False economy What’s in it for me? Understand what makes the

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.
As a result, US tech companies and their 
investors pursue their own projects with their 
own money, for their own objectives. And within 

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a free-market capitalist system, their main 
objective is simply increasing their profits.
To make money and keep their investors happy 
in the fiercely competitive and rapidly evolving 
tech industry, companies need to develop new, 
marketable goods as quickly as possible. 
Otherwise, their competitors will outflank them, 
and their customers and investors will send their 
money elsewhere.
As a result, US tech companies are pressured 
into taking a reckless, short-sighted approach to 
innovation. Locked into a frantic race to beat 
their competitors, they lack the time and 
incentives to fully vet their products and services 
before releasing them to the world. Crucial 
questions are left unanswered – questions like, 
could this product or service have a negative 
impact on society? And could it violate ethical 
standards?
The tech industry’s attitude toward these 
questions tends to be “build it first and ask for 
forgiveness later.” In other words, rush the 
product or service to the market and wait for the 
public to find out the consequences. If they turn 
out to be negative, well, just issue an apology 
and move on. The result has been a number of 
headline-grabbing stories in the news over the 
past few years, such as the Facebook–
Cambridge Analytica scandal of 2018, in which 
millions of Facebook users’ personal data were 
compromised.
With AI, the stakes are even higher, as we’ll see 
a little later. But first, we need to take a look at 
the Chinese tech industry to round out our 
picture of the political and economic landscape 
in which AI is developing.