Reconciling Irrational Human Behavior with AI based Decision Making: A Quantum Probabilistic Approach
This work tackles the problem of enhancing AI systems to better interact with humans by accounting for irrational behaviors, though it appears incremental as it adapts an existing quantum framework to a specific domain.
The paper addresses the challenge of modeling irrational human decision-making that classical AI systems cannot capture, proposing a quantum probabilistic approach to detect and predict cognitive biases for improved human-agent interaction.
There are many examples of human decision making which cannot be modeled by classical probabilistic and logic models, on which the current AI systems are based. Hence the need for a modeling framework which can enable intelligent systems to detect and predict cognitive biases in human decisions to facilitate better human-agent interaction. We give a few examples of irrational behavior and use a generalized probabilistic model inspired by the mathematical framework of Quantum Theory to model and explain such behavior.