AI Superpowers by Kai-Fu Lee

AI Superpowers by Kai-Fu Lee

Deep learning will eliminate many jobs that were once considered safe from automation. White collar, blue collar… every profession will feel the impact before the year 2039.

Machines powered by artificial intelligence have excelled at games for decades. IBM’s Deep Blue defeated chess champion Garry Kasparov in 1996. Alphabet’s AlphaGo defeated world champion Go player, Ke Jie, in 2017.

Game-focused AI is highly specialized and mostly ineffective in in other areas. What about general purpose AI, software that can mimic human intelligence and make human-like decisions? What about applications beyond games?

Dr. Kai-Fu Lee examines these questions in his book, AI Superpowers: China, Silicon Valley, and the New World Order. Lee draws on his background as a pioneering AI researcher and successful entrepreneur to explain why certain subsets of AI produce results, and how readers of the book might benefit.

Rules, Neural Nets, and Deep Learning

In their quest to mimic human intelligence, AI researchers in the 1980s pursued two main paths.

Neural networks fell out of favor in the 1990s because computer hardware was not powerful enough to make them work well. However, the technology has recently re-emerged under a new moniker, deep learning networks.

The most advanced deep learning networks learn from each other. For example, AlphaGo Zero, a newer version of the system that beat the human Go champion, learned to play the game by competing against other instances of itself. As with humans, the toughtest competitors emerge from the fiercest battles.

Deep Learning Re-Emerges

Of all the AI subsets, Lee believes that deep learning will generate the largest ROI in the next few years. His belief is based on decades of experience and these observations: Today, our computers are powerful enough and our algorithms are good enough.

Advancements in computer vision and speech recognition have given our machines new ways to collect massive amounts of data. Cameras are cheap and ubiquitous. Speech recognition is so inexpensive and so good that Amazon/Google can give it away for (almost) free and turn a profit when customers buy goods through the voice interfaces. And let us not forget the data. Deep learning needs massive amounts of data in order to work. Data collected by so many cameras and microphones is more valuable than petroleum.

Deep Learning and Human Careers

Deep learning will wreak havoc with careers. Human jobs that require pattern recognition will be replaced by deep learning tools. For example:

Bottom line: Deep learning will eliminate (or drastically alter) many professions that were once considered safe from any sort of mechanical automation. Lee predicts that 40% of jobs worldwide will be displaceable by deep learning and related technologies by 2039.

Deep Learning in China

As the founder of a VC firm operating in China, Lee offers some interesting thoughts about how Chinese companies will perform in an era of deep learning.

Deep learning thrives when given two key resources: Processing power and large amounts of data. The processing power is here, today. But data can be tougher to get, especially in the United States where privacy concerns are part of the culture.

But in China, the data required to train deep learning algorithms is plentiful and largely untethered by privacy laws. Algorithms designed to learn from Chinese consumer behavior have plenty of data - a big advantage. Lee shares examples of companies, based in China, that were once considered imitators of their US-counterparts. But in most cases, the Chinese company has grown larger than the US company it formerly emulated, thanks to deep learning and a mountain of data.

People Displaced by Deep Learning? What’s Next?

Revisiting the concern about displaced careers: Since we know that the wave of deep learning is coming, what should we do?

Some people will argue that we’ve been through changes like this before. Whenever humans develop new, labor-saving technology, new jobs emerge that we never would have dreamed of before. How many readers of this blog work in careers that didn’t exist twenty years ago?

Lee argues that the deep learning wave will be different in two ways:

Even deeper, so many of us, especially in the USA, define ourselves by our careers. What will it mean to be human when career-based definitions have evaporated?

Lee observes that the shift may give us an opportunity to connect with a uniquely human gift in new and positive ways. Lee believes that we will re-connect with our ability to love.

Lee shares more about the path that led to this way of thinking in the book.

About Kai-Fu Lee

For deeper insight into AI Superpowers, it might be helpful to know more about the author.

Dr. Kai-Fu Lee is a PhD computer scientist and founder of Sinovation Ventures, a $2 billion technology investment firm with offices in Beijing, Shanghai, Shenzhen, Seattle, and Silicon Valley.

Lee was born in China. He was sent to the USA at the age of eleven because his mother wanted him to be educated beyond the rote memorization curriculum that was available in the town of his birth. To maintain his Chinese writing skills, Lee’s mother required him to write to her weekly in Chinese. And she would return each of his letters to him with corrections. Motherly encouragement paid off. Today, Lee is fluent in Chinese and English and he flows easily between the cultures.

Lee holds degrees in Computer Science from Columbia University (A.B.) and Carnegie Mellon (PhD). He pioneered speech recognition research at Apple. Later, he served in technical leadership positions at SGI, Microsoft, and Google. He founded Sinovation Ventures in 2009.


AI Superpowers offers insights that go beyond technology. The author considers economic, social, and emotional concerns that are rarely discussed in a business book. Anyone interested in AI, business, or the interaction between Chinese and American industries will find the book valuable.