AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee – Here are my six lessons and takeaways

Artificial Intelligence – noun — the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

Machine LearningMachine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without that studywithout using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence.

 What is the point? — Artificial Intelligence is already here; and always/only getting “better.” Among many questions raised by this are: will China surpass the United States as the AI superpower? What will displaced people do; to survive; to thrive?

Artificial Intelligence is here, and getting bigger and better by the day/by the hour.  The job loss will be real for jobs of all-color-collars. This book helps us deal with the very real, real-world implications of the impact of these AI Superpowers.

“The future is coming.  And we’re not ready.” — Elle Hansen, Regeneration, Dallas, TX

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For those of us who constantly ask the question “what is going on?,” we try to keep up with the implications of Big Data, Artificial Intelligence, and Machine Learning.  But, for those of us who do not actually work in those spaces, we definitely need some help from those who can explain it to us.

Kai-Fu Lee + AI SuperpowersThe book AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee is one of those explainer books. And, it is a good one.

I presented my synopsis of this book at the March 1 First Friday Book Synopsis. As always, I ask: Why is this book worth our time?  Here are my three answers:

#1 – This book is a pretty good history of the rise of Artificial Intelligence.  It will help you understand what this means, and why it matters?
#2 – This book is a pretty good history of the modern business rise in China.  This is something we might need to pay a great deal of attention to.
#3 – This book raises the philosophical concerns that will arise as jobs are lost and people are left…foundering.  This is something we will definitely need to ponder.

Here are just a few of my favorite highlighted passages from the book:

AlphaGo runs on deep learning, a groundbreaking approach to artificial intelligence that has turbocharged the cognitive capabilities of machines.
Deep-learning-based programs can now do a better job than humans at identifying faces, recognizing speech, and issuing loans.
The threat to jobs is coming far faster than most experts anticipated, and it will not discriminate by the color of one’s collar, instead striking the highly trained and poorly educated alike.
That same job-eating technology is coming soon to a factory and an office near you.
Deep learning is what’s known as “narrow AI”—intelligence that takes data from one specific domain and applies it to optimizing one specific outcome. While impressive, it is still a far cry from “general AI,” the all-purpose technology that can do everything a human can.
That global shift is the product of two transitions: from the age of discovery to the age of implementation, and from the age of expertise to the age of data. … Much of the difficult but abstract work of AI research has been done, and it’s now time for entrepreneurs to roll up their sleeves and get down to the dirty work of turning algorithms into sustainable businesses.
The more examples of a given phenomenon a network is exposed to, the more accurately it can pick out patterns and identify things in the real world.  Given much more data, an algorithm designed by a handful of mid-level AI engineers usually outperforms one designed by a world-class deep-learning researcher. Having a monopoly on the best and the brightest just isn’t what it used to be.
Based on the current trends in technology advancement and adoption, I predict that within fifteen years, artificial intelligence will technically be able to replace around 40 to 50 percent of jobs in the United States. Actual job losses may end up lagging those technical capabilities by an additional decade, but I forecast that the disruption to job markets will be very real, very large, and coming soon.
Inequality will not be contained within national borders. …The AI world order will combine winner-take-all economics with an unprecedented concentration of wealth in the hands of a few companies in China and the United States. This, I believe, is the real underlying threat posed by artificial intelligence: tremendous social disorder and political collapse stemming from widespread unemployment and gaping inequality.
The physical automation of the past century largely hurt blue-collar workers, but the coming decades of intelligent automation will hit white-collar workers first.
The truth is that these workers have far more to fear from the algorithms that exist today than from the robots that still need to be invented.
In short, AI algorithms will be to many white-collar workers what tractors were to farmhands: a tool that dramatically increases the productivity of each worker and thus shrinks the total number of employees required. And unlike tractors, algorithms can be shipped instantly around the world at no additional cost to their creator. 

Here are some of my bullet points, pulled from reading the book: 

  • A short history of the arrival and development of Artificial Intelligence
  • The United States was the only game in town – (the story of the birth of deep learning took place almost entirely in the United States)
  • China entered with full energy and focus; The United States was no longer the only game in town; but was dominant
  • The United States is maybe still dominant; but, in some areas, only barely
  • The United States is no longer dominant
  • The United States will fall further behind
  • China and the United States are pretty close to the only games in town
  • The two “superpowers” in a Neural Network:
  • computing power
  • data – note, big data is really big; but, it has to be really big data to be really big! (and, note:  China wins the “big data” competition over the United States)
  • The four waves of Artificial Intelligence:
  • Internet AI – (your next streaming recommendation)
  • Business AI — (early, clustered in the financial sector)
  • Perception AI – (sensors; smart devices – the IoT)
  • Autonomous AI – (the Holy Grail)
  • Now, we are in the Age of Implementation – “This is the age of implementation” —
  • That global shift is the product of two transitions: from the age of discovery to the age of implementation, and from the age of expertise to the age of data.
  • Core to the mistaken belief that the United States holds a major edge in AI is the impression that we are living in an age of discovery…
  • The BIG Data belongs to China, because: more People = more Data
  • China leapfrogged right to mobile – and that was an enormous data accumulation advantage
  • from (no) credit cards direct to mobile pay
  • The threats:
  • the loss of jobs
  • the loss of meaning and purpose (because, our meaning is tied up with/in our work)
  • and, of course, the BIG threat:utopia vs. dystopia (Stephen Hawking; Elon Musk)
  • Solutions:
  • Relax; there will be enough jobs. – (Probably not true…)
  • Retraining – we will not be able to do enough of this!
  • Job sharing
  • Universal Basic Income – Yes? No? Maybe? – Maybe a “hybrid,” with some kind of “compassion/human” requirements.
  • some form of guaranteed income may be necessary to put an economic floor under everyone in society. But if we allow this to be the endgame, we miss out on the great opportunity presented to us by this technology.

It seems to me that the two really big considerations are these:  #1, we really are in the Age of Implementation, not in the Age of Discovery.  And, #2, the bigger the data, the bigger the advantage. And that means the advantage goes to China, because China has more people, with far, far more people using mobile technology, thus adding to their big data advantage by the minute, every minute of every day of every week of every month of every year…

And, here are my six lessons and takeaways from the book:

#1 – All types of jobs are threatened by the ongoing progress of artificial intelligence.  We’d best get ready.
#2 – There are things that AI cannot do – human things.  We need to find ways to maximize such traits, and build new jobs around such traits.
#3 – The United States will likely lose the big battle over AI to China, because of the role of big data.  Note:  big data is bigger data with more people.
#4 – Don’t forget this:  work ethic, and desperation, play important motivational roles. — {A question:  will work ethic ultimately win out?}
#5 – Read this carefully, and ponder this: maybe we need big, big government roles in an age of AI.  (And, what will we think/decide about the Universal Basic Income strategy?)
#6 – There is very likely a coming threat of “emptiness.”  In other words, if we have defined our lives by our work, then…  We’d better get ready for this human dilemma!
#7 – And; AI will definitely exacerbate the “winners win all” reality.

I have read a number of books that try to explain what is happening in this era:  The Second Machine Age; Machine Platform Crowd; Thank You For Being Late, The Third Wave, Human + Machine, among others.  This is a worthy explainer volume to add to this list.

The world is changing.  The future is coming.  And we are not ready.  We’d probably better get much more ready, really soon.

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Click here to see a segment with the author, Kai-Fu Lee, from 60 Minutes.

Click here to view a TED Talk by Kai-Fu Lee.

(My synopsis, with the audio recording of my presentation, along with the multi-page, comprehensive synopsis handout, will be available for purchase soon from this web site).

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