Phil S. Yang职业教育国际研讨会2020-11-26
In recent years, I made two important decisions and put them in in action. One was my investment and participation in China’s TVET, Technical and Vocational Education and Training. With some investment, I am now International President of Jilin Vocational & Institute of Technology, Jilin Chengshi Zhiye jishu shueyuan, in Changchun. The other was my investment and participation in artificial intelligence. With focus on Vision AI, I am CEO of Mega AI Lab, Seoul, Korea. This opportunity provided for me by <2020 Belt and Road International Conference on TVET> is not only a great honor to me but also a great chance for me to combine what I did in the past and what I will do in the present and future. I would like to express my gratitude for speech invitation to the leaders and staffs of the conference and its participants. This conference is, in my opinion, to integrate the advance of the digital economy, the improvement of technical and vocational talent, and the global cooperation of TVET on the basis of China’s initiatives of Belt and Road. In 2017, I was lucky enough to be invited by the General Executive Bureau of Silk-Road Industry and Finance International Alliance to write about my expert opinion about China’s Initiatives of Belt and Road, in Chinese. Well, my Chinese was, still is not good enough to write a professional paper about such a serious topic. In order to understand Belt and Road in depth, however, I decided to do it with the assistance of my students at Tsinghua University in Beijing. When it was published, I was surprised to find my name along with Premier Li Keqiang and Mr. Chen Yuan and others in the list of contents. Indeed, it was a great honor to me. Let me briefly share with you what I wrote under the title of “One Belt and One Road Perceived from Chinese Dream to Global Dream.” Belt and Road Initiatives and TVET Five hundred years ago, the Age of Exploration opened up a version 1.0 of globalization. Three hundred years later, a version 2.0 of globalization began, which could be called the age of imperialism. Finally, in the 21st century, the “Belt and Road” initiatives are expected to be the beginning of a version 3.0 of globalization. Looking back at these three versions of globalization, globalization in the age of Exploration and the era of imperialism has not only brought historical progress to mankind but also conflict and inequality to us. However, this is not and more importantly, should not be the case with the Road and Belt Initiatives. The Initiatives should be a powerful driving force for the realization of a global community with a shared future for mankind. The “Belt and Road” initiatives are based on the principles of consultation, joint construction, and sharing. The age of Exploration was initiated by the greed for gold and other precious metals. The imperialist era that followed was based on the greed for territorial expansion. In effect, the “Belt and Road” initiatives were able to end the unilateral domination of the world by Western powers. It tried to systematically solve that problem with the achievements of science and technology, such as the Internet in the early stage and Artificial Intelligence in the later stage, as the background and the vision of a globalized future for mankind. Compared with the past era of Exploration and imperialism, the Belt and Road Initiatives are considered as sincere efforts to discover the historical significance of mankind. Demonstrating such efforts in a sincere manner will eventually eliminate the West’s suspicion of the “Belt and Road” initiatives on the one hand, and the Asian and African countries’ fear of the “Belt and Road” strategy on the other. As a result, the Belt and Road Initiatives will rapidly encompass both East and West to integrate the whole world. In terms of theory, the concept and strategy of the Belt and Road Initiatives may be understood as following the traditions of Karl Marx and Mao Zedong which place great emphasis on equality and communication. On the contrary, the age of Exploration and the era of imperialism were marked by inequality and contradiction. In the age of Exploration, there existed a social gap between the rich and the poor as well as the inequality between countries. In effect, the age of imperialism furthered such an inequality. Of course, there were resistance and struggle against imperialism. Eventually, the world could not escape division and chaos. The “One Belt, One Road” initiatives, however, pursue equality and communication and seek for a world community in which wealth and knowledge are equally distributed. The “Belt and Road” cosmopolitanism advocated by Chinese President Xi Jinping forms part of the further development of Marx’s and Engel’s internationalism. While putting aside differences in production relations, eliminating internal struggles and oppositions in society, and ultimately advancing a globalization 3.0 with a consensus that transcends social and national boundaries, the “Belt and Road” initiatives pursue environmentalism to which Marx’s and Mao’s socialist tradition failed to pay serious attention. Today, the survival of mankind has reached the point where it is indeed inseparable from environmental problems; as a matter of fact, some environmental problems have already reached a very serious point of crisis. To a certain extent, the nature of environmentalism is, thus, not an option for the “Belt and Road” initiative, but a necessary duty of it. President Xi’s initiatives of Belt and Road inherited the traditional Chinese culture and wisdom. Confucius once advocated “harmony without difference”, Heerbutong, emphasizing diversity that is coordinated but not uniformity that is imposed and forced. In effect, the initiatives lead people of different nationalities, different countries, and different ideas to respect each other’s diversity, only to form a global community with a shared future based on the principles of mutual consultation, joint construction and sharing. The Belt and Road Initiatives are, to be sure, a combination of Marxist tradition and traditional Chinese wisdom. In this context, the Belt and Road Initiatives are to rise from the “Chinese Dream”, Zhongguomeng, to the “World Dream,” Shijiemeng. It is not simply the Chinese people who pursue and enjoy the fruits of such a development, but the people all over the world are pursuing and sharing those of the Initiatives. As a matter of fact, the past, present and future are closely connected. To achieve such a shared dream, other countries and people need to abandon their doubts about the Belt and Road Initiatives and join together to promote them together with the Chinese people. Therefore, the Belt and Road Initiatives should transcend a simple concept of economic exchange; they should be realized through comprehensive exchanges such as cultural and educational exchange, in particular the exchange and cooperation of TVET in the Belt and Road network. Even though China witnessed its long history of TVET, it waited a while for its institutionalization. Today, the government pays more serious attention to it. Not only in China but also in the whole world, including Korea, jobs have become a critical issue of society; the education and training for jobs have been especially important to young people. In the case of China, two challenges emerge to TVET. One is quality over quantity. The other is internationalization. In this context, teaching and training artificial intelligence become crucial to the quality of TVET; international exchange and cooperation in the Belt and Road network are not only important to the Belt and Road Initiatives themselves, as pointed out before, but also to the upgrading the quality of each TVET institution in China. Now let’s turn to what artificial intelligence in general, deep learning in particular is and how it is immersed into the pedagogy of TVET. Artificial Intelligence and Deep Learning Every company will be an artificial intelligence company. When? I think it will be within 10 years in China, much faster than in other countries. What is artificial intelligence? I would like to tell you about the history of artificial intelligence, that is., AI. In 1956, a number of researchers and professors got together at an American university called Dartmouth College, one of the prestigious Ivy League universities, to which my daughter went. They discussed the possibility that machine could think like human beings, which was called as artificial, not real, intelligence. Since then, there have been ups and downs of that technology. In history of AI, the year of 2012 was important as much as that of 1956. Two great events occurred. On the software side, what is called deep learning was innovated by a number of Canadian researchers; they coded computer programs working like human brain. Like the neural network of human brain, computers learn and think by themselves on the basis of data. That software program is called algorithm. On the other hand, new process chips were manufactured to manipulate graphic data in a massive volume, which is called GPU, graphic process unit. This innovation entailed a large capacity of computing power which in turn requires that of electricity as well as a large amount of capital investment. These new trends merged together which brought about a new technology of deep learning, a subset of machine learning which forms part of artificial intelligence. In 2016, the world was surprised to witness AI beat Lee Sedol in a five-game match of Go. Although it lost to Lee Sedol in the fourth game, Lee resigned in the final game, giving a final score of four games to one in favor of AlphaGo, an AI computer program. The next year, AlphaGo beat Ke Jie, the number one ranked player in the world at the time, in a three-game match. Since then, the self-taught AlphaGo Zero achieved a 100–0 victory against the early competitive version of AlphaGo, and its successor AlphaZero is currently perceived as the world’s top player in Go. It was a shocking event. However, the Chinese leaders and businessmen did not just watch it but they took immediate action. In 2017, the government began to encourage venture capitalists to make investment in order to achieve the new goal of making China as Number One AI Country in the world. With more data and computing power, Chinese engineers and businessmen took advantage of the recent advance of deep learning technology, which mimic human brain’s neural network. Like the human cognitive system, deep learning is composed of voice AI, vision AI, and
language AI. In general, people call voice AI as voice bot or chatbot, vision AI as computer vision, and finally language AI as natural language processing, that is NLP. Even before the emergence of deep learning in 2012, efforts were made to develop voice AI like chatbots, which failed to monetize to a great extent. It was vision AI that made money due to its diverse applications, such as autonomous driving, security, safety, agricultural drone, and so many applications. Because Chinese people have, indeed for a long period of time, been engaged in digital life, especially through the use of smartphones, China had a competitive advantage of big data against any other country, including United States. This means the great potential for China to be Number One AI country in the world; as a matter of fact, in some fields of AI, such as vision AI, China has already surpassed America which remains Number One in many areas of AI yet.
In particular, Shenzhen will become, or has already become, one of the major centers for AI technology. Interestingly enough, the city has everything from sensor suppliers, injection-mold engineers, small-batch electronics factories and so on. Some people now do not say “made in China” but rather “made in Shenzhen.” More importantly, it has the unparalleled flexibility of the supply chains and the abundant pipelines of skilled field engineers who can make prototypes of new devices and build them at scale. To me, it is the city’s culture that makes it a true crown for hardware and a new Chinese Silicon Valley for software. For example, a week of Shenzhen amounts to a month of America. While Zhongguancun in Beijing is now competing with Silicon Valley in the United States, Shenzhen will come to compete with it in a near future due to the nature of AI technology in general, deep learning in particular, which entail both software and hardware power. In this context, it is indeed meaningful that today’s conference is held in Shenzhen, especially with topic of AI education and training for TVET students.
As Li Kaifu, one of the leading AI experts points out, it is very unlikely to see another round of technology breakthrough in the field of deep learning, which means that there exist no chances for deep learning to have such a major achievement or advance in a near future as that of 2012. In effect, the quality of AI algorithms for deep learning depends on more a volume of data than a novelty of proprietary research. In this context, more middle-level engineers are needed than elite engineers with Ph.D. or Master’s degree; with strong computing power and humongous Big data, they encode more powerful algorithms than elite AI experts, if the latter cannot afford to possess computer power and data volume as much as the former.
AI Education for TVET
The unique situation of current AI technology leads us to find a way how TVET nurtures AI talent. First of all, there are great demands for middle-level AI talent not only in China but also in other countries; the more AI deployment, the more field AI engineers. As pointed out earlier, it is not difficult for those who finish TVET to create novel AI algorithms which have commercial value. For the students of TVET, learning AI-legacy hybrid technology is more important and useful than learning its state-of-the-art knowledge and skills, especially for their employment. Here, a legacy technology is defined as an old technology or application program that is yet still in use but also is paving the way for the standards that will follow it; in particular, in computing, a legacy system refers to software or hardware that has been superseded but is difficult to replace because of its wide use. On the other hand, a hybrid is a mixture of two different things, resulting in something that has a little bit of both.
In the real world, such disruptive technology as deep learning AI is not rapidly adopted by companies because of its costs and human bottleneck in human. A combination of AI and traditional IT is a natural course of AI adoption for the companies in the real world. As a result, much more demands have emerged for the AI-legacy hybrid technology than for the state-of-the-art AI technology which is considered as important in the research laboratory. Finally, as pointed out at the beginning, every company will be an AI company whatever industry it belongs to. That means more and more jobs will be available for TVET students who learn AI technology.
Of course, the TVET institutes have a challenge to overcome. Above all, teachers who are able to teach AI are not enough in quantity for TVET. This is also true for universities, including Tsinghua University in Beijing. At today’s conference, I would like to suggest that a collective effort be made to develop teaching curriculum and material for the AI education of TVET students. Now that due to the corona virus, virtual education becomes popular; as a result, video and virtual material become necessary and cheap for the AI education of TVET in the form of collective teaching. Once again, I would emphasize that the content of TVET education should focus on the AI-legacy hybrid technology.
The students of TVET will be able to have the easy access to high-paid employment by taking advantage of their AI knowledge and skills. As more companies need more middle-level AI engineers who are not necessarily either Ph.D. or graduate of four-years colleges, the students of TVET have more chances to have employment especially due to their familiarity with the industrial field. In this context, combined with the tradition of field-focused learning, the TVET students develop their AI knowledge and skills that the real world and their employers desperately need. From my observation as university professors in Korea, China, and the US, the knowledge and skills learned from the four-year universities tend to have a distance from the real world, which is not a matter of good or bad things. It is just the division of labor between university education and TVET.
In the meantime, the TVET institutes should be ready for teaching how to organize and manage start-ups. The digital economy facilitated by AI technology will require more startups than traditional IT economy. More applications are needed to apply AI technology to the real world. As I pointed out earlier, the proprietary algorithms which are responsible for running the main engine of deep learning will remain the same for a while; in the field of deep learning which possesses a lot of application solutions with commercial value, no technology breakthrough will occur in a near future. Now it is a time of big data and computing power that facilitate the development of AI technology in general, deep learning in particular, which will bring more jobs and business opportunities than any other subset of AI technology. As a result, this will bring about more business opportunities for startups. In order to help the students with startups, the school needs to provide incubation experience for them. Now that the Chinese TVET institutes fall short of incubation capabilities, they join together with other schools for collective efforts like those of collective curriculum and teaching materials as mentioned earlier.
In my opinion, the idea of collective efforts for TVET’s AI education may be extended to a global scale. That is also a way to achieve China’s Initiatives of Belt and Road in the realm of TVET. To be sure, the global cooperation of TVET may start with the collective efforts to teach AI technology in the Belt and Road network.
AI Education for Belt and Road
Now China forms part of AI G2 along with the United States, which means that China and United States are leading the AI technology of the world. The country has competitive edge over big data; due to its wealth, its computing power is also competitive. By taking advantage of those superior elements, middle-level engineers can have well-paid jobs and set up their own startups in China; the TVET institutes are, in effect, responsible for nurturing them. Inside of China, the TVET institutes make collective efforts to nurture them in order to fill up the gap between the future goals and the current capacities.
Because local data is more important than local algorithms, AI requires a higher degree of localization for globalization than internet services. Some algorithmic training can be transferred between different user bases, but it is not possible to substitute the local data of one country for those of another country. With regard to AI talent, the extent of localization is more demanding; as a result, more local engineers should be provided for each country. This is to lead us to realize the importance of global exchange and cooperation for the AI education and training of the TVET students. In order to put the agenda of global cooperation in the context of the Belt and Road Initiatives, that logic of idea may be simply extended to outside of China. Collective efforts across national boundaries will be made to develop and share the teaching curriculum and materials for the AI education and training of the TVET students. Now that it has abundant resources of AI talent and technology, China will play a leading role in the AI TEVET network. This will, to be sure, contribute to the advance of China’s Initiatives of Belt and Road, which will, in turn, facilitate the development of TVET in China. Through the global cooperation of TVET in the field of AI technology, other countries and their people will get rid of their prejudice, if any, against China’s Initiatives of Belt and Road. In particular, Asian and African countries will come to consider it as more friendly and positive. Thanks to the AI education and training in the Belt and Road network, the young generations of the world will have better life and higher income and as well more opportunity to understand each other regardless of their color of skin and language of speech. To be sure, the AI education and training for TVET students will not only improve the quality of China’s TVET system but also promote the globalization of it, which are its two great challenges today.
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