Science 3 min read

Can Quantum Cognition Explain our Bad Decisions?

MattLphotography /

MattLphotography /

Humans, by nature, are smart. But, we still make foolish or let’s say irrational decisions.

Why’s that?

Some scientists think the answer to this question is quantum physics-based.

The laws that govern the behavior of objects on a microscopic scale could help shed new light on the human decision-making process.

Quantum Cognition: the “Uncertain” Human Behavior

We tend to make the wrong decisions, even when we have all the facts and know for sure what the outcome would be.

No one is perfect. Our “intelligence” could fail us sometimes, and we end up making all kinds of wrong decisions.

You do your homework, go through a reasoning process, and weigh up your options before coming to the final decision. And yet you still can miss the correct choice.

At the crossroads between quantum physics and psychology, quantum cognition is an emerging discipline that may help us explain the fallacies of the human cognition machine.

Some physicists and cognitive scientists are working to develop a quantum approach to the study of human cognition. Researchers are investigating how quantum physics concepts can offer better mathematical frameworks than classical theories of decision-making.

According to B.F Skinner’s operant conditioning, or classic reinforcement learning, humans learn through reward and punishment. This also affects our decision-making.

The decisions we make could involve “reward” or “punishment,” either literal or figurative. In reality, however, people can’t always make subjective, seemingly simple decisions.

Researchers at the University of Science and Technology in China have tested Quantum Reinforcement Learning (CRL) on human decision-making. They think human decision-making fallibility can be explained by “quantum uncertainty.”

In quantum mechanics, the uncertainty principle states that you can never predict what happens in the subatomic world.

The researchers believe QRL models outperform CRL models in predicting human behavior, and they designed their study to prove this was the case. They asked subjects to perform the Iowa Gambling Task, a game-like psychological test that uses cards to study decision making. MRI scans were produced to track the brain activity of subjects.

“In all groups, the QRL models performed well when compared with the best CRL models and further revealed the representation of quantum-like internal-state-related variables in the medial frontal gyrus in both healthy subjects and smokers, suggesting that value-based decision-making can be illustrated by QRL at both the behavioral and neural levels.”

The full result of the study (Quantum reinforcement learning during human decision-making) is published in the journal Nature Human Behavior.

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Zayan Guedim

Trilingual poet, investigative journalist, and novelist. Zed loves tackling the big existential questions and all-things quantum.

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