Understanding human decision-making processes has traditionally relied on classical probability theories and Bayesian models, but these models have failed to fully comprehend the complexities of human thought. Quantum cognition is a revolutionary theory that applies the mathematical framework of quantum mechanics to human cognitive processes. This theory explains the extraordinary phenomena occurring in the human mind that cannot be understood through traditional probability theory, such as the observation effect, the concept of superposition, and the phenomenon of entanglement. This paper will present aspects of human decision-making in light of quantum cognition theory that go beyond classical Bayesian models.

Different possibilities coexist simultaneously in the human mind until one of them is given final form. This is the fundamental principle of quantum superposition. When we are about to make a decision, different options coexist in our minds, and only after the observation process does one possibility collapse. For example, when you are deciding whether to purchase a product, both possibilities of buying and not buying coexist in your mind. This is the state of superposition. When you make the final decision, this superposition collapses. This phenomenon cannot be understood through classical probability theory, where probabilities are considered mutually exclusive. Modern research reveals that this superposition in the human mind is not limited to simple decisions but also exists in complex decision-making scenarios.

Connections exist between different ideas and concepts in the human mind that work like quantum entanglement. Changing one idea affects other related ideas. For example, if you change your opinion about someone, other related ideas automatically change as well. This interconnection is overlooked in classical probability models, where every variable is considered independent. According to quantum cognition, this entanglement of concepts in our minds helps us make complex decisions. Neuroscience research reveals that these connections between brain neurons constantly change through synaptic plasticity.

Similar to quantum mechanics, probabilities also interfere in the human mind. When two different possibilities interact with each other, their overall probability differs from the sum of their individual probabilities. This is why our decisions sometimes are not based on linear probability patterns. For example, when we face simultaneous choices, their interaction affects our final decision, which cannot be predicted by classical probability theory. This interference effect becomes particularly evident when we are making decisions between conflicting information.

The effect of context is very important in quantum cognition. The same decision can emerge differently in different contexts. This point is overlooked in classical Bayesian models, which assume context-independent probabilities. For example, a person’s investment decision may depend on the overall mood of the market, not just on objective data. This context dependency resembles the measurement problem in quantum mechanics.

Human decision-making processes can be understood through linear time evolution, but according to quantum cognition, this evolution can sometimes be non-linear as well. Our thoughts and decisions sometimes undergo abrupt changes, similar to quantum jumps. This phenomenon is overlooked in classical models, which assume smooth transitions. Neuroscience studies reveal that the formation of ideas in our brain is sometimes gradual and sometimes emerges in the form of sudden insights.

Quantum cognition helps us better understand human behavior in ambiguous situations. When information is incomplete, the human mind works like quantum superposition, holding all possible interpretations simultaneously. This helps in understanding phenomena like the Ellsberg paradox, where people prefer options with clear probabilities over ambiguous options. Ambiguity tolerance is actually a measure of our mind’s capacity to process uncertain information.

Recent neuroscientific research suggests that the human brain’s operating mechanism might be something that resembles quantum processes. Patterns are observed in neurotransmitter release at synapses and communication between neurons that resemble quantum phenomena. This provides biological evidence for quantum models of cognitive processes.

According to quantum cognition, our past decisions affect our present decisions, just as a quantum system’s history affects its present state. This hysteresis effect is overlooked in classical probability models. For example, an investor’s past investment decisions affect their current risk tolerance, even if objective circumstances remain the same.

Quantum cognition better understands the phenomenon of cognitive dissonance. When two conflicting ideas exist in the mind, they behave like superposition, and when one idea is accepted, the other is automatically rejected. This process differs from classical logic, where different rules exist for resolving contradictions.

The human mind sometimes makes decisions through analogies, which work like quantum tunneling. To solve a problem, the mind tunnels a solution that doesn’t seem related on the surface. This is the fundamental mechanism of creative thinking, which goes beyond classical rational decision models.

Quantum cognition understands aspects of risk perception that cannot be understood through expected utility theory. Such as why people sometimes overestimate small probabilities and underestimate large ones. This probability weighting function can be modeled as quantum interference.

Human time discounting behavior can also be better understood through quantum cognition. We treat future rewards like quantum superposition in the present, where their value keeps collapsing over time. This better explains the phenomenon of hyperbolic discounting.

The principles of quantum game theory can be applied to human strategic decision-making. When players use quantum strategies, their results differ from classical game theory predictions, which are closer to actual human behavior.

Human pattern recognition can be modeled as quantum measurement. When we recognize a pattern, it resembles the collapse of a quantum state, where one of multiple possibilities becomes actuality. This process helps us understand why different people see different patterns in the same information.

The principles of quantum cognition can be used in artificial intelligence, behavioral economics, and clinical psychology. It can help us create more human-like AI systems, develop better economic models, and improve mental health treatments.

Quantum cognition opens a new path in the study of human decision-making. It provides us with a means to understand those complex phenomena that are beyond the reach of classical models. In the future, further research in this field can help us understand the mysteries of the human mind and better model our decision-making processes.