Are Engineers Better in Educating Human or Training Robots?

We are living in a fast changing world that requires the ability to quickly adapt to new knowledge and technology. However, the evolution of the education system is relatively slow and the majority of approaches still aim at the transfer of technical knowledge. In particular, education administration still focuses on the quality and quantity of content, using syllabus as the governing tool. This results in training based on pattern recognition similar to machine learning, producing employees equipped with specific skills whose objective is to look for jobs. It is also a trend that engineers are more interested in devoting attention and resources to research in Artificial Intelligence for training robots rather than humans. The competition between AI and technically trained humans becomes unavoidable. So, what is the problem with the current education system? On the other hand, with the help of AI training, how can educators take advantage of it and move education to a higher level with a human-centric approach? This talk will address the above questions based on recent experience.

Prof. Mansun Chan is currently serving as the Alex Wong Siu Wah Gigi Wong Fook Chi Professor of Engineering and Chair Professor of the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology (HKUST). He received his BSc in Electrical and Computer Engineering from the University of California, San Diego in 1991, and his PhD from the University of California, Berkeley in 1995. An expert in emerging semiconductor devices, he has published over 300 journal and 500 conference papers on the subject. Prof. Chan is widely recognized for his contributions to the development of the unified BSIM model for SPICE, adopted as the first industrial standard MOSFET model by most US companies and the Compact Model Council (CMC). He is also known for leading the research group that demonstrated the first Stacked CFET technology, considered the most promising option to extend CMOS scaling beyond the 2nm technology node. Actively engaged in entrepreneurship and educational initiatives, he has co-founded and invested in over 20 companies, with three successfully completing IPOs. He launched an animation-based MOOC class on semiconductor devices with over 25,000 students enrolled worldwide, and initiated electronic circuit construction training modules and competitions for primary and secondary school students, which have become a key outreach program for EDS. Prof. Chan has received the teaching award four times from the Engineering School of HKUST, the Michael Gale Medal for Teaching Excellence, and the IEEE EDS Education Award for pioneering innovative approaches in electronic engineering education. He is a Distinguished Lecturer and Fellow of IEEE.