Interactive systems based on Artificial Intelligence (AI) algorithms are raising new challenges, including establishing a bond of trust between users and AI. This trust must be calibrated to match the degree of reliability of AI in order to avoid over-trusting and under-trusting. However, trust is a subjective characteristic that is difficult to assess as it can vary from one person to another. This paper explores how it is possible to estimate the trust of users, especially through behavioral and physiological sensing. It also explains how, from trust assessment, it becomes possible to develop techniques for calibrating trust.