Universities must transform to ensure no one is left behind in the era of AI

By instilling a passion for innovation and interdisciplinary exploration, higher education can and must remain relevant, say Teruo Fujii and Joseph Aoun 

January 10, 2024
A transformer robot, symbolising artificial intelligence
Source: iStock

As leaders of two pre-eminent global universities, we find ourselves at the crossroads where academic tradition intersects with rapid digital innovation. We are fully aware that the transformative potential of artificial intelligence is poised to shape the future of what we teach and how we learn, but we are still straining to see exactly where that road could and should take us.

Educators today are in the difficult position of not fully knowing what the concrete outcomes of AI will be. But we know that we are responsible for educating students for a future of technological reinvention that will likewise demand personal reinvention. And to serve students in such a period of flux, it is paramount that we do not delay in reinventing higher education to prepare our students for this new era.

The universities we oversee – The University of Tokyo in Japan and Northeastern University in the US – are steeped in very different cultures, and our personal backgrounds are decidedly dissimilar, too. One of us has gravitated towards linguistics, driven by a deep interest in natural languages and formal modelling that resonates in the age of AI. The other’s academic expertise is anchored in a childhood fascination with the ocean, which has led to a career spanning naval architecture and microfluidics. But at a recent AI symposium in New York hosted by The University of Tokyo, we found that we are firmly united in the belief that the traditional paradigm of higher education must undergo a profound transformation.

We agree that universities across the world must nurture creativity and critical thinking, human-centric skills that will become even more valuable in a technologically advanced world. These literacies should be integrated with sound understanding of technology and data.

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Being a specialist in one academic area is no longer enough. Higher education must become more comprehensive, too. Students should be encouraged to explore diverse disciplines and merge their strengths, such as by combining STEM fields with humanities and social sciences.

At Northeastern, for instance, students are increasingly opting for “combined majors”, which integrate a wide variety of disciplines. At The University of Tokyo, interdisciplinary studies reflect a growing awareness of the interconnectedness of global issues. For example, the university’s “SPRING GX” programme allows doctoral students from any school to study humanities, business management, engineering, science and medicine to address the complex social challenges of green transformation.

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In addition, the “ivory tower” must finally be dismantled. Historically, the relationship between academia and industry has not necessarily been harmonious. Yet so much of what industry commercialises has its origins in university research. Generative AI and related technologies are no exception. It is critical that faculty keep a finger more closely on the pulse of technological industries in particular by participating more fully in the private sector. This collaborative spirit is essential for maintaining transparency, openness and ethical considerations in the development and deployment of AI technologies.

In a world where technology will play an ever-larger role, the value of real-life experiences will also grow. Students must acquire an idea of what machines can do, but must also be able to see what they, as individuals, can contribute. At Northeastern, students participate in “co-ops”: immersive internships lasting as long as six months. Through these experiences, they test their knowledge to see where their competences lie, as well as which areas they need to improve in.

The University of Tokyo also offers its students hands-on learning opportunities at a variety of locales – from remote villages to overseas corporate branches – to both cultivate empathy and provide practical experience. Through experience-based learning, students translate knowledge between novel contexts, which machines cannot do, learning to take risks and accept failure as part of the process.

Universities have a collective responsibility to ensure that no one is left behind as the AI revolution transforms the jobs market. We must accept that our responsibilities as educators do not end once a first-time graduate heads off into the jobs market or into another programme of study. It will become our duty to see individuals through the course of their professional lives, developing measures to reskill and upskill them throughout their careers. And in that continuum there will be considerable potential for start-ups to ignite or cutting-edge technology to be developed in university labs.

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Wherever we are in the world, it is clear that the AI revolution demands a higher education model that seamlessly integrates lifelong and online learning with in-person experiences. By instilling a passion for innovation, creativity and interdisciplinary exploration, we can ensure that higher education remains not just a means to a career but also to a deeper understanding of our world and to greater impact on it.

We are confident in the potential of higher education to shape this future by embracing an emphasis on customisation, flexibility and responsiveness to individual and societal needs. By embracing these principles, universities can not only survive, but can also thrive in the age of AI, contributing to the development of skilled and adaptable talent that can navigate the complexities of our evolving world.

Teruo Fujii is president of The University of Tokyo and Joseph E. Aoun is president of Northeastern University.

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Reader's comments (2)

Funny, for decades working in HE it seems thatI was under the illusion that creativity and critical thinking were at the heart of what I did but no suddenly this is something that must be nurtured in HE. As a STEM researcher I have had no wish or reason to talk with or collaborate with my respected colleagues in the humanities, and they in turn have seemed quite capable of getting on with their day-to-day business without my input so it is unclear why the "advent of AI" is going to bring about some need to mix oil and water. and the ivory towers that the authors are in a hurry to dismantle have had an invaluable roll in preventing the mediocre concerns of industry from polluting the longer-term needs of the academic enterprise. I fear the authors have misinterpreted the rush to embrace "generative AI" as a goldrush rather than than a rush towards iron pyrite. Happily students with a solid thorough understanding of the reality of computer science obtained by having both feet planted solidly in one discipline rather than adopting the intelectually undignified posture of being sub-divided across campus to accommodate the fad for "interdisciplinarity" will still be equipped to guide industry and academia away from such folly.
I would agree that the widespread adoption of generative AI has significant implications for HEIs. I am not sure if the suggestions here are a sufficient response. 'Co-op' learning and applied learning with industry and communities is a very long-established and common approach - especially amongst technological universities and universities of applied science. In itself these admirable practices will not address the issues of knowledge creation and textual production that underpin contemporary assessment practices. This is where the challenges are: in what it means to 'learn' and how to demonstrate and assess such learning; and what this then means to 'teach'. Fundamental issues for all levels of education. I do agree that a multidisciplinary approach is necessary: these are technological, social and ethical questions that are interconnected.

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