The Age of A.I. and Our Human Future

by Henry Kissinger

AI is not an industry, let alone a single product. In strategic parlance, it is not a “domain.” It is an enabler of many industries and facets of human life: scientific research, education, manufacturing, logistics, transportation, defense, law enforcement, politics, advertising, art, culture, and more. The characteristics of AI — including its capacities to learn, evolve, and surprise — will disrupt and transform them all. The outcome will be the alteration of human identity and the human experience of reality at levels not experienced since the dawn of the modern age.

The AI did not just process data more quickly than humanly possible; it also detected aspects of reality humans have not detected, or perhaps cannot detect.

The advent of AI obliges us to confront whether there is a form of logic that humans have not achieved or cannot achieve, exploring aspects of reality we have never known and may never directly know.

A novel human-machine partnership is emerging: First, humans define a problem or a goal for a machine. Then a machine, operating in a realm just beyond human reach, determines the optimal process to pursue. Once a machine has brought a process into the human realm, we can try to study it, understand it, and, ideally, incorporate it into existing practice.

In the fifteenth and sixteenth centuries, the Western world underwent twin revolutions that introduced a new epoch — and, with it, a new concept of the role of the individual human mind and conscience in navigating reality. The invention of the printing press made it possible to circulate materials and ideas directly to large groups of people in languages they understood rather than in the Latin of the scholarly classes, nullifying people’s historic reliance on the church to interpret concepts and beliefs for them. Aided by the technology, the leaders of the Protestant Reformation declared individuals were capable of — indeed, responsible for — defining the divine for themselves.

Because London, Amsterdam, and other leading cities declined to proscribe the spread of printed material, freethinkers who had been harried by their home governments were able to find refuge and access to advanced publishing industries in nearby societies.

During this Renaissance, or rebirth, of classical learning, societies produced art, architecture, and philosophy that simultaneously sought to celebrate human achievement and inspire it further. Humanism, the era’s guiding principle, aimed to foster individuals capable of full participation in civic life through clear thought and expression. These virtues, humanism posited, were cultivated through the humanities: art, writing, rhetoric, history, politics, and philosophy. Accordingly, Renaissance men who mastered these fields — Leonardo da Vinci, Michelangelo, Raphael — came to be revered. Widely adopted, humanism cultivated a love for reading and learning — the former facilitating the latter.

A machine-learning algorithm that improves a model based on underlying data, however, is able to recognize relationships that have eluded humans. As previously noted, such AI is imprecise in that it does not require a predefined relationship between a property and an effect to identify a partial relationship. It can, for example, select highly likely candidates from a larger set of possible candidates. This capability captures one of the vital elements of modern AI. Using machine learning to create and adjust models based on real-world feedback, modern AI can approximate outcomes and analyze ambiguities that would have stymied classical algorithms. Like a classical algorithm, a machine-learning algorithm consists of a sequence of precise steps. But those steps do not directly produce a specific outcome, as they do in a classical algorithm. Rather, modern AI algorithms measure the quality of outcomes and provide means for improving those outcomes, enabling them to be learned rather than directly specified.