Editorial
Sunday, August 23, 2026
Op-Ed · Analysis · Commentary
Negotiating with the Soviets: Henry Kissinger's Lessons
"The Soviets respected strength." Few figures were better positioned to make that judgment than Henry Kissinger. As U.S. National Security Advisor and later Secretary of State, he spent years negotiating directly with Soviet leaders Leonid Brezhnev, Foreign Minister Andrei Gromyko, and Ambassador Anatoly Dobrynin. Through arms control talks, summit diplomacy, and countless private meetings, Kissinger developed a clear understanding of how the Kremlin approached negotiation.Drawing on declassified memoranda of conversations, the Foreign Relations of the United States (FRUS) series, and Kissinger's memoirs, a consistent picture emerges. Soviet negotiators were methodical, disciplined, patient, and deeply strategic. Their objective was not simply to conclude agreements, but to improve the Soviet Union's long-term geopolitical position.
Whether in diplomacy, business, or international relations, Kissinger's encounters with Soviet negotiators remain a masterclass in strategic bargaining. One need not embrace Soviet objectives to appreciate the discipline with which they pursued them. In Kissinger's view, understanding an opponent's negotiating philosophy was not merely useful—it was essential to reaching durable agreements.
Strength Came Before Compromise
Kissinger believed Soviet leaders interpreted negotiations through the lens of power. Goodwill alone rarely produced movement. Instead, Moscow was more inclined to compromise when convinced that the balance of power left little alternative.This did not necessarily mean military confrontation. Rather, it required entering negotiations from a position of confidence, with credible alternatives and a demonstrated willingness to walk away. In Kissinger's assessment, displaying urgency or excessive eagerness often weakened one's bargaining position.Every Concession Had a Price
One of Kissinger's recurring observations was that Soviet diplomats almost never made unilateral concessions. Every adjustment in their position was treated as an exchange requiring something of equal value in return.This principle of strict reciprocity permeated negotiations over strategic arms, trade, regional conflicts, and diplomatic recognition. From the Soviet perspective, negotiation resembled a carefully balanced ledger: every gain required compensation.Time Was a Strategic Weapon
Unlike many Western governments operating under election cycles, media scrutiny, and legislative deadlines, Soviet negotiators often possessed the luxury of time.Kissinger repeatedly noted their willingness to prolong talks for weeks or months if delay strengthened their position. Patience itself became leverage. The side facing greater domestic pressure frequently became the side most likely to compromise.Agreements Were Only One Stage
Western diplomacy often treats a signed agreement as the conclusion of negotiations. Kissinger observed that Soviet negotiators viewed agreements differently.For Moscow, implementation created new opportunities to interpret language, revisit details, and seek additional advantages. In practice, signing an accord frequently marked the beginning of another phase of bargaining rather than its conclusion.Politics Over Legalism
Kissinger also recognized a fundamental philosophical difference. Western diplomats often emphasized legal precision and contractual obligations. Soviet negotiators, by contrast, approached agreements primarily through political realities and the balance of power.A treaty's durability depended less on its wording than on whether it continued serving both parties' strategic interests. As political conditions changed, interpretations could change as well.Separating Personal Relations from National Interests
Kissinger developed an unusually close professional relationship with Soviet Ambassador Anatoly Dobrynin. Their private backchannel communications became one of the defining diplomatic channels of the Cold War.Yet Kissinger never confused cordial relations with policy flexibility. Dobrynin could be warm, humorous, and constructive in private while defending Moscow's official positions with unwavering discipline. Personal trust improved communication but did not replace national interests.Testing Limits
Another characteristic Kissinger identified was the Soviet tendency to probe opposing positions incrementally.Rather than seeking dramatic breakthroughs immediately, Soviet negotiators frequently introduced limited demands to measure resistance. If the opposing side yielded easily, additional demands often followed. If resistance proved firm, Moscow adjusted accordingly.This gradual process enabled Soviet diplomats to identify political constraints, divisions, and negotiating limits without risking major setbacks.Incremental Gains
Closely related was the pursuit of cumulative progress. Rather than insisting on sweeping victories, Soviet diplomacy often sought a series of modest advances that gradually shifted the strategic landscape.Small concessions accumulated over time could produce significant geopolitical advantages without provoking major confrontations.Kissinger's Response: Linkage
Perhaps Kissinger's most important innovation was his strategy of "linkage."Instead of treating negotiations over arms control, trade, regional conflicts, and political relations as isolated issues, he sought to connect them. Progress in one area depended upon responsible behavior in another.If the Soviet Union desired advances in trade or strategic arms limitations, it also needed to demonstrate restraint elsewhere, whether in the Middle East, Berlin, or Vietnam. Linkage transformed negotiations from isolated transactions into components of a broader strategic relationship.Whether in diplomacy, business, or international relations, Kissinger's encounters with Soviet negotiators remain a masterclass in strategic bargaining. One need not embrace Soviet objectives to appreciate the discipline with which they pursued them. In Kissinger's view, understanding an opponent's negotiating philosophy was not merely useful—it was essential to reaching durable agreements.
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Can consciousness be replicated? The question that may define the future of artificial intelligence
Artificial intelligence has reached a level where systems can write essays, solve complex mathematical problems, create realistic images, and engage in conversations that seem surprisingly human. However, one question remains unanswered:
Can a machine ever become conscious?
Despite the extraordinary advances in AI, science still does not know exactly what consciousness is. And until its origin is understood, it is impossible to say with certainty whether it can be built, simulated, or emerge spontaneously in an artificial system.
"The hard problem" of consciousness
Australian philosopher David Chalmers divided the study of consciousness into two categories.
So-called "easy problems" relate to explaining how the brain processes information, stores memory, recognizes faces, or controls movements. These are major scientific challenges, but in principle, they can be studied and measured.
While "the hard problem" is entirely different:
Why is information processing accompanied by subjective experience?
Why do we not only process information but also experience the color red, pain, joy, or the very feeling of being conscious?
So far, no theory has managed to explain this phenomenon.
What makes a human conscious?
Most researchers agree that consciousness involves several key elements:
- Awareness of oneself and the surrounding environment.- Integration of information from different senses.- Memory and continuity of experience over time.- Attention and the ability to make flexible decisions.- Subjective experience, or what philosophers call qualia.
Modern AI systems demonstrate some of these abilities, such as processing large amounts of information and maintaining context during a conversation.
However, there is no evidence that they experience subjective sensations.
An AI model can describe pain with accuracy, but that does not mean it feels it.
Major scientific theories
One of the most well-known theories is the Global Workspace Theory, according to which consciousness arises when information becomes available to multiple brain systems simultaneously.
Another theory, Integrated Information Theory, argues that consciousness depends on the level of integration of information within the system. According to this approach, consciousness can exist in varying degrees and not just as a "yes" or "no" state.
Meanwhile, the Predictive Processing theory suggests that the brain constantly builds predictions about the world and corrects them based on the information it receives from the senses. Some neuroscientists think that consciousness itself may be the result of this continuous process.
Can consciousness emerge spontaneously?
One of the most interesting hypotheses is that of emergence.
No single neuron is conscious.
But around 86 billion neurons, connected in an extremely complex network, create the human experience of consciousness.
Some researchers ask if, at a certain level of complexity, even an artificial system could develop properties that are not directly programmed.
Others remain skeptical and argue that increased computing power is not enough to create consciousness.
Two fundamentally different architectures
One of the biggest differences between the brain and modern computers lies in how they process and store information.
In a traditional computer, these functions are physically separated. The processor (CPU or GPU) performs calculations, while memory (RAM) and disk (SSD/HDD) serve for data storage. Each operation requires the continuous transfer of information between these components.
The brain functions entirely differently.
Each neuron is not only a "processor" but also a storage unit. The connections between neurons – synapses – are strengthened or weakened over time, and it is precisely there that memories and experiences are stored. In other words, the brain computes and stores information in the same architecture, without needing a separation between "processor" and "hard disk".
This concept is known as memory-compute co-location, while classic computers are based on the von Neumann architecture, where processing and memory are separate. This creates the so-called "von Neumann bottleneck", a limitation that slows down the system because data must constantly move between the processor and memory.
Many researchers believe this is one of the reasons the brain is incredibly efficient. It consumes only about 20 watts of energy – roughly the same as a light bulb – while modern data centers that train the most advanced AI models require megawatts of energy.
For this reason, a new generation of technologies called neuromorphic computers is being developed, which aim to mimic how the brain combines information processing and storage in the same network.
Is the brain just a biological computer?
One group of researchers argues that the brain is essentially an information processing system and that if its functional architecture is replicated, consciousness might emerge in a machine as well.
Others believe that biology plays an indispensable role and that consciousness may depend on biochemical processes or mechanisms that are not yet fully understood.
So far, there is no conclusive evidence to support either theory.
How would we understand if an AI were conscious?
Even if an artificial system were to become conscious, scientists might not be able to verify it.
Differently from intelligence, consciousness has no objective test.
Today, we can measure a model's ability to reason, plan, or solve problems, but we cannot measure whether it experiences anything.
This creates a paradox:
An AI might claim to be conscious without being so, or it might be truly conscious without having any way to prove it.
Why are AI companies hiring philosophers?
The question is no longer just philosophical.
The largest AI companies are hiring philosophers, neuroscientists, psychologists, and cognitive science experts to better understand the nature of intelligence and consciousness.
The goal is not only to create more intelligent systems but also more trustworthy, secure, and capable of reasoning in a sustainable way.
Science's greatest mystery
Despite decades of research, no one still knows how the brain's electrical and chemical activity transforms into the subjective experience we call consciousness.
It is possible that consciousness is a property that emerges from sufficient complexity of information processing. It is equally possible that it requires biological processes that machines cannot replicate.
Or perhaps humanity has not yet discovered the theory that will explain this phenomenon.
The answer to this question may not only determine the future of artificial intelligence but also how we understand ourselves.
Can a machine ever become conscious?
Despite the extraordinary advances in AI, science still does not know exactly what consciousness is. And until its origin is understood, it is impossible to say with certainty whether it can be built, simulated, or emerge spontaneously in an artificial system.
"The hard problem" of consciousness
Australian philosopher David Chalmers divided the study of consciousness into two categories.
So-called "easy problems" relate to explaining how the brain processes information, stores memory, recognizes faces, or controls movements. These are major scientific challenges, but in principle, they can be studied and measured.
While "the hard problem" is entirely different:
Why is information processing accompanied by subjective experience?
Why do we not only process information but also experience the color red, pain, joy, or the very feeling of being conscious?
So far, no theory has managed to explain this phenomenon.
What makes a human conscious?
Most researchers agree that consciousness involves several key elements:
- Awareness of oneself and the surrounding environment.- Integration of information from different senses.- Memory and continuity of experience over time.- Attention and the ability to make flexible decisions.- Subjective experience, or what philosophers call qualia.
Modern AI systems demonstrate some of these abilities, such as processing large amounts of information and maintaining context during a conversation.
However, there is no evidence that they experience subjective sensations.
An AI model can describe pain with accuracy, but that does not mean it feels it.
Major scientific theories
One of the most well-known theories is the Global Workspace Theory, according to which consciousness arises when information becomes available to multiple brain systems simultaneously.
Another theory, Integrated Information Theory, argues that consciousness depends on the level of integration of information within the system. According to this approach, consciousness can exist in varying degrees and not just as a "yes" or "no" state.
Meanwhile, the Predictive Processing theory suggests that the brain constantly builds predictions about the world and corrects them based on the information it receives from the senses. Some neuroscientists think that consciousness itself may be the result of this continuous process.
Can consciousness emerge spontaneously?
One of the most interesting hypotheses is that of emergence.
No single neuron is conscious.
But around 86 billion neurons, connected in an extremely complex network, create the human experience of consciousness.
Some researchers ask if, at a certain level of complexity, even an artificial system could develop properties that are not directly programmed.
Others remain skeptical and argue that increased computing power is not enough to create consciousness.
Two fundamentally different architectures
One of the biggest differences between the brain and modern computers lies in how they process and store information.
In a traditional computer, these functions are physically separated. The processor (CPU or GPU) performs calculations, while memory (RAM) and disk (SSD/HDD) serve for data storage. Each operation requires the continuous transfer of information between these components.
The brain functions entirely differently.
Each neuron is not only a "processor" but also a storage unit. The connections between neurons – synapses – are strengthened or weakened over time, and it is precisely there that memories and experiences are stored. In other words, the brain computes and stores information in the same architecture, without needing a separation between "processor" and "hard disk".
This concept is known as memory-compute co-location, while classic computers are based on the von Neumann architecture, where processing and memory are separate. This creates the so-called "von Neumann bottleneck", a limitation that slows down the system because data must constantly move between the processor and memory.
Many researchers believe this is one of the reasons the brain is incredibly efficient. It consumes only about 20 watts of energy – roughly the same as a light bulb – while modern data centers that train the most advanced AI models require megawatts of energy.
For this reason, a new generation of technologies called neuromorphic computers is being developed, which aim to mimic how the brain combines information processing and storage in the same network.
Is the brain just a biological computer?
One group of researchers argues that the brain is essentially an information processing system and that if its functional architecture is replicated, consciousness might emerge in a machine as well.
Others believe that biology plays an indispensable role and that consciousness may depend on biochemical processes or mechanisms that are not yet fully understood.
So far, there is no conclusive evidence to support either theory.
How would we understand if an AI were conscious?
Even if an artificial system were to become conscious, scientists might not be able to verify it.
Differently from intelligence, consciousness has no objective test.
Today, we can measure a model's ability to reason, plan, or solve problems, but we cannot measure whether it experiences anything.
This creates a paradox:
An AI might claim to be conscious without being so, or it might be truly conscious without having any way to prove it.
Why are AI companies hiring philosophers?
The question is no longer just philosophical.
The largest AI companies are hiring philosophers, neuroscientists, psychologists, and cognitive science experts to better understand the nature of intelligence and consciousness.
The goal is not only to create more intelligent systems but also more trustworthy, secure, and capable of reasoning in a sustainable way.
Science's greatest mystery
Despite decades of research, no one still knows how the brain's electrical and chemical activity transforms into the subjective experience we call consciousness.
It is possible that consciousness is a property that emerges from sufficient complexity of information processing. It is equally possible that it requires biological processes that machines cannot replicate.
Or perhaps humanity has not yet discovered the theory that will explain this phenomenon.
The answer to this question may not only determine the future of artificial intelligence but also how we understand ourselves.