What is the main message of The Big Nine?

The power and perils of AI, the role of Big Tech, and the need for ethical decision-making in shaping our future.

How long does it take to read The Big Nine?

Reading time for The Big Nine varies, but you can read the Blinkist summary in just 15 minutes.

Is The Big Nine a good book? Is it worth reading?

The Big Nine is definitely worth reading. It provides eye-opening insights on AI and its impact on society.

Who is the author of The Big Nine?

Amy Webb is the author of The Big Nine.

The Big Nine Summary of Key Ideas and Review

Name: The Big Nine
Rating: 4.4 (135 reviews)
Author: Amy Webb

Introduction

What’s in it for me? Learn about the disturbing directions in which artificial intelligence is currently headed – and how humanity can change course before it’s too late.

If you’ve watched any science fiction movies or TV shows from the past few decades, then you’ve probably seen some dark visions of the future. In many of those visions, the downfall of humanity is brought about by the advancement of artificial intelligence or AI.

Broadly defined, AI refers to any computer program or system that can perform tasks that resemble acts of human intelligence. Some specific, present-day examples include recognizing objects, understanding speech and implementing strategies to accomplish goals, such as beating a person at a board game. AI can also refer to the field of research and development in which those programs and systems are created.

In these blinks, you’ll learn about AI in both senses of the term. After a look at AI’s current level of advancement and some of the most cutting-edge examples, you’ll meet the key players – the “big nine” corporations of the tech industry. Who are they? What do they want? Why do they want it? And where are they taking AI as a result?

In these blinks, you’ll receive answers to those questions. Along the way, you’ll also find out about

the ways in which AI has already achieved superhuman intelligence;
the competing visions of the world currently shaping the field of AI; and
the likelihood of some version of those dark sci-fi scenarios coming to pass.

Key idea 1 of 8

AI has been revolutionized by the development of deep neural networks.

Since the turn of the twenty-first century, AI has made remarkable progress. The key to this progress has been the development of deep neural networks or DNNs.

The precise mechanics of how these work are rather complicated, but the basic idea behind them is fairly simple. Somewhat similar to the human brain, a DNN consists of thousands of simulated neurons linked together and arranged into hundreds of complex layers. By sending and receiving signals to and from each other, these layers of neurons are able to do something called deep learning. That means they can teach themselves how to do things with little or no human supervision; they don’t have to be taught by their human creators, like computer programs of yore.

By harnessing the deep-learning power of DNNs, AI was able to defeat one of its longest-standing adversaries: the ancient Chinese board game of Go. Played with white and black stones on an open grid, this strategy game is even more complex than chess, despite its simple appearance. For instance, whereas chess has only 20 possible opening moves, Go has 361. And by just the second round of play, the possibilities balloon all the way up to 128,960!

Because of the game’s complexity, an AI Go program needs to be able to engage in very creative, responsive and on-the-fly strategic thinking to win a game against a skilled human opponent. For decades, such a victory was one of the primary benchmarks against which the power of AI was measured. And from the 1970s all the way through the early 2000s, AI failed to meet the mark, losing even to novices and children. The game was just too complex for it.

But then along came a start-up called DeepMind that specialized in deep learning and was acquired by Google in 2014. In that same year, the team from DeepMind deployed a DNN-powered program called AlphaGo against a professional Go player, Fan Hui. It beat him five games to zero. It then went on to play in tournaments, where it trounced every human opponent it encountered – including the reigning world champion!

The benchmark of winning at Go had finally been reached, and the incredible deep-learning powers of DNNs had been dramatically demonstrated. But as you’ll find out in the next blink, AlphaGo was just a taste of things to come.

Key idea 2 of 8

AI is already beginning to achieve superhuman intelligence.

As remarkable as it was at the time, the success of AlphaGo in 2014 has already been eclipsed by its successor, AlphaGo Zero, which debuted in 2017. To understand the key difference between the two programs, you need to understand a bit more about the DNNs that power them.

While a DNN is able to teach itself how to do something like playing Go without specific instructions from humans, it still needs learning material with which to work. For the original AlphaGo, that meant an initial data set of 100,000 previously played games of Go. By sifting through this library, AlphaGo was able to develop a sense of judgment about how to play.

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Key idea 3 of 8

The range and power of AI will increase exponentially over the course of the next 50 years.

Beating world champions at Go might be an impressive feat, but it’s also a pretty limited one. After all, those same champions don’t just know how to play Go; they can also tie their shoes, write love letters, formulate political opinions and do innumerable other things that humans can do. In contrast, a program like AlphaGo Zero does one thing very, very well – but only one thing: in this case, playing Go.

Given the narrowness of the domain in which it’s intelligent, such a program is called artificial narrow intelligence, or ANI. Applications of ANI already surround us in modern society; they include spam filters, voice transcribers, self-driving cars and virtual assistants like Apple’s Siri and Amazon’s Alexa, both of which are powered by DNNs.

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Key idea 4 of 8

There’s a brief window in which the future of AI will be shaped, primarily by actors in the United States and China.

As it evolves, AI will eventually develop a mind of its own: an ability to think about the world in a way that’s both independent of human input and distinctly non-human in the way it functions. We can’t predict exactly what that mind will evolve into, but we do know what it will evolve from: the AI systems being built right now.

That means we’re living in a pivotal period of history. From now until some time in the next two decades, our current AI research and development will shape the contours of the landscape on which the future of humanity will be built.

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Key idea 5 of 8

The US approach to tech research and development revolves around consumerism, profit-making and short-term thinking.

In an ideal world, AI would be harnessed toward lofty, humanistic goals – goals that have humanity’s best interests in mind, like curing cancer or alleviating poverty. Unfortunately, those are not the primary goals of current AI research and development, neither in the United States nor China.

Let’s start with the United States. Here, the government subscribes to an ideology of free-market capitalism. This entails a relatively hands-off, do-nothing approach to guiding the nation’s economy. To be sure, there’s some regulation and oversight, but there’s an absence of grand-scale, government-led economic planning, policy-making and nurturing of industries. Essentially, the market is left to its own devices.

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Key idea 6 of 8

China has a government-led tech industry that prioritizes AI and is aimed toward control and global domination.

China’s guiding ideology and its resulting tech-industry landscape contrast sharply to those of the United States. Instead of free-market capitalism, the Chinese government champions a hybrid form of socialism and capitalism. This features a relatively protected market presided over by a strong, centralized and authoritarian state.

As a result, China’s tech industry is largely shielded from foreign competition. That’s especially true of the industry’s “big three ”companies, each of which can be likened to an American counterpart: roughly speaking, Baidu is like Google, Alibaba is like Amazon and Tencent is like Facebook. Both Google and Facebook are banned from operating in China, and Amazon has been heavily impeded from gaining a foothold there.

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Key idea 7 of 8

The current course of AI development could lead humanity to a tremendous disaster.

What could happen if AI research and development were left to continue on more or less its present course?

The following answers are speculative, but one of their main premises is a pretty safe bet: in the not-too-distant future, sophisticated AI-powered apps, systems and devices will be intertwined with nearly every facet of human life, from stocking our refrigerators to finding our next date.

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Key idea 8 of 8

To safeguard the future of AI, the United States and its allies need to develop the right policies and international cooperation.

AI could provide us with tremendous benefits, but it could also lead us into many dangers. How do we ensure we can reap the former while avoiding the latter?

In the United States, the answer is clear: the country’s major tech companies need to reorient their AI research and development around humanistic values, prioritizing the pursuit of humanity’s best interests over corporate profit. For example, before releasing any new AI system to the market, companies should safely and thoroughly test them – not just to see if they work, but also to see if they would have any unintended negative consequences on society. In the near future, one way to do this could be to use existing AI to conduct simulations of the societal impact of new AI.

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