Dr Michele Piazzai, Senior Lecturer in Creative Industries at the University of Edinburgh Business School, has co-authored new research that uses quantum logic to explain how people reason and make decisions. The study describes a mathematical framework that models human thought more accurately than traditional logic in complex and uncertain situations.
A man in a suit sits at a boardroom table, hand to face, deep in thought, with a TV visible in the background.

The study, co-authored by Dr Michele Piazzai and published in Synthese, explores how quantum logic, a mathematical framework inspired by quantum physics, can help explain how people think. Unlike classical logic, which treats statements as simply true or false, quantum logic allows for uncertainty and interaction between ideas. This flexibility makes it better suited to modelling the nuance and context of human reasoning.

By bridging logic, psychology and decision theory, the research provides a new foundation for understanding how people think and how organisations can design better tools for analysing behaviour and decision-making.

Dr Piazzai worked with colleagues at Complutense University of Madrid and the National University of Distance Education (UNED) in Madrid. Together, they argue that quantum logic can capture reasoning patterns that classical models cannot, such as shifts in opinion depending on question order, context-sensitive decisions and the way uncertainty disappears once people commit to a choice.

People rarely think in ‘classically’ rational terms. We form opinions on the fly based on whatever information is at hand, and our choices often depend on how questions are ordered or framed. Classical logic can’t capture that complexity. Quantum logic provides a mathematical framework for describing these patterns, helping us understand how thought evolves before a decision is made. This has real implications for fields such as marketing, research design and policy where understanding how people reason is critical to predicting behaviour.
Michele Piazzai, Senior Lecturer in Creative Industries

Why it matters

The research has practical implications across business, marketing and data science.

  • Improving research design: Quantum-informed models can help researchers anticipate how question order and context influence responses.
  • Supporting better decisions: People often combine information in ways that defy classical probability. Quantum logic provides a structure for modelling how confidence and preferences evolve under uncertainty.
  • Understanding language and branding: Ideas and meanings can behave like entangled concepts, helping explain how even distant associations between words, messages and brands affect consumer behaviour.
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Michele Piazzai

Senior Lecturer in Creative Industries