Friday, February 5, 2021

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ai curriculum

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This is the abridged version of our popular programme, AI for Everyone (AI4E)®. In this video, you will learn about AI and its ...

in this chapter i'll be rec


00:16 first why AI? there's only one key difference that                        separates AI from traditional software or programs                                                                                                         next i'll explain how AI works to give you clues: AI is not magic most of us will have practiced developing AI on paper during our school days                                                                                                                                                                            lastly i'll share some existing applications of AI : in Singapore AI is used in our local community to make our life better but we might not have noticed their applications, so what's AI?                                                                                                                     

   00:49 AI is a system of software that can learn to improve itself without explicit instructions for humans; the ability to learn is a key differentiation factor between traditional software and AI.                                                                                                                                a traditional software system does not have the ability to learn to improve itself; whereas  AI has a variety of applications such as the ability to see, hear, speak, feel and move. AI uses computer visions to see and learn from its surroundings thereby enabling self-driving cars; AI uses natural language processing (NLP) to understand human speech and writing, thereby allowing it to understand and translate words for us. AI in the field of robotics uses a variety of sensors to feel and move .. there's a lot of interesting applications for AI but before we go deeper let me share with you some common terms that people use when they are talking about AI                                            01:52 when you read about AI you might come across different terms such as machine learning and deep learning -they are all related: again AI is used to describe any programs that can sense, reason, adapt, and act: even a simple rule-based system such as automatically turn off air conditioning when you leave the house is considered AI                                           

                                                                                                                                                                                                                                                                  02:13 machine learning is a subset of AI : it refers to a branch of AI that uses the algorithm to improve  its performance as IT IS exposed to more data : if your AI has the ability to  learn your usage behavior over time and adjust its setting  automatically  then it has moved from AI to machine  learning  ... deep learning is a subset of machine  learning which uses something called neural networks  to improve its performance over time with more data ... the design of neural networks is inspired by how our brain functions and requires large amounts of data to perform well                                                              most of the interesting applications of AI such as self-driving cars, google translate and amazon alexa are made possible by deep learning                                                                                                                 03:06 at this point you might be wondering how exactly AI works underneath the hood- is it some sort of magic?  that somehow possesses human cognitive  ability? The answer is no : in our early school days our math teachers will ask us to draw multiple points on graph paper followed by a straight line that best capture the relationship between all the points; subsequently when we have new data we can predict the value of this new data by checking it against the straight line that we have drawn . what we have gone through is called linear regression ; this is perhaps the simplest form of AI because whenever there are new data  points the best fit line will be adjusted                                                                                                                                                                                                                                                                                                    although  linear scientific mindsets sometimes  fulfill  our earlier definition of ai: the ability to learn  and improve itself  -there need to be as many different forms of ai as nature herself - the computer brain can now analyse far  more complex data than human brains can - see the shockwaves in china when humans were beaten at go - a game much more mathematical than chess -. Climate AI  involves integrating the diversity of nature exponential data  but apps could be as simple as linear. 04:13 So ai is not magic: it is just a fanciful way  of describing and using math to develop  self-learning algorithms                                                                     INTERMISSION                                                                                                         .4:24 now that we have understood why is ai 04:25 and how it works let's explore some 04:28 of ai applications used in our local 04:30 community in singapore 04:33 ai is really in our community without us 04:35 noticing 04:37 during the circuit breaker period in 04:38 singapore the government introduced a 04:40 robot at bishan america park 04:42 they remind people about social 04:44 distancing inside the campus of nus 04:47 there is a driverless charter bus to 04:49 ferry students and staff 04:51 across the campus ais singapore has also 04:54 developed 04:55 an open source ai solution that can 04:57 measure people's distance 04:59 from each other to ensure compliance 05:02 with social distancing 05:04 all these applications use computer 05:06 visions for the ai to make sense 05:08 of its surroundings and respond 05:10 accountingly 05:12 air is also used inside our local indoor 05:14 vegetables farms 05:16 based on the sensor's readings the ai 05:18 can automate certain processes 05:21 such as swatting of plants or putting 05:23 more fertilizer 05:24 to improve the farm's productivity 05:28 on the singapore government websites 05:30 they have introduced us gme chatbot 05:32 where citizens can ask questions and get 05:35 quick reply 05:37 ai singapore has also introduced our own 05:39 special text engine 05:40 to translate multiple languages in real 05:42 time 05:43 this is different from typical special 05:45 text applications 05:46 where they could only translate one 05:48 predetermined language to another both 05:52 applications use 05:53 natural language processing for the ar 05:55 to make sense of our speeches and taxes 05:57 and respond accountingly before we end 06:01 off this segment 06:02 let's watch an interesting demonstration 06:03 of ai singapore speech 06:19 woodland central there can you all have 06:21 yet come 06:22 that they also feel very loud 06:26 here's the recap of this chapter why is 06:28 ai 06:29 ai is any system or software that can 06:32 learn to improve itself with more data 06:35 how does air work air is not magic it is 06:38 just math 06:39 even a simple linear equation is 06:42 considered ai 06:44 what are the common applications of ai 06:46 ai is 06:47 all around us without us noticing that 06:50 make our life better 06:51 and more convenient given the 06:53 understanding of air now 06:55 you might be wondering what are the 06:56 different types of ai 06:58 i will share more review in the next 06:59 chapter of this series welcome to 07:02 chapter 2 07:03 of ai for everyone multilingual version 07:06 this is the second of three chapters in 07:08 this short series 07:09 in this chapter i'll be covering the 07:12 following key concepts 07:13 first i'll describe the common types of 07:16 machine learning 07:17 recall that machine learning is subset 07:18 of ai and although there are many 07:20 different applications of machine 07:22 learning 07:23 most of them fall under just two types 07:26 next i'll explain the key differences 07:29 for each type of 07:30 machine learning the key difference that 07:32 separate the two common types of ml 07:34 lies within the data available lastly 07:38 i will share the main commercial 07:40 applications of each type of ml 07:42 there are two types of machine learning 07:44 supervised learning 07:45 and unsupervised learning our first talk 07:48 about supervised learning 07:50 the best way to understand supervised 07:52 learning is to imagine teaching a child 07:54 how to solve a math problem you can 07:56 teach 07:57 by giving multiple examples of problem 07:59 and a child will learn 08:01 by making and creating his or her 08:02 mistakes 08:04 eventually he or she will learn to solve 08:06 the problems on their own 08:08 it is the same concept for machine 08:10 learning you will provide data for the 08:12 ai to learn 08:13 the data should contain the right answer 08:15 for each task 08:17 if the ai makes a mistake you will 08:18 penalize the ai 08:20 it will then seek to improve itself by 08:22 updating its algorithm 08:23 and eventually you'll learn how to do 08:26 the task 08:27 essentially in supervised learning you 08:30 want the ai to learn to do a task query 08:32 by providing multiple examples counting 08:35 of applications that survivally can be 08:37 useful 08:39 the first type of survival learning is 08:41 classification 08:43 classification is applied whenever the 08:45 task covers answering questions 08:47 that involve yes or no these are that 08:50 the most common application of 08:52 classification is image classification 08:55 or separating images into their 08:57 respective categories 08:59 for instance if you have a question of 09:01 dog and cat pictures 09:02 you can train an ai to automatically 09:04 recognize the animal 09:06 and separate the images into their 09:08 respective folders 09:10 other common applications of 09:11 classification include 09:13 will existing customers extend their 09:15 contracts with us 09:17 the ai can highlight potential customers 09:19 who will not be renewing their contracts 09:21 and therefore allow suicide to follow up 09:24 such as 09:25 offering regular contract discount 09:28 does this review contain a positive or 09:31 negative sentiment 09:32 the ai can detect the mood of the 09:34 consumer based on their reviews 09:36 and provide input to the marketing 09:38 department on how consumers 09:40 are reacting to their products or 09:42 services 09:43 is this email spam the ai can identify 09:46 spam emails 09:47 and move them to the junk folder in 09:50 summary 09:51 classification is used when outcome 09:53 involves a label 09:55 or category the second type of survival 09:57 screening 09:58 is regression regression is applied 10:01 whenever the task covers answering 10:02 questions 10:03 that involves continuous value such as 10:06 the dollar amount of an item 10:08 the most common application of 10:09 regression is price prediction 10:12 for instance if you are buying a hdb 10:14 apartment and you would like to know 10:16 its fair market value it can train ai 10:19 to predict the price given the 10:21 characteristics of the hdb apartment 10:23 such as its total floor area and 10:25 location 10:27 other common applications of regression 10:29 include when will the next bus arrive 10:32 the ai can evaluate the distance between 10:34 the bus to your location 10:35 and the traffic conditions to predict 10:37 the arrival time of the bus 10:40 how likely is it going to rain tomorrow 10:42 the ai can learn 10:43 how to this weather patterns can affect 10:45 tomorrow weather's conditions 10:48 what are the sales numbers for next 10:49 quarter the ai can read through news 10:52 and internet emails to predict how well 10:53 the company might perform in this 10:55 quarter 10:56 in summary regression is used when the 10:59 outcome 10:59 involves a continuous value the next 11:02 common type of machine learning is 11:03 unsupervised learning if you recall 11:06 survive learning is like teaching a 11:08 child 11:09 how to solve a math problem by using 11:10 multiple examples 11:12 there is a correct answer which the 11:14 child can learn from 11:16 it is different for unsupervised 11:18 learning 11:19 there is no correct or right way of 11:20 solving the task the ai will have to 11:23 figure it out 11:24 imagine you have a basket of toys and 11:26 you ask the kid to separate 11:28 similar ones into groups at first 11:31 he will play the toys randomly but 11:33 eventually he will find his own way 11:35 to best group similar items together 11:38 there is no quiet way 11:39 to group the toys together it'll be 11:42 dependent on what your child thinks 11:44 is the right approach sometimes the 11:46 result might be unexpected 11:49 it is the same concept for unsupervised 11:51 learning you provide the data 11:53 to the ai and you'll learn the best way 11:55 to group the data together 11:57 there is no right answer on how it 12:00 should be done 12:01 the ai will figure it out on its own 12:04 therefore 12:05 the learning is unsupervised essentially 12:08 for unsupervised learning you want the 12:10 ai to find similar data 12:12 and group them together so what 12:14 applications can 12:15 unsurprisingly be used for the most 12:18 common type of unsurvived scenario 12:20 is grouping grouping is a machine 12:22 learning technique that clusters data 12:24 together 12:24 based on their similarities for example 12:28 you have a collection of shapes you can 12:30 train an ai to group similar shapes 12:32 together 12:34 in this example the ai might learn to 12:36 group all objects 12:37 with four corners together and hence the 12:39 rectangle is grouped together with 12:41 squares 12:42 other common applications of 12:44 unsupervised learning include 12:46 customers orientation the ai can 12:49 identify 12:50 common characteristics among customers 12:52 and group them together 12:54 this way we can create targeted 12:56 marketing message to 12:57 each groups for better results determine 13:00 similar product types 13:02 this use case is the same as customer 13:04 segmentation 13:05 but instead of people the ai is now 13:08 grouping similar products 13:10 recommendation engines the ai can 13:13 attempt to recommend new products 13:14 based on the details provided during 13:16 registration 13:18 for instance if other people in their 13:20 30s 13:21 like to listen to classical music the ai 13:23 might recommend classical music to you 13:25 if your profile matched theirs in 13:28 summary 13:29 clustering or unsurprisingly is used 13:32 when you want to group similar data 13:34 together here's the recap of this 13:36 chapter 13:37 there are two common types of machine 13:38 learning supervised 13:40 and unsupervised learnings suffice 13:43 learning requires you to provide answers 13:45 to train the am order unsurvivaling 13:48 doesn't require you to provide answers 13:51 to train the air model 13:53 survey setting is used when you want to 13:55 identify which category the data point 13:56 belongs to 13:58 such as whether it's a spam email or 14:00 non-spam email 14:01 or when you want to predict value of 14:03 something such as the received price of 14:05 your car 14:06 unsurvising is used when you want to 14:09 group similar data together 14:10 such as customers with similar purchase 14:13 behavior 14:15 given the multiple applications of 14:16 machine learning you might be wondering 14:18 if it can replace our jobs 14:20 i will share with you more in the next 14:22 and final chapter of this series 14:24 see you there welcome to chapter 3 of ar 14:28 for everyone multilingual version 14:31 this is the last of three chapters in 14:33 this short series 14:34 in this last chapter i'll be covering 14:36 the following key concepts 14:38 first given the self-learning ability 14:41 and vast 14:41 applications of ai while ai replaced our 14:44 jobs 14:45 next i will list some resources 14:47 available to get you started 14:48 in ai most of the resources are free and 14:51 online 14:52 which means you can learn them at your 14:54 own pace 14:55 lastly i will share some of the career 14:57 opportunities in ai 14:59 the good news is that not all of the 15:01 roles require postgraduate 15:02 qualifications 15:04 i would like to share with you an 15:05 interesting story to answer the question 15:07 of whether ai will replace our jobs 15:09 in 2018 a company developed an ai 15:12 to review non-disclosure agreements or 15:15 ndas 15:16 to test the performance of the ar model 15:19 the company challenged a group of top 15:21 corporate lawyers in u.s on reviewing 15:23 ndas 15:24 the results the air is more accurate and 15:27 faster than the lawyers 15:29 the investments formula lawyers are 15:31 interesting 15:32 instead of feeling threatened they are 15:34 excited by the ai 15:36 why weaving ndas is usually boring and 15:39 low 15:40 value activity one of the lawyers 15:42 thought 15:43 that the ai will be useful as it allows 15:45 lawyers to focus on more complex 15:47 projects 15:48 what does she mean by that let me 15:50 illustrate imagine you are the person at 15:52 the center 15:53 your job is made of many different tasks 15:56 some are simple 15:57 like doing inventory stock decay and 15:59 some are complex 16:00 like negotiating with suppliers if an ai 16:04 was developed to take over some of the 16:05 simple 16:06 boring tasks what will you do well you 16:09 can pass those tasks over to the ai 16:12 with the additional time on hand you can 16:14 then take on 16:15 more complex and higher order tasks this 16:18 way 16:19 you'll learn new skills create new 16:20 values and hopefully get pay raise 16:23 another interesting response from a 16:25 lawyer is he believes that the future of 16:26 law is 16:27 human and computer versus human and 16:30 computer 16:31 what does it mean by that in the future 16:34 more just 16:34 require digital literacy learning in 16:37 demand skills is the best way 16:39 to stay resilient and future-proof your 16:41 career 16:42 the world economic forum has published a 16:44 report 16:45 stating that technology design and 16:47 programming is the most 16:49 valuable job skills and its demand is 16:51 expected to grow till 2022 16:54 therefore there is no better time than 16:56 now to pick up new skills 16:58 ais singapore has developed courses to 17:00 help you get started on ai 17:02 you are currently watching the abridged 17:04 version of af for everyone 17:06 if you are keen to learn more you can 17:08 watch our full version on our website 17:11 it is a three hours long program 17:13 comprising of theory 17:14 and hands-on to build a simple ai model 17:18 those who are keen to advance further 17:20 can register for our ai for industry 17:23 program 17:24 where you learn how to program in patent 17:26 programming language 17:27 and build air models from scratch are 17:30 the ai singapore 17:31 big names from the industry like 17:33 microsoft 17:34 google intel and amazon have also 17:38 developed courses 17:39 that educate people on ai no matter 17:42 which course you choose to take 17:44 they are all good and should get you 17:46 started on ai 17:47 now you might be wondering am i too old 17:50 to learn ai absolutely not let's watch 17:54 an inspiring video 17:55 by imda featuring kevin 18:00 does my future look like i always 18:02 imagine retiring 18:04 and traveling around the world that's 18:06 what i would say 18:07 if you asked me in the past now i'm an 18:10 ai consultant i help companies make use 18:13 of this new technology to improve their 18:15 business performance 18:16 and you know many companies they want to 18:18 use ai but they don't know how 18:20 so i give them advice and help them 18:22 explore opportunities 18:24 customers have problems to solve and we 18:27 have solutions for them 18:29 but of course it is not as simple 18:32 my name is kevin and as you can see i'm 18:35 not very young 18:36 and my colleagues are not very old but 18:38 if you think about it 18:40 we are the same we write code we wear 18:43 t-shirts and jeans to work 18:44 and we drink bubble tea except maybe for 18:47 the wrinkles 18:48 i spent more than 25 years in sales and 18:51 marketing 18:51 and it was very comfortable things like 18:54 checking code 18:54 i wouldn't know how to do this is where 18:57 i had my first technical interview 18:59 in the past i was the one interviewing 19:01 people but now 19:02 i was the one being interviewed it was 19:05 totally out of my comfort zone 19:07 during my time we usually have just one 19:10 professional skill 19:11 and that will see us through our entire 19:13 career 19:14 but now i have to learn technical skills 19:16 like python 19:18 r revise my math and many other things 19:21 i think passion is the most important 19:24 thing in 19:24 learning new skills let me show you 19:26 where we come up with all the good ideas 19:29 actually my ex-colleague asked me aren't 19:31 you afraid of going back to school 19:33 well this is nothing like school the 19:35 program 19:36 under the tesla initiative gave us 19:38 customers and real-life problems to 19:40 solve 19:41 and there were great mentors and 19:42 colleagues to work with 19:44 we were also given a stipend and that 19:47 financial support 19:48 allow us to focus on our training 19:51 so you ask me what my future looks like 19:54 there's so many possibilities 19:56 but i know it will be exciting and 19:58 bright 19:59 [Music] 20:01 and i'm just getting started 20:09 how was the video i find it very 20:12 inspiring and hope it is the same for 20:14 you 20:15 there are multiple job roles related to 20:17 ai but not all of them 20:18 requires coding skills they are 20:21 essential roles that support different 20:23 aspects of an ai project 20:25 they are jobs that support ai 20:27 development work such as a software 20:29 engineer 20:30 jobs that catalyze the commercialization 20:32 of an ai solution 20:34 like product manager and jobs that 20:37 ensure the data privacy 20:38 such as data protection officer 20:41 skillsfuture has a comprehensive skills 20:44 framework for infocomm technology job 20:46 roles 20:47 you can check their website for more 20:49 information on the skills required 20:51 for the various jobs in this sector here 20:54 is the recap of this last chapter 20:56 a job consists of multiple tasks ai 20:59 tasva 21:00 can only perform specific tasks that 21:02 they are trained to do 21:04 therefore they are unlikely to replace 21:06 our jobs 21:07 there are free online courses by ai 21:09 singapore and industry 21:11 which can help you get started this 21:13 means you can learn about ai at your 21:16 free time 21:16 without paying anything there are 21:19 multiple 21:20 career opportunities in the ai ecosystem 21:23 not all roles require you to be an 21:25 expert coder 21:27 you can find out more information about 21:29 each of the role and its requisite 21:31 from skills future website these bring 21:34 us to the end 21:35 of this three part series on ai for 21:38 everyone 21:39 multilingual version i hope you enjoy it 21:42 and become inspired 21:43 to learn about ai and perhaps
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Syllabus -see edx




A major geopolitical contest has broken out between America and China. It will be the main driving


force of global geopolitics for the next decade or two. The main goal of this MOOC, entitled US-


China relations: Past, Present and Future, is to deliver a deep understanding of the historical roots, the structural forces, the major misunderstandings and possible alternative policies that both drive and could drive the US-China relationship.




Week 1: Chinas Century of Humiliation vs Americas Century of Triumphalism


After an introductory video explaining the purpose and structure of the course, the remaining five


videos will explain how a major source of misunderstanding between America is a result of the different historical experiences of the two countries. Hence, in week 1, we will take a deep dive into their respective histories.

China suffered 100 years of humiliation from roughly 1840 to 1949. The key events included the


Opium War, the sacking of the Summer Palace, the Western Settlements in Shanghai, the Sino-


Japanese War, the May Fourth 1919 movement, the Japanese Occupation. This century of humiliation


was probably the worst century ever in China’s history. No one can understand contemporary China


without understanding the psychological impact of this century of humiliation.


America enjoyed a hundred years of triumphalism from roughly 1890 to 1990. The key events


included Teddy Roosevelts imperialist moves, the overtaking of Great Britain as the worlds number 1 economic power, the World War II victories, the landing on the moon, the explosion of the American middle class, the scientific breakthroughs, Silicon Valley and the end of the Cold War. This century was clearly the best century in Americas history.

It is important to understand these different mindsets of Chinese and American leaders if one wants to


understand the deeper sources of misunderstanding between China and the US.




Week 2: US-China relations: 1949 to 2020


Week 2 will first cover the three phases of US-China relations from 1949 to 2020. Phase 1 saw deep


hostility and direct conflicts between America and China from 1949 (the year of the founding of the


Peoples Republic of China (PRC) to 1971. This hostility should have continued between a Communist China and a Democratic America. Instead, with the surprise visit of Henry Kissinger to Beijing to meet Mao Zedong and Zhou Enlai in July 1971, two decades of close collaboration and partnership followed. The end of the Cold War and the June 4th 1989 Tiananmen Incident triggered







Phase III of the relations, which were characterized by ambivalence, with both cooperation and


competition at play between the two powers.


By 2020, it has become clear that a major geopolitical contest has broken out between America and


China. Initially, it appeared anchored to the trade war that President Trump launched in July 2018.


Soon it spread to other dimensions: technology, military, political. Strategic mistakes made by both sides have led to the eruption of this geopolitical contest. Chinas main mistake was to alienate one of its main supporting constituencies in America, the American Business Community. Americas main mistake was larger: it launched a major geopolitical contest against China without first working out a thoughtful and comprehensive long-term strategy, an insight Henry Kissinger passed to me personally when I had lunch with him in New York in March 2018. In so doing, America has ignored some key elements of geopolitical wisdom left behind by past American strategic thinkers, like George Kennan, who had formulated Ameri-cas strategy against the Soviet Union at the beginning of the Cold War.



Week 3: Fundamental misunderstandings between America & China


In Week 3, we will study in depth the fundamental misunderstandings that have developed be-tween America and China. It will build on a key strategic axiom provided by one of China’s greatest strategic thinkers, Sun Tzu. He said, If you know the enemy and know yourself, you need not fear the result of a hundred battles.”

America has ignored this advice in two critical respects. First, while it is aware of its strengths, it is


unaware of certain critical weaknesses it has developed. Second, while it is aware of Chinas


weaknesses, it is unaware of the great strengths China has developed. The goal of this week is to


develop a realistic understanding of each side’s strengths and weaknesses.


Most American believe that in a contest between a dynamic, flexible democracy and a rigid,


centralized communist party system, the democracy will always triumph, as demonstrated in Americas victory over the Soviet Union. Yet, new realities have emerged. America, as Martin Wolf has confirmed, has become a plutocracy, leading to a sea of despair among its working classes. China, by contrast, is run by a meritocracy. A meritocratic system can deliver better performances than a plutocracy.

America has also wasted trillions of dollars on excessive defense spending and fighting unnec-essary


wars in the Middle East. Can America make U-turns? Surprisingly, it cannot. By con-trast, China has


been prudent and careful in both these dimensions. It’s the only major power that hasnt fought a war


in forty years. Many Americans believe that America has to stand up to China because it has become


aggressive and militaristic. Actually, a study of the two thousand years of Chinas history reveals China prefers to avoid military conflicts. Chinas strategic culture discourages participation in wars, although it encourages preparing for them.






The goal of this weeks lectures is to develop a more objective and accurate understanding of the


actual behavior and behavioral patterns of America and China in the global order.




Week 4: Can America and China choose a better path?


The paradox of the geopolitical contest that has broken out between America and China is that it is both inevitable as well as avoidable. The inevitable dimension has been spelled out in the first three weeks. Week 4 will explain how this geopolitical contest can and should be avoided.

While there are 1.4 billion people living in China and 330 in America, there are still 6 billion people


living outside. In the Cold War that America launched against the Soviet Union, many countries


around the world joined Americas side, including the West Europeans and major Third World


countries, like Turkey, Iran, Egypt, Pakistan, Thailand, Indonesia and China. This time around, in the


contest against China, virtually no country has explicitly joined America’s side. By looking at case


studies of countries like Australia and Europe, India and Japan, this week will explain why America


will find it difficult to marshal a strong coalition against China. Instead, most countries of the world


are likely to develop closer trade and investment links with China and not take sides in the US-China geopolitical contest.

Bearing in mind all the points made above an in earlier weeks, this course will conclude by


recommending that a wiser course of action for America to take would be to realise that fundamen-


tally there are five non-contradictions between America and China. The term non-contradiction is not


often used in Western discourse. The Western mind is used to black-and-white distinctions. One side


is right; one side is wrong. The Chinese mind is different. Both black and white can be right, as


spelled out in the philosophy of yin and yang.


Hence, for example, if the primary goal of America is to improve the well-being of its people and if


China has a similar goal for its people, both sides can cooperate and fulfil their goals. Similarly, both sides share a common goal in overcoming global challenges, like global warming and Covid-19. Even in the area of values and civilizational differences, both sides can adopt a philosophy of live and let live.

The strategic goal of this course therefore is to enable the students to engage in deep reflection on this


major geopolitical contest that has broken out. Deeper reflection will show that a wiser course of


action for both sides would be to avoid an outright zero-sum geopolitical contest and thereby improve


the well-being of their own people and the six billion who live outside. In short, huge stakes are at


play in this contest. A course like this is absolutely critical and vital now.











Reading List




The following is the full reading list forUS-China Relations: Past, Present and Future. These


resources will complement the main video lectures for the course. The main text for this course will


be Has China Won? The Chinese Challenge to American Primacy. The necessary excerpts will be uploaded for all learners, and Verified Learners will get a soft copy of the full book. In addition, there will be a selected list of required and optional readings. Do read the required readings before the start of the week, except for those marked with an *, which you will read alongside the video lectures for the week. The optional readings are for further learning, and will build on the points made in the video lectures. Links for open-access to the readings will be provided. The longer readings will also have the key pages marked in red, if you do not have the time to read the entire reading. As you go through the course, do refer regularly to this list to ensure that you are on track with the readings.





    Has China Won? The Chinese Challenge to American Primacy


o Excerpts will be provided from pages which are part of the required reading


o Verified Learners will have access to a PDF of the full book


o A physical copy of the book can be bought at and all major bookstores




Week 1: Chinas Century of Humiliation vs Americas Century of Triumph




    *Monique Ross and Annabelle Quince, Modern China and the legacy of the Opium Wars,”


ABC, 2 September 2018,



    *Harold Evans, The 20th century belongs to America,” Irish Times, 20 September 1999,





    Angus Maddison, Chinese Economic Performance in the Long Run: 960-2030 AD,”


Development Centre Studies, OECD, 2007


o Accessible at o Read pages 15-20





    Alison Adcock Kaufman, The Century of Humiliation, Then and Now: Chinese


Perceptions of the International OrderPacific Focus 25, no. 1 (2010): 1-33.


o A summary can be read at

    Ezra F. Vogel, China and Japan: Facing History, Cambridge: Harvard University Press, 2019. o Chapter 3: Responding to Western Challenges and Reopening Relations, 1839-1882.

Pp. 65-99.


o Chapter 7: Political Disaster and the Road to War, 1911-1937. Pp. 203-247.       China’s Century of Humiliation - documentary


    Fairbank, John K. "" American China Policy" to 1898: A Misconception." Pacific Historical Review 39, no. 4 (1970): 409-420.

    Luce, Henry R. "The American Century." Diplomatic History23, no. 2 (1999): 159-171. o Accessible at o Read pages 167-171




Week 2: US-China relations: 1949 to 2020




    Has China Won (HCW)


o Chapter 1: Introduction


*Read excerpt: ten unthinkable questions for the US”


o Chapter 2: China’s Biggest Strategic Mistake


Read pages 25-38


    Campbell, Kurt M., and Ely Ratner. "The China reckoning: how Beijing defied American


expectations." Foreign Aff. 97 (2018): 60-70.


o Can be accessed at 20china%20reckoning.pdf

    Mike Pompeo, Communist China and the Free World’s Future, 23 July 2020













    Di, He. "The most respected enemy: Mao Zedong's perception of the United States." The


China Quarterly 137 (1994): 144-158.


    Cohen, Warren I. America's response to China: a history of Sino-American relations.


Columbia University Press, 2019.


o Chapter 8: Rapprochement – At Last


    Skidmore, David, and William Gates. "After Tiananmen: The struggle over US policy toward


China in the Bush administration." Presidential Studies Quarterly 27, no. 3 (1997): 514-539.      Jisi, Wang, and Hu Ran. "From cooperative partnership to strategic competition: a review of

ChinaUS relations 2009–2019." China International Strategy Review 1, no. 1 (2019): 1-10.


    Mike Pence, Remarks by Vice President Pence on the Administrations Policy Toward


China, October 4, 2018,




    Michael Posner, “Weiqi: The game that holds China's key to world domination.” The Globe


and Mail, 10 June 2011.




    Stephen Roach and Shan Weijian, The Fable of the Chinese Whistleblower, Project






o can also be accessed at

    Henry Kissinger. On China. New York: Penguin Press, 2011.





Week 3: Fundamental misunderstandings between America & China






o The Assumption of Virtue


Read pages 183-192


o Should China Become Democratic?


Read pages 152-162


o *Memo to Comrade Xi excerpt


    John Mearsheimer,Introduction,” In George Kennan, American Diplomacy, 1900-1950







o An excerpt can be found at

o Read pages xvi-xxviii


    Marvin Zonis, The Faltering Veil of Legitimacy in the United States.


o Accessible at

    Cunningham, Edward, Tony Saich, and Jessie Turiel. Understanding CCP Resilience:


Surveying Chinese Public Opinion Through Time. Ash Center for Democratic Governance


and Innovation (2020).


o Accessible at


o Read pages 1-4








    Martin Gilens and Benjamin I. Page,Testing Theories of American Politics: Elites, Interest


Groups, and Average Citizens,” Perspectives on Politics 12, no. 3 (September 2014): 564–




o Accessible at

o Read concluding section, American Democracy?


    Alexander Hertel-Fernandez, Theda Skocpol, and Jason Sclar, When Political Mega-Donors


Join Forces: How the Koch Network and the Democracy Alliance Influence Organized U.S.


Politics on the Right and Left,” Studies in American Political Development 32, no. 2 (2018):




o Accessible at


o Read pages 75-77


    Jean Fan, The American Dream is Alive in China,” Palladium Magazine, October 2019.


    Pankaj Mishra, Flailing States, London Review of Books, 16 July 2020,









    Joseph Stiglitz, How Did China Succeed?, 14 September 2018,




Week 4: Can America and China choose a better path?






o Chapter 8: How will other countries choose?


o Conclusion


    Dino Djalal, Why Trumps Anti-China Policy Falls on Deaf Ears in Southeast Asia, The


Diplomat, 15 October 2020.

    Fuying, Cooperative Competition Is Possible Between China and the U.S.” New York Times,


24 November 2020,


    Kanti Bajpai, China and India: A New Diplomacy, Asian Peace Programme, 01 July 2020,


    Michael Vatikiotis, The Biden Era: challenges and opportunities for Southeast Asia,” Asian


Peace Programme, 21 November 2020,






    Wang, Jisi, "Marching Westwards: The Rebalancing of China’s Geostrategy." In The World


in 2020 According to China, pp. 129-136. Brill, 2014.


    Lee Hsien Loong, "The Endangered Asian Century." Foreign Aff. 99 (2020): 52.




    Gideon Rachman, A new cold war: Trump, Xi and the escalating US-China confrontation”


Financial Times, 5 October 2020.




    Hugh White, America or China? Australia is fooling itself that it doesn't have to choose,


The Guardian, 26 October 2017,

    Chas Freeman, After the Trade War, a Real War with China?”, 12 February 2019,







    Allison, Graham. Destined for war: Can America and China escape Thucydides's trap?.


Houghton Mifflin Harcourt, 2017.


o For excerpts, see and . See also

    Martin Jacques, From Follower to Leader: The Story of China’s Rise, 21 September 2021,

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