Failures are natural and unavoidable events in any form of interaction, especially in human-robot interactions (HRI). Throughout the literature, the definition and classification of failures are diverse, depending on the source and application domain. However, the tolerance to the aftereffect of these failures is low in teleoperation due to its unstructured application domains. One such type of failure is called human induced interaction failure. This is an interesting and often overlooked failure type, due to the perspective that robots are designed always to obey the instructions given by the human operators. Regardless of the degree of automation that the robot is equipped with. But what if the instructions provided are faulty, dangerous, or misleading. This paper addresses the above mentioned research gap. It introduces a framework based on the concept of Intelligent Disobedience (ID), derived from guide dog training methods, to manage human induced interaction failures in teleoperation scenarios.