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AI Superpowers: China, Silicon Valley, and the New World Order
GLOBAL AFFAIRS & ECONOMICS

AI Superpowers: China, Silicon Valley, and the New World Order

An analytical examination of how artificial intelligence is changing the balance of power throughout the world by reexamining the competition between the Chinese and Silicon Valley.

AI Superpowers: China, Silicon Valley, and the New World Order
Manufacturer Kai-Fu Lee
Device Category Technology, Artificial Intelligence, Geopolitics, Nonfiction Critical Analysis
Key Innovation Data Beats Discovery Phase
Market Impact Globally Paradigm-Shifting.
Analysis Reading Time 7 Minutes Deep Dive
Release Date Sep 25, 2018
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In recent years, artificial intelligence has gone from being a specialist branch of technology to becoming one of the driving forces of global power. Governments, corporations and research institutions have now come to recognize the transformative potential of AI as a technological innovation tool and as a strategic asset, one that can allow them to redefine economic leadership and geopolitical influence. In his book AI Superpowers: China, Silicon Valley, and the New World Order, Kai-Fu Lee delivers a compelling analysis on how two players, the United States and China, have been emerging in the world of AI as the go-to powerhouses. Rather than providing an algorithmic and software-focused refresh, Lee takes a new, macro look at the ecosystem all around artificial intelligence: data, entrepreneurship, government policy, and cultural attitudes towards innovation. 

Silicon Valley: AI Innovation Hub of the World

For decades, Silicon Valley is in the core of technological development. Many of the breakthroughs that shaped modern artificial intelligence - from early research in machine learning to the massive internet modern and technology platforms such as - originated in American universities and tech companies. Companies like Google, Facebook and Microsoft built the infrastructure on which massive amounts of data could be collected and processed in order for machine learning systems to evolve and develop at a rapid pace.  

Lee stresses that the United States was able to dominate the field of AI research at the beginning of its development by virtue of its academic institutions and it's venture capital system and a culture of experimentation. Silicon Valley fostered risk-taking and innovation, and allowed startups to rapidly amount to global technology giants. In this environment, artificial intelligence became embedded in the search engines, social media platforms, and digital advertising systems.  

But Lee also suggests that being a leader in the early years does not ensure long-term control. The next stage of the AI race relies less on theoretical research work and more on the capacity to deploy AI systems at massive scale-something that China has proven to be most competitive in.  

The Engineering Wins

China's sudden emergence in artificial intelligence surprised many observers in the technology world. Within a relatively short time frame, it was Chinese companies like Baidu, Alibaba, and Tencent that built ecosystems that can compete directly with American technology companies. What made this transformation possible was not just technological capability, but the structure of China's digital economy, which is unique. 

 

Chinese platforms produce extraordinary amounts of data from daily behaviors, i.e., payments, transportation, e-commerce. This huge information environment is great training material for machine learning systems. Contrasting the early American emphasis on academic research, in China often the focus is on quick implementation. Startups test things rapidly and copy things that work and then scale them to huge numbers of users.  


Lee says that this data-rich environment enables Chinese AI firms to optimize their systems based on feedback in the real world with remarkable speed. The end effect is an ecosystem where innovation is being produced not only out of the labs, but in the body of everyday digital interactions. This model, according to Lee, has helped China narrow the technological gap faster than average with Silicon Valley.  

The Hard Truths

Artificial intelligence is no longer a technology industry. Governments increasingly view it as a strategic capability that has implications for economic development and for national security and international influence. Lee's analysis indicates the competition between China and the United States is becoming a larger battle for technological leadership in the twenty-first century.  


In the fields of financial markets, logistics networks, healthcare systems, and military technologies, AI systems play a role. Nations that manage to integrate AI into these sectors might benefit, in the long run, from some economic advantages. At the same time, the rapid automation that corresponds with AI has the potential to reshape labor markets across the entire planet, forcing societies to reconsider jobs, school and economic policy.  


The geopolitical ramifications are great. Just as industrial power was who determines global influence in the nineteenth century and nuclear technology defined the Cold War, artificial intelligence may be one of the defining strategic assets of the modern era.  

One of the most striking pieces of Kai-Fu Lee's argument is that it will not be important who ever invents new algorithms in order to dominate AI, but who controls the largest and most active data ecosystems. In other words, the advantage might go to the societies who are able to generate, collect, and apply massive amounts of real-world data on a scale.  

The Human (Cost) and the Search for a New Economy Model

While much of Lee's book is concerned with the role of technological competition, he also raises concerns about the social consequences of artificial intelligence. Automation threatens to eliminate large areas of routine work, from manufacturing jobs to administrative positions. As AI systems become more capable, entire industries may become transformed by them.  


Lee says that societies need to be preparing for this transition now. Education systems may need to focus on creativity, empathy and complex problem-solving - things which are still really hard for machines to replicate. Some policymakers have also started talking about some new economics, such as universal basic income or other versions of social support as possible responses to mass automation.  


At its most fundamental level, however, Lee's argument is not strictly technological but human in character. Artificial intelligence will change economies and political structures, but how the future will turn out depends on how societies decide to adapt. The actual challenge is not only how to write powerful algorithms, but to ensure that technological progress benefits humankind in general.  

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