Artificial intelligence will behave differently in different cultures. Photo: Wikimedia Commons
Artificial intelligence will behave differently in different cultures. Photo: Wikimedia Commons

Chinese children will come home from school, show a photograph of their math homework to the home robot and get an immediate answer. Calculators may go the way of the abacus.

In high school, homework will become more complex. Students may be asked to write a paper on complex contemporary issues: How can we apply the wisdom of Confucius to solve current social problems? Is Jean-Paul Sartre’s existentialism relevant to modern China?

The artificial intelligence in the Chinese robot will probably give different answers than a French or American system, but all AI systems, regardless of cultural bias, will operate on the same (binary) logic.

Misunderstanding AI

Artificial intelligence is one of the most important and misunderstood sciences of today. Much of this misunderstanding is caused by a failure to understand its immediate predecessor – cybernetics. Both AI and cybernetics are based on binary logic, and both rely on the same principle for the results they produce: intent. The logical part is universal, the intent is culture-specific.

In the 1940s, a team of scientists headed by Norbert Wiener developed the first self-regulating and self-correcting systems. Wiener called it cybernetics, from the Greek word for “steersman”. The US military used the technology to develop the first guided missiles and in the 1950s, the technology became standard equipment in airlines – the automatic pilot.

Wiener and his team developed the required technology using digital (binary) rather than analog circuits. Most computers at the time were based on analog systems. As did most other computer scientists at the time, Wiener realized that digital systems were more precise and easier to program. By the 1960s nearly all computer design had moved to binary systems.

Boolean logic

One reason Wiener turned to digital systems was Boolean algebra. In the 19th century, English mathematician George Boole developed an algebra of classes based on binary choices – yes and no.

Boolean logic could be perfectly implemented in digital circuitry. An open binary gate would mean “off”, a closed binary gate would mean “on”. The idea was first proposed in the 1930 by Claude Shannon, the spiritual father of the Information Age. (Shannon also realized that a binary number or string of numbers could be used to symbolize anything, from letters and symbols to sounds and images.)

A textbook example of Boolean logic is this: If the symbol x represents a generic class of all “white objects” and the symbol y represents a generic class of all “round objects”, the symbol xy represents the class of objects that are both white and round.

In binary computing, Boolean logic is simply a sequence of yes or no/true or false choices. There is no “maybe” – unless “maybe” is conditional on another probability or likelihood. “If I get a raise, then I will buy a new car.” (Those familiar with ancient Chinese text The I Ching may see a parallel here; the “logic” of The I Ching is also based on binary choices and weighing options.)

IBM’s AI system Big Blue used Boolean logic to beat world chess champion Garry Kasparov. “If white opens with D4, then I will counter with C5.” The Chinese game of Go has many more possible moves than chess, but Google’s AlphaGo AI program defeated world champion Ke Jie. A computer beating the world champion at Go is impressive, but it’s not magic. AI can simply weigh and process more options faster than humans can.

Subjective logic

The rule of thumb in AI: Bigger is better. Bigger in this context means more data. And China with its 1.3 billion people is generating massive amounts of data, from the very mundane, such as consumer preferences, to the highly personal and sensitive, such as medical records and social attitudes. The power that comes from having valuable data on nearly a quarter of the world’s population (combined with being the world’s largest manufacturer) can only be imagined.

Consumer preferences, self-driving cars and logistics are still part of what we may call AI 1.0. Things become more complex when AI is applied to social, environment and ethical domains where values, judgment and intent come into play. The intent of a chess computer is straightforward – winning. AI applied to domains that impact the lives of a people involves issues that go beyond winning and losing.

We can only speculate on how Chinese AI will develop in the coming years, but we do know that the country has a deep reservoir of knowledge that will come into play.

Fiction and non-fiction

Jack Ma of China’s e-commerce giant Alibaba Group gave us a hint when he said in a recent interview: “Every culture has its own religion. China’s religion originates from three branches – Taoism, Buddhism and Confucianism. The theme of Taoism is how to change yourself to be harmonious with the environment and nature. The theme of Buddhism is how to change your behavior to be harmonious with society and community. The theme of Confucianism is how to change yourself to be harmonious with society.”

Chinese students asking philosophical questions about work, life and society may get various answers, but if the deep roots of Taoism and Confucianism are any indication, Chinese AI will be “biased” toward the ancient Chinese way of reconciling binary opposites:

One should not be progressive or conservative; one should be both
One should not be materialistic or spiritual; one should be both
One should not be idealistic or realistic; one should be both

Regardless of how Chinese AI develops, it will be based on binary/Boolean logic (a point we may have to revisit if scientists succeed in merging analog and digital computing).

For now, Boolean logic is just that, a binary choice between multiple options. It can offer a surprising response; IBM’s Deep Blue made some moves the programmers did not anticipate, but it still acted within the binary/Boolean logic of the system. If an AI system is instructed to interpret facts, it will still rely on binary/Boolean logic.

Unless programmed to ignore the difference between fiction and non-fiction, AI will not make up non-existing facts, just as an autopilot will not fly an aircraft to a non-existing airport.

Jan Krikke

Jan Krikke is a former Japan correspondent for various media, former managing editor of Asia 2000 in Hong Kong, and author of Leibniz, Einstein, and China (2021).

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