Algorithmic Foreign Policy

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Algorithmic Foreign Policy

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Last year, China unveiled its development of a new Artificial Intelligence system for its foreign policy. It’s called a “geopolitical environment simulation and prediction platform,” and it works by crunching huge amounts of data and then providing foreign policy suggestions to Chinese diplomats. According to one source, China has already used a similar AI system to vet almost every foreign investment project in the past few years.

Consider what this development means: Slowly, foreign policy is moving away from diplomats, political-risk firms and think tanks, the “go-to” organizations of the past. Slowly, foreign policy is moving toward advanced algorithms whose primary objective is to analyze data, predict events and advise governments on what to do. How will the world look when nations are using algorithms to predict what happens next?

Predicting the Next Episode of Social Unrest

Alongside China, the U.S. is also developing predictive capabilities. In fact, the nation’s capabilities have become so advanced that, according to the CIA, in some cases, they can predict “social unrest and societal instability” three to five days in advance. How might the U.S. apply this technology? One way could be to give its multinationals a “heads-up” on possible disruption.

For example, in early 2019 Chennai and several other Indian cities were hit by a series of water shortages. As the months passed, the crisis intensified, leaving millions without water. By June 2019, protests had begun, with hundreds of people being arrested in one incident. Certain political parties have also begun calling on people to protest. As the water shortage continues, could major social unrest follow? If the U.S. predicts it will, then the country may inform several of its companies operating in India.

Major tech companies might be told that major social unrest is about to begin in India in the next 48 to 72 hours. With such intelligence, these companies could take action, be it moving employees to safe areas, boarding up offices or shifting operations to parts of India that will be stable. This is one possibility. Companies might use the predictions to protect their footprint (that is, physical security or operations). And there’s another possibility: they might use the predictions for business.

For example, one of Uber’s largest markets is India. It may not want to shut down there. Instead it might view the freshwater shortage as a new business opportunity. The company could, say, launch a new service to deliver freshwater to people for a marked-up price. While Uber’s competitors, from other countries, might be disrupted by the social unrest, Uber could profit from it. And it could use those profits to reward drivers or provide water to people who can’t afford it.

By sharing predictions, U.S. companies could have “foresight” that helps them navigate complex geopolitical events. At the same time, people all over the world may become more dep

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