原标题：
Computer Science at University 2.0: What the Future Holds and How We Can Shape It
1 Introduction
The 21st century ushers in an age of information where algorithmic analysis and manipulation influences social and economic activities in breadth and depth that the 20st century could never have imagined. Computer science, unlike Physics, aims to develop theories and algorithms that shape our world rather than explain it. As more and more fields are impacted and come to require computer science skills, education reform becomes increasingly necessary [1]. Computer science, as a discipline, has to advance to get ready for this new age focusing more on artificial intelligence (AI), diversity, sustainability, and so forth, so as to support the synergy of disciplines needed for solving today’s big problems.
For example, students in engineering have to be familiar with computer science skills around data science and machine learning such that a more digitally enhanced engineering can be achieved. Another example is the use of artificial intelligence rooted in laws of physics and chemistry to automatically discover candidates for smart materials – which reduces the time and costs of experimental validation of design candidates.
Thanks to the incredible achievements of computer science, we are ready for realizing the vision of a so-called University 2.0, where almost all fields, like engineering, finance, and the natural sciences can interact with each other to facilitate their evolution, to drive innovation, yet to keep their own sense of discipline. The I-X initiative of Imperial College London serves as a test bed for University 2.0. Specifically, three main projects, namely ‘digital twins’ of biological environments or industrial systems; virtual-real co-presence; and collaboration, AI, and machine learning systems are moon-shot ambitions of the I-X initiative to facilitate the oncoming revolution of many interdisciplinary subjects.
2 Computer Science 2.0 in University 2.0
2.1 Develop research programs that encourage collaboration across departments
Significance of Computer Science. The core theme of this paper is Computer Science 2.0 at University 2.0. First, what is computer science? It is not only about computing as a process and the explanation of the world, as physics or some of the life sciences might do. Computer Science also develops theories and algorithms that shape our world. At the same time, the computations are rooted in the physical world, and thus there is a really interesting tension here as well – seen for example in quantum computing and its information theory.
Then, what is Computer Science 2.0? In short, it is the fact that nowadays, computer science is at the center of almost all other fields, like engineering, finance, social science, and so on. Computer Science 2.0 is the foundation of University 2.0 that facilitates transdisciplinary education, research, and innovation.
Computer Science is Changing Education. Computer science 2.0 has huge implications on the structure of University 2.0, and we have to embed computer science competency in all the academic departments and faculties. The other driver here is the pace of digital innovation, which definitely shapes the 21st century and its impact and the acceleration of this change. For example, Google and TikTok have changed the world a lot in only a few years.
Therefore, computer science today has become the key driver in education. In the United Kingdom, social science, history and language programs are being downsized in many universities, and almost every student has to become computing literate. This gives Computer Science more responsibility as its impact on life sciences, social sciences and their supportive policy making by regulators and governments is ever increasing.
An education in computing and computer science should give students of all subjects the tools to make the world better.
2.2 Computer Science 2.0 and Other Fields
Computer Science 2.0 is almost everywhere in the university. Specifically,
(1) Law & Regulation. Digital technology has a rich relationship with law and the responsibility that comes from using legal technology. On the regulatory side, the Personal Information Protection Law in China has come into force on the first of November this year. Regulation of AI in the European Union (EU) might see some laws that constrain certain use cases within the EU by 2025. Hence, there is a very tight connection between computing and regulatory and legal efforts around digital technology and its impact.
(2) Engineering. The digitalization of engineering is underway. For example, at Imperial College London, virtual geological expeditions replaced planned trips to mines in South America during the pandemic. AI supports the design of smart materials, reducing costs, and also may discover materials that traditional methods might never discover. The important question is what is the essential computing that all engineers should learn at university to support their professional careers and career development.
(3) Finance & Economics. The bank and consumer market has been transformed by digitization. Traditional banks are facilitating apps that give people a rich user experience, and a much speedier way of interacting with financial instruments and transactions. Digital platforms, such as Amazon and Baidu, may become too powerful. Hence, China, the EU and the US are considering how to balance economic freedom and the public good in regulating such platforms.
(4) Natural Science. Novel structures and materials will be vital for realizing future computing paradigms that go beyond conventional models and hardware for
computation. The natural sciences will play a key role in this. An example of structure is application-specific hardware for deep learning. At the same time, some computing materials can also facilitate advances in natural science. For example, Hayles’ proof of Kepler’s conjecture leverages automatic theorem proving that basically completely operationalizes an incredibly complex mathematical proof and then verifies it a large set of non-linear inequalities.
(5) Life Science & Medicine is highly regulated fields. However, there’s also a tremendous impact potential for computing in such a highly regulated space. AI for health, such as the AI for Health Doctor Training Center at Imperial College London, will definitely lead to better patient experience and outcomes. However, any direct patient intervention is highly regulated. Therefore, much more effort should be taken in this case to realize innovations to reach the patients and benefiting them. Recently, medical imaging has made huge advances, which might soon lead to a change of workflow and the effectiveness in clinical diagnostics.
(6) Social Sciences. In the past, when people thought of social sciences, they might have had an image of someone sitting in a chair, thinking about theories and possibly conducting some experiments to validate them in the field. However, recent advancements in computer science have affected social sciences a lot. For example, the advances in natural language processing have really transformed the discipline of Computational Linguistics. This may jeopardize these established academic disciplines but also offers opportunities for rejuvenating them.
Therefore, we should take care that, as computing goes forward in the University 2.0, all sciences have their proper place and work well together with technologically driven disciplines such as computing. For this, it is very important that data-driven methodologies are used responsibly and competently – to ensure that findings are scientifically sound. Generally speaking, Computer Science 2.0 should take care of many significant factors like privacy, policy and regulation, sustainability, inclusive education and so on, which help University 2.0 to improve collaboration, education outcomes, and socially responsible innovation and entrepreneurship.
2.3 Develop research programs that encourage collaboration across departments
The I-X initiative is a strategic initiative by Imperial College London to put into practice the ideas surrounding Computer Science 2.0. It aims to work across disciplines in integrated teams, merging together research and education. It strives for deep and impactful collaboration with industry and digital technology users. Cohabitation of industry partners, academics and students in the same space will be a central aspect of this college.
Here are three example ambitions from the I-X initiative.①Building ‘digital twins’ of biological environmental or industrial systems, which can help the collaboration between computer science and biology. ②Developing new techniques for virtual-real co-presence and collaboration, which helps humans to collaborate on almost all fields virtually. ③Building AI and machine learning systems that understand the real world, which may help many fields to achieve automation and intelligent inference.
In summary, the I-X initiative is designed to have a broad focus around everything digital, which might be considered as University 2.0 in the future.
3 Conclusion
This paper introduces Computer Science 2.0 and its place within the University 2.0. The key message is that, nowadays, methods and skills from computer science play a significant role among almost all fields, often seemingly invisible but indispensable. For example, AI can support engineering automation, leading to Engineering 2.0 and can help discover healthier foods, leading to Life Sciences 2.0. This digitization of the sciences and engineering produces new forms of collaboration, education outcomes, and career models in University 2.0, where academics work more across the boundaries of disciplines and may complete secondments in industry or create their own start-ups to innovate.
University 2.0 may look like Alexander von Humboldt’s vision of what Universities should look like, to quote from his letter to the then Prussian King: “There are undeniably certain kinds of knowledge that must be of a general nature and, more importantly, a certain cultivation of the mind and character that nobody can afford to be without. People obviously cannot be good craftworkers, merchants, soldiers or businessmen unless, regardless of their occupation, they are good, upstanding and – according to their condition – well-informed human beings and citizens. If this basis is laid through schooling, vocational skills are easily acquired later on, and a person is always free to move from one occupation to another, as so often happens in life.” Profiles of educators: Wilhelm von Humboldt (1767–1835) by Karl-Heinz Günther (1988) [2].
Computer Science 2.0 and University 2.0 should be seen in this tradition of educating socially responsible citizens and to now equip them with computer science skills that can make the world a better place.
References
[1] Yao A, Yin X, Liu Y, et al. Perspectives from the second Global Forum on Development of Computer Science[J]. Science China Information Sciences, 2022, 65(7).
[2] Günther K. Profiles of educators: Wilhelm von Humboldt (1767–1835)[J]. Prospects, 1988, 18(1): 127-136.
Michael Huth is Head of Department Computing at Imperial College London and Co-founder and Chief Research Officer at Xayn, a private search and discovery browser with personalized AI that users control. His research focuses on Cybersecurity, Mathematical Modelling, Cryptography, as well as Security and Privacy in Machine Learning.
Professor Huth studied Mathematics at the Technical University of Darmstadt (Germany), received his PhD from the Tulane University of Louisiana (USA), and held positions in the US, the UK, and Germany before joining Imperial College London in 2001. Since 2020, he provides leadership across Education, Research, Transfer, and Innovation to prepare his department for the future of Computing in 2030+.
• Michael Huth is with Department of Computing, Imperial College London, London SW7 2AZ, UK. E-mail: m.huth@imperial.ac.uk.
引文格式：Michael Huth. Computer Science at University 2.0: What the Future Holds and How We Can Shape It[J].计算机教育,2022(12):178-181.
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