Professional skills for engineering the third industrial revolution


Course description

We are living in a period of unprecedented change with the survival of human civilization at stake. Within one generation, you will have to implement the 3rd industrial revolution to restore biosphere integrity and biogeochemical flows, and reverse climate and land-system change (Rifkin 2001; Steffen et al. 2015).


In addition, you will need to define what it means to be human and redefine freedom and democracy, debate the ethics of and introduce regulation on genetic engineering, artificial intelligence, data ownership, social media, and privacy. All while managing the tension of the geopolitical shift, taking care of the ageing population, and abandoning lost cities. Do you feel that you understand the world and are you ready?


As engineers, it is our responsibility and privilege to serve humanity through these greatest years of need. We built the unsustainable fossil fuel based centralized energy system, the automobile based transportation system, and telecommunication system of the 2nd industrial era, now it is time to build a renewable decentralized energy system, a shared autonomous transportation system, and a cyber-physical communication system of the 3rd era.


Any society that fails to convert within a generation will not only risk all our survival, but be outcompeted due to the productivity and conversion efficiency limit of the old systems. In this course, we will together look at the challenges, current systems and development, future visions and predictions from an engineer’s perspective, with an emphasis on mechanical engineering. The focus is on introducing facts, ideas, skills, and critical analysis methods not currently thought at the mechanical engineering department that will help you to successfully live and build the future.


To succeed you will need to understand how the world of today works, and develop professional and personal skills. According to studies conducted by Prof. Korte at three U.S. organizations—a global automobile manufacturing company, a manufacturer of computer components, and a government transportation agency—20-50% of newly graduated employees quit within 24 months, mainly due to factors related to the team they were placed in, such as relationships, collaboration, mentoring, acceptance, leadership, and assignment (Korte et al. 2015).


In this course, you will learn to collect information, critically examine claims, debunk myths and fake news, live healthier and happier, be successful, and make a difference. We will cover three themes—“A world of facts, challenges, and ideas”; “Personal health, happiness, and society”; and “Professional skills to success”. Together we will watch thought provoking talks and documentaries by visionary leaders and bright intellectuals (mostly with Chinese subtitles), identify, discuss, and examine claims by gathering, analyzing, and visualizing data.


Tutorials will also be given and Q&A sessions held. This course will give an introduction to many topics and highlight how they all are interconnected and essential to us engineers. The aim is to awaken your awareness and passion, so that you become ready to grow with the challenge of your generation.


我們生活在一個前所未有的變化時期,人類文明的生存受到威脅。在一世代,即你們,親愛的千禧一代,將不得不實施第三次工業革命,以恢復生物圈的整體性與生物地球化學之流動,以及扭轉氣候和陸地系統的變化(Rifkin 2001; Steffen et al。2015)。此外,你將需要定義身為人類的意義與重新定義自由和民主、辯論與介紹基因工程、人工智慧、數據所有權、社交媒體和隱私之倫理或規範。同時管理地緣政治轉變的緊張局勢,照顧人口老齡化,放棄失落的城市。你覺得你了解這個世界且準備好了嗎?

身為工程師,我們有責任和特權透過這些需求大量之歲月為人類做出貢獻。我們建立了不可永續,以化石燃料為主之集中能源系統、以汽車為主的交通系統,與第二此工業革命時代的電信系統。現在是時候該建立一個可再生分散能源系統、共享自治交通系統和第三次工業革命時期之網路實體通訊系統。 任何不能內轉變的社會,不僅會危及我們所有人的生存,在一世代還會因舊系統的生產率和轉換效率的限製而失去競爭力。在此課程中,我們會著重於機械工程,從工程師之角度一起看一切挑戰、現今之體系與發展、未來之願景與預測。本課程之將聚焦在介紹能幫助你們成功地建造未來以及在未來生存,但機械工程部門目前尚未考慮到的事實,想法,技能和關鍵分析方法。

為了達到此目標,你需要了解今天的世界如何運作,並發展專業與個人技能。根據Korte教授在三個美國組織(一家全球汽車製造公司,一家電腦零組件製造商與一家政府運輸機構)執行之研究,20-50%之新鮮人在24個 月內辭職,主要因素皆跟他們被配置之團隊有關,如人際關係,合作能力、指導、容忍度、領導立和指派任務。(Korte et al。2015)。


Course Objectives

Divided into three themes:

Theme 1 - “A world of facts, challenges, and ideas”

  1. Know the current world demographics
  2. Ability to use demographics to explain engineering needs
  3. Understand planetary boundaries and the current state
  4. Understand how the current economic system fails to distribute resources
  5. Be familiar with future visions and their implications, such as artificial intelligence

Theme 2 - “Personal health, happiness, and society”

  1. Understand how data and engineering enable a healthier life
  2. Know that social relationships gives a 50% increased likelihood of survival
  3. Be familiar with depression and mental health issues
  4. Know the optimal algorithm for finding a partner for life

Theme 3 - “Professional skills to success”

  1. Develop a custom of questioning claims to avoid “fake news”
  2. Be able to do basic analysis and interpretation of time series data
  3. Experience of collaborative and problem-based learning
  4. Understand that professional success depends on social skills
  5. Know that the culture of the workplace affect performance

Teaching Strategies

How this course is going to be taught

  • Lecture 15% 15%
  • Discussion 14% 14%
  • Group Project 40% 40%
  • Video/Music Appreciation 30% 30%

Course material

Mainly videos of talks given by visionary leaders and bright intellectuals and documentaries (see the references for a partial list). A few journal articles and books are also recommended (see the references).

Course outline
  1. What will our world look like?
  2. What does our world look like?
  3. How to check facts and give sources?
  4. How does the financial system work?
  5. Why does extremism flourish?
  6. How to live healthy?
  7. How to handle depression?
  8. How to choose happiness/fulfilment?
  9. How does the legal system work?
  10. How to stay connected and free?
  11. How to make sense of events?
  12. Planetary boundaries
  13. Why a third industrial revolution?
  14. How to succeed?
  15. How to solve our problems?
  16. How to make a difference?
  17. How to find the best partner?
  18. Why is surveillance your problem?
  1. Korte, R. et al. (Mis)Interpretations of Organizational Socialization: The Expectations and Experiences of Newcomers and Managers. Human Resource development quarterly, 26(2), 185-208, (2015). DOI: 10.1002/hrdq.21206
  2. Steffen, W. et al., 2015. Planetary boundaries: Guiding human development on a changing planet. Science, 347(6223), pp.1259855–1259855. Available at:
  3. Rifkin, J., 2011. The Third Industrial Revolution, Palgrave Macmillan.
  4. Werner, R., 2003. Princes of the Yen: Japan’s Central Bankers and the Transformation of the Economy, Routledge.
  5. Harari, Y.N., 2017. Homo deus: a brief history of tomorrow 1st English edt., Harper.
  6. Morris, I., 2011. Why the West Rules—for Now: The Patterns of History, and What They Reveal About the Future Reprint., Picador.
  7. O’Neil, C., 2016. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, Crown Random House. Available at:
  8. Raworth, K., 2017. Doughnut economics: seven ways to think like a 21st century economist, Chelsea Green Publishing.
  9. Pinker, S., 2018. Enlightenment now: the case for reason, science, humanism, and progress 1st Ed., Viking.
  10. Jordan, M.I., 2018. Artificial Intelligence — The Revolution Hasn’t Happened Yet. Medium. Available at:
  11. Purdy, M. & Daugherty, P., 2016. Why artificial intelligence is the future of growth, Available at:
  12. Holt-Lunstad, J., Smith, T.B. & Layton, J.B., 2010. Social Relationships and Mortality Risk: A Meta-analytic Review C. Brayne, ed. PLoS Medicine, 7(7), p. e1000316. Available at:
  13. Dalio, R., 2010. A Template for Understanding What’s Going On, New York City, New York, USA.
  14. Provost, F. & Fawcett, T., 2013. Data Science for Business 1st ed., Sebastopol, USA: O’Reilly Media, Inc. Available at:
  15. Good, P.I. & Hardin, J.W., 2006. Common Errors in Statistics (and How to Avoid Them), Hoboken, NJ, USA: John Wiley\& Sons, Inc. Available at:
  16. Wasserman, L., 2004. All of Statistics: A Concise Course in Statistical Inference, Springer.
  17. Abu-Mostafa, Y.S., Magdon-Ismail, M. & Lin, H.-T., 2012. Learning From Data, Available at:
  18. “97% Owned”, directed by Michael Oswald, produced by Mike Horwath, 2012,
  19. “Princes of the Yen”, directed by Michael Oswald, 2014,
  20. “The Spider’s Web: Britain’s Second Empire”, directed by Michael Oswald, produced by John Christensen, 2017,
  21. “Strawman – The Nature of The Cage”, directed by John K. Webster, 2015,
  22. “FOUR HORSEMEN”, directed by Ross Ashcroft, Renegade Inc., 2012,

Course policy

Every lecture, you will either get a tutorial and/or we will watch a few thought provocative videos related to the theme of the lecture, followed by a Q&A session. Then you will get a mini problem related to the topic and work in groups to solve it. You are expected to meet once with your group and work for 1-3 hours in between the lectures to prepare your solution. We discuss your solutions in class the next time. Most mini problems will consist of a claim presented in the video and you need to select a perspective, find quantitative data, analyze it, visualize your result, and either confirm or refute the claim.


This course is building on the pedagogics of collaborative learning and problem-based learning. Attendance 70% (Counted based on lecture attendance, number of presentations given, and number of committed lines in the GIT repository of the course.) Exam 30% (Exactly the same exam on world facts will be given in the beginning and at the end of the course, the grade is based solely on the score at the end. During the course, you will learn the facts that you answered wrongly in the beginning.) If you in the exam score 70% correct at the end of the course, have attended >90% of the lectures, have presented at least three times, and the other members of your group says that you have contributed actively to the work, then you are guaranteed a grade of 70.


If you in the exam score 85% correct at the end of the course, have attended all of the lectures, presented at least six times, and the other members of your group says that you have made major contributions to the work, then you are guaranteed a grade of 85. The precise grade is determined based on your individual commits to the GIT repository (70%) and your exam result (30%). If the number of attending students is so large that not everyone can present 6 times, then the requirement on the number of presentations will be decreased.