to real-world intervention, driving policy decisionmaking in automated manufacturing, smart logistics and robotic systems. At this technological turning point, university professors in Taiwan are facing a clear disconnect between knowledge and implementation levels. A survey indicates that while the share of university professors using AI is between 50 and 70 percent, their application mostly remains at the level of assistive tools for tasks such as literature review and data summarization, while broader structural transformation of curriculum design and research methods has yet to take place. Most teachers possess a basic understanding of AI but lack the ability to integrate it into their professional contexts. Additionally, the education system concentrates on preventing student plagiarism and ensuring academic integrity. This has compressed the positive application space for AI as an extension of capabilities. To break through this situation and enhance the international competitiveness of Taiwan’s higher education, several steps could be taken. First, the education system should reshape student evaluation mechanisms away from plagiarism prevention and toward coexistence with AI. This would reduce excessive anxiety over plagiarism and instead incorporate AI into learning evaluation criteria. Teachers should design tasks AI cannot complete alone, such as requiring students to submit chat histories showing repeated revisions with AI or increasing the proportion of oral exams and practical assessments. AI should be seen as an extension of abilities rather than a tool for cheating — transforming the framework that says “AI equals cheating.”
Next, universities should establish a “micro-credit” system to mitigate institutional lag. While AI technology evolves month by month, yearly curriculum adjustments lag behind. Schools should introduce flexible micro-courses, allowing teachers to offer short-term credit courses targeted at the latest AI advancements. At the same time, they should provide support by incorporating teachers’ contributions into faculty promotion and evaluation incentives. This would help keep the pace of educational change closer to that of modern technology. Last, schools should promote “upward” mentorships through cross-generational collaboration. Research shows that senior teachers tend to have lower levels of AI literacy. Young academics or teaching assistants proficient in AI tools could serve as “AI mentors” for senior professors, assisting them with integrating AI into traditional research methods. Through this exchange of experiences, universities could reduce delays in technological implementation and help senior academics become more familiar with new technology. Young academics could lead the adoption of AI tools for certain research projects or courses while senior professors provide domain knowledge, accelerating the flow of knowledge and skills between generations. While some industries have come to regard AI as a basic skill and necessity, higher education remains stuck debating whether to adopt it. More than just a technological gap, this is a watershed moment for generational competitiveness. Taiwan’s universities must reform their institutions and mindsets to redefine the value of higher education in the AI era. Hsiao Hsi-huei is a freelancer. Translated by Eddy Chang