We claim that ideas of etiquette can be expanded and utilized to facilitate, inform, and predict human-computer in- teraction and perceptions. By expanding on the qualitative model of etiquette proposed by Brown and Levinson we created a quantitative, computational model of etiquette that allows a machine to interpret and display politeness. This model was then embedded into a testbed and a series of experiments involving human task performance were completed to test various hypotheses related to the model. Relevant compliance data (e.g., accuracy, response time, attitudes, etc.) were obtained as dependent variables. The results show that the variables included in our model have important effects on subjects' decision making and performance in our experimental tasks. The results also demonstrate that variations in etiquette can result in objective, measurable consequences in human+machine performance.