pMHCTCR

pMHCTCR stands for probabilistic model of human-computer interaction with a focus on trust and reliance. It is a theoretical framework used to understand how individuals develop and adjust their trust in automated systems, particularly in complex or critical environments. The model posits that trust is not a static attribute but a dynamic construct that evolves based on an individual's assessment of the system's performance, reliability, and predictability.

The core idea behind pMHCTCR is that humans continuously update their beliefs about a system's trustworthiness through a probabilistic reasoning process. This process involves observing system actions, comparing them to expected behaviors, and evaluating the consequences of relying on the system. The model incorporates factors such as the user's prior experience, the system's transparency, and the perceived risk associated with its failure.

When a system performs as expected, a user's trust might increase, leading to greater reliance. Conversely, unexpected or erroneous behavior can decrease trust and reduce reliance. The "probabilistic" aspect highlights that this assessment is often uncertain, with users assigning probabilities to different levels of system trustworthiness. This uncertainty influences decision-making, especially in situations where a wrong decision could have significant negative outcomes.

pMHCTCR has been applied in various fields, including aviation, medicine, and autonomous vehicle research, to design user interfaces that promote appropriate levels of trust and prevent automation complacency or over-reliance. Understanding these dynamics is crucial for developing safe and effective human-automation collaborations.