Artificial intelligence (AI) has the potential to enhance every technology as it resembles enabling technologies like the combustion engine or electricity. Many people in this field believe AI is general purpose, with a multitude of applications across many different disciplines. We believe the nature of AI is interdisciplinary. In other words, the power of AI lies in augmenting its ability to accelerate research exponentially and the possibilities are endless.
As a result, demand for professionals who are hard-wired in AI technology knowledge but who also possess interdisciplinary perspectives and transferable skills is becoming increasingly important. This article explores the endeavor of nurturing an educational ecosystem to foster AI+X education in China via an interdisciplinary initiative.
China is fostering AI education in universities by strengthening the interdisciplinary links between AI and relevant fields, instead of merely offering a few core courses as a part of the CS discipline.
AI is committed to the realization of machine-borne intelligence. The appropriate utilization of AI to a variety of research fields is speeding up multiple digital revolutions, from shifting paradigms in health care, to education offered worldwide, to future cities made optimally efficient by autonomous vehicles. However, contemporary AI systems are good at specific predefined tasks and are unable to learn by themselves from data or from experience, intuitive reasoning, and adaptation. From the perspective of overcoming the limitations of existing AI, interdisciplinary scientific efforts are necessary to boost future research in this field. As a result, the next AI breakthroughs will be endeavors that draw upon neuroscience, physics, mathematics, electronic engineering, biology, linguistics, and psychology to deliver great theoretical, technological, and applicable innovations, address complex societal issues, reshape the national industrial system, and more.2,6,8
AI Undergraduate and Graduate Curricula
AI has become an undergraduate major at more than 300 universities in China as of March 2021, as approved by the Ministry of Education in 2019. Many Chinese universities established AI schools (such as Xidian, Nanjing University, and Xi’an Jiao-tong) and institutes (such as Zhejiang University, Peking University, and Tsinghua University) in recent years for research training, especially AI Ph.D. programs. Today, AI is the fastest-growing discipline at China’s universities. China is fostering AI education in universities by strengthening the interdisciplinary links between AI and relevant fields, instead of offering a few core courses as a part of the computer science discipline. For example, China’s top music university—Central Conservatory of Music—started to recruit students with the three-year Ph.D. program covering music and AI, and Southwest University of Political Science & Law opened a school of AI and law to equipped students with strong AI+ law knowledge and professional skills.
Since the fundamental goals of AI are to enable machines with human-like capabilities, such as sensing (for example, speech recognition, natural language understanding, computer vision), problem-solving (for example, search, optimization, and learning) and acting (for example, robotics and systems), the core AI courses in undergraduate and graduate curricula generally consist of computer science, mathematics, and statistics. In particular, AI ethics and responsibility to humankind are an important part of the courses since the long-term goal of keeping AI beneficial to human society is crucial.
AI+X Micro-Program
A micro-program consists of a set of micro-courses in a specified field. Micro-courses can help learners gain knowledge in small units in a short period of time. As a result, micro-courses provide potential opportunities for professionals to expand their competencies without leaving their current roles and are designed to keep their expertise up to date.
In April 2021, an AI+X micro-program was offered to 300 students outside the AI discipline by six top universities in east China—Shanghai Jiao Tong University, Fudan University and Tongji University in Shanghai, Zhejiang University in Zhe-jiang Province, Nanjing University in Jiangsu Province, and the University of Science and Technology of China in Anhui Province, and with some companies such as Huawei, Baidu, and SenseTime. Since an AI+X micro-program is expected to train students with a solid background in a thematic discipline (X) who need AI to tackle a specific scientific challenge, the AI+X micro-program currently allows the students from thematic discipline to register.
The accompanying table lists the curricula of the AI+X micro-program, which consists of more than 40 online courses in six categories (prerequisite course, AI fundamental compulsory course, module course, algorithmic practical course, interdisciplinary course, and summer camp course). Each course is taught in online SPOC (small private online course) to registered students for 11 weeks. Each course is scheduled to meet 1–2 hours a week. After finishing each course, an offline examination is given.
Table. The curricula of AI+X micro-program.
Each registered student is required to complete a total of at least 12 credits within 1–2 years to obtain a certificate signed together by the aforementioned universities. Moreover, these universities allow registered students to use AI+X online courses to count toward their degrees. That is, registered students who enroll in an AI+X micro-program may have those credits transferred to fulfill their major requirements.
Motivated by the mission of quality-first, with open and cooperative sharing, AI+X micro-program courses are expected to be available to the public in the near future.
AI+X Education Ecosystem
The foundation for a healthy AI educational ecosystem is built on AI+X skills training, textbooks, online courses, and practice platforms as well as the collaboration between universities, government, and industry.
Textbooks are essential for students as well as teachers. For the student, an effective textbook offers guidelines for what they can expect to learn. For the teacher, it provides objective reasons for why a particular topic should be taught and the educational goals it satisfies. In cooperation with more than 30 universities, China’s higher education press is publishing a series of AI textbooks that cover theoretical models, algorithms, technologies, AI ethics as well as AI+X interdisciplinary research.
Online courses allow students to learn from anywhere and at any time, which is more flexible, customized, and cost-effective than traditional education. Each course in the AI+X micro-program is required to be available online and some courses have been recognized as national-level, high-quality MOOCs.
The best way to learn AI is to practice. One cannot truly learn until and unless one truly gets some hands-on training for solving real problems. The training platform used in the AI+X micro-program is Wise Ocean, which provides a one-stop repository of resources to help AI+X curriculum learners better understand the promise and implications of domain-specific AI, such as machine-learning driven drug discovery (see the accompanying figure).
Figure. The architecture of Wise Ocean.
Wise Ocean, like MINIX, is not merely a teaching tool. Early versions of MINIX were created merely for educational purposes. Starting with MINIX 3, the primary aim of development shifted from education to the creation of a highly reliable and self-healing microkernel OS. The Wise Ocean platform would collect open source codes for plenty of AI+X interdisciplinary innovative research since registered students will finish their assigned projects. Therefore, Wise Ocean will evolve into a synergistic combination of research and education—a platform that can educate students (future innovators) to apply cutting-edge AI technologies to many industries.
Wise Ocean will evolve into a synergistic combination of research and education—a platform that can educate students (future innovators) to apply cutting-edge AI technologies to many industries.
In March 2020, China’s Ministry of Education, the National Development and Reform Commission, and the Ministry of Finance co-issued guidelines to urge universities to create interdisciplinary skill-cultivation systems to substantially improve the level of graduate education in AI and also encourage enterprises to ramp up investment to support the development of AI-related disciplines and high-level skills training. The AI+X micro-program sets up a collaborative innovation system via interactions with universities and industry for AI development. For example, companies provide their programming tools, industrial demands, and computing power to cultivate AI+X students.
Challenges and Conclusion
Most research fields increasingly encompass data analysis that requires computer science skills. The University of Illinois has designed a set of CS+X degree programs that allow students to pursue a flexible program of study incorporating a strong grounding in computer science with technical or professional training in the arts and sciences (such as CS+ Astronomy, CS+ Chemistry, and CS+ Economics). AI+X microprograms in China must practice online (MOOC or SPOC), resulting in several challenges:
- Qualified textbooks as well as the corresponding online courses to guide students to better learn online courses.
- A flexible training platform consisting of data, model, teaching scenario, and industrial demands.
- Computing power for students to train their AI models online is difficult, but rising faster than ever before.
- Bridging the gap between AI+X interdisciplinary research to offer suitable AI+X teaching projects for students not from AI discipline.1,3,4
Accelerating the development of a new generation of AI is a key strategy for China, to boost developments in science and technology, to upgrade every industrial domain, and to increase overall productivity.5,7 Building up an AI ecosystem is very important to nurture more AI+X talents. In a healthy AI ecosystem, each participant across multiple industries and domains can find various ways to thrive.
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